Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities; Updates to the Quality Reporting Program and Value-Based Purchasing Program for Federal Fiscal Year 2024

AGENCY:

Centers for Medicare & Medicaid Services (CMS), Department of Health and Human Services (HHS).

ACTION:

Final rule.

SUMMARY:

This final rule updates payment rates, including implementing the second phase of the Patient Driven Payment Model (PDPM) parity adjustment recalibration. This final rule also updates the diagnosis code mappings used under PDPM, the SNF Quality Reporting Program (QRP), and the SNF Value-Based Purchasing (VBP) Program. We are also eliminating the requirement for facilities to actively waive their right to a hearing in writing, treating as a constructive waiver when the facility does not submit a request for hearing.

DATES:

These regulations are effective October 1, 2023, except for the amendments to §§ 411.15 and 489.20 in instructions 2 and 11, which are effective January 1, 2024.

FOR FURTHER INFORMATION CONTACT:

PDPM@cms.hhs.gov for issues related to the SNF PPS.

Heidi Magladry, (410) 786–6034, for information related to the skilled nursing facility quality reporting program.

Alexandre Laberge, (410) 786–8625, for information related to the skilled nursing facility value-based purchasing program.

Lorelei Kahn, (443) 803–8643, for information related to the Civil Money Penalties Waiver of Hearing.

SUPPLEMENTARY INFORMATION:

Availability of Certain Tables Exclusively Through the Internet on the CMS Website

As discussed in the FY 2014 SNF PPS final rule (78 FR 47936), tables setting forth the Wage Index for Urban Areas Based on CBSA Labor Market Areas and the Wage Index Based on CBSA Labor Market Areas for Rural Areas are no longer published in the Federal Register . Instead, these tables are available exclusively through the internet on the CMS website. The wage index tables for this final rule can be accessed on the SNF PPS Wage Index home page, at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.

Readers who experience any problems accessing any of these online SNF PPS wage index tables should contact Kia Burwell at (410) 786–7816.

To assist readers in referencing sections contained in this document, we are providing the following Table of Contents.

Table of Contents

I. Executive Summary

A. Purpose

B. Summary of Major Provisions

C. Summary of Cost and Benefits

D. Advancing Health Information Exchange

II. Background on SNF PPS

A. Statutory Basis and Scope

B. Initial Transition for the SNF PPS

C. Required Annual Rate Updates

III. Analysis and Responses to Public Comments on the FY 2024 SNF PPS Proposed Rule

A. General Comments on the FY 2024 SNF PPS Proposed Rule

IV. SNF PPS Rate Setting Methodology and FY 2024 Update

A. Federal Base Rates

B. SNF Market Basket Update

C. Case-Mix Adjustment

D. Wage Index Adjustment

E. SNF Value-Based Purchasing Program

F. Adjusted Rate Computation Example

V. Additional Aspects of the SNF PPS

A. SNF Level of Care—Administrative Presumption

B. Consolidated Billing

C. Payment for SNF-Level Swing-Bed Services

D. Revisions to the Regulation Text

VI. Other SNF PPS Issues

A. Technical Updates to PDPM ICD–10 Mappings

VII. Skilled Nursing Facility Quality Reporting Program (SNF QRP)

A. Background and Statutory Authority

B. General Considerations Used for the Selection of Measures for the SNF QRP

C. SNF QRP Quality Measures

D. Principles for Selecting and Prioritizing SNF QRP Quality Measures and Concepts Under Consideration for Future Years: Request for Information (RFI)

E. Health Equity Update

F. Form, Manner, and Timing of Data Submission Under the SNF QRP

G. Policies Regarding Public Display of Measure Data for the SNF QRP

VIII. Skilled Nursing Facility Value-Based Purchasing Program (SNF VBP)

A. Statutory Background

B. SNF VBP Program Measures

C. SNF VBP Performance Period and Baseline Periods

D. SNF VBP Performance Standards

E. SNF VBP Performance Scoring Methodology

F. Updates to the Extraordinary Circumstances Exception Policy Regulation Text

G. Updates to the Validation Process for the SNF VBP Program

H. SNF Value-Based Incentive Payments for FY 2024

I. Public Reporting on the Provider Data Catalog website

IX. Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

X. Waiver of Proposed Rulemaking

XI. Collection of Information Requirements

XII. Economic Analyses

A. Regulatory Impact Analysis

B. Regulatory Flexibility Act Analysis

C. Unfunded Mandates Reform Act Analysis

D. Federalism Analysis

E. Regulatory Review Costs

I. Executive Summary

A. Purpose

This final rule updates the SNF prospective payment rates for fiscal year (FY) 2024, as required under section 1888(e)(4)(E) of the Social Security Act (the Act). It also responds to section 1888(e)(4)(H) of the Act, which requires the Secretary to provide for publication of certain specified information relating to the payment update (see section II.C. of the FY 2024 SNF PPS proposed rule) in the Federal Register before the August 1 that precedes the start of each FY. In addition, this final rule includes requirements for the Skilled Nursing Facility Quality Reporting Program (SNF QRP) for the FY 2025 and FY 2026 program years. This final rule will add two new measures to the SNF QRP, remove three measures from the SNF QRP, and modify one measure in the SNF QRP. This final rule will also make policy changes to the SNF QRP, and begin public reporting of four measures. In addition, this final rule includes a summary of comments received in response to our request for information on principles we will use to select and prioritize SNF QRP quality measures in future years and on the update on our health equity efforts. Finally, this final rule includes requirements for the Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program, including adopting new quality measures for the SNF VBP Program, finalizing several updates to the Program's scoring methodology, including a Health Equity Adjustment, and finalizing new processes to validate SNF VBP data. We are also changing the current long-term care (LTC) facility requirements that will simplify and streamline the current requirements and thereby increase provider flexibility and reduce unnecessary administrative burden, while also allowing facilities to focus on providing healthcare to residents to meet their needs. This proposal was previously proposed and published in the July 18, 2019 Federal Register in the proposed rule entitled, “Medicare and Medicaid Programs; Requirements for Long-Term Care Facilities: Regulatory Provisions to Promote Efficiency, and Transparency” (84 FR 34718). We are finalizing this revision for a facility to waive its hearing rights and receive a reduction in civil money penalties. This change to the current LTC requirements will simplify and streamline the current requirements and thereby increase provider flexibility and reduce excessively burdensome regulations, while also allowing facilities to focus on providing high-quality healthcare to their residents.

B. Summary of Major Provisions

In accordance with sections 1888(e)(4)(E)(ii)(IV) and (e)(5) of the Act, the Federal rates in this final rule update the annual rates that we published in the SNF PPS final rule for FY 2023 (87 FR 47502, August 3, 2022). In addition, this final rule includes a forecast error adjustment for FY 2024 and includes the second phase of the PDPM parity adjustment recalibration. This final rule also updates the diagnosis code mappings used under the PDPM.

Beginning with the FY 2025 SNF QRP, we are modifying the COVID–19 Vaccination Coverage among Healthcare Personnel measure, adopting the Discharge Function Score measure, and removing the (1) Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function measure, (2) the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure, and (3) the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure. Beginning with the FY 2026 SNF QRP, we are adopting the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure. We are also changing the SNF QRP data completion thresholds for the Minimum Data Set (MDS) data items beginning with the FY 2026 SNF QRP and making certain revisions to regulation text at § 413.360. This final rule also contains updates pertaining to the public reporting of the (1) Transfer of Health Information to the Patient-Post-Acute Care (PAC) measure, (2) the Transfer of Health Information to the Provider-PAC measure, (3) the Discharge Function Score measure, and (4) the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure. In addition, we summarize comments received in response to the Request for Information (RFI) on principles for selecting and prioritizing SNF QRP quality measures and concepts and the update on our continued efforts to close the health equity gap, including under the SNF QRP.

We are finalizing several updates for the SNF VBP Program. We are adopting a Health Equity Adjustment that rewards top tier performing SNFs that serve higher proportions of SNF residents with dual eligibility status, effective with the FY 2027 program year and adopting a variable payback percentage to maintain an estimated payback percentage for all SNFs of no less than 60 percent. We are adopting four new quality measures to the SNF VBP Program, one taking effect beginning with the FY 2026 program year and three taking effect beginning with the FY 2027 program year. We are also refining the Skilled Nursing Facility 30-Day Potentially Preventable Readmission (SNFPPR) measure specifications and updating the name to the Skilled Nursing Facility Within-Stay Potentially Preventable Readmission (SNF WS PPR) measure effective with the FY 2028 program year. We are adopting new processes to validate SNF VBP program data.

In addition, we are finalizing our proposal to eliminate the requirement for facilities facing a civil money penalty to actively waive their right to a hearing in writing in order to receive a penalty reduction. We are creating, in its place, a constructive waiver process that will operate by default when CMS has not received a timely request for a hearing. The accompanying 35 percent penalty reduction will remain. This will streamline and reduce the administrative burden for CMS, and result in lower administrative costs for most LTC facilities facing civil money penalties (CMPs). The accompanying 35 percent penalty reduction will remain for now, although we plan to revisit this in a future rulemaking. The move to a constructive waiver process in this rule purely reflects the need to reduce costs and paperwork burden for CMS in order to prioritize current limited Survey and Certification resources for enforcement actions, and we continue to consider whether the existing penalty reduction is appropriate given this final policy. The operational change finalized here will streamline and reduce the administrative burden for CMS.

C. Summary of Cost and Benefits

D. Advancing Health Information Exchange

The Department of Health and Human Services (HHS) has a number of initiatives designed to encourage and support the adoption of interoperable health information technology and to promote nationwide health information exchange to improve health care and patient access to their digital health information.

To further interoperability in post-acute care settings, CMS and the Office of the National Coordinator for Health Information Technology (ONC) participate in the Post-Acute Care Interoperability Workgroup (PACIO) to facilitate collaboration with interested parties to develop Health Level Seven International® (HL7) Fast Healthcare Interoperability Resource® (FHIR) standards. These standards could support the exchange and reuse of patient assessment data derived from the post-acute care (PAC) setting assessment tools, such as the minimum data set (MDS), inpatient rehabilitation facility -patient assessment instrument (IRF–PAI), Long-Term Care Hospital (LTCH) continuity assessment record and evaluation (CARE) Data Set (LCDS), outcome and assessment information set (OASIS), and other sources. The PACIO Project has focused on HL7 FHIR implementation guides for: functional status, cognitive status and new use cases on advance directives, re-assessment timepoints, and Speech, language, swallowing, cognitive communication and hearing (SPLASCH) pathology. We encourage PAC provider and health IT vendor participation as the efforts advance.

The CMS Data Element Library (DEL) continues to be updated and serves as a resource for PAC assessment data elements and their associated mappings to health IT standards such as Logical Observation Identifiers Names and Codes (LOINC) and Systematized Nomenclature of Medicine Clinical Terms (SNOMED). The DEL furthers CMS' goal of data standardization and interoperability. Standards in the DEL can be referenced on the CMS website and in the ONC Interoperability Standards Advisory (ISA). The 2023 ISA is available at https://www.healthit.gov/sites/isa/files/inline-files/2023%20Reference%20Edition_ISA_508.pdf.

We are also working with ONC to advance the United States Core Data for Interoperability (USCDI), a standardized set of health data classes and constituent data elements for nationwide, interoperable health information exchange. We are collaborating with ONC and other Federal agencies to define and prioritize additional data standardization needs and develop consensus on recommendations for future versions of the USCDI. We are also directly collaborating with ONC to build requirements to support data standardization and alignment with requirements for quality measurement. ONC has launched the USCDI+ initiative to support the identification and establishment of domain specific datasets that build on the core USCDI foundation. The USCDI+ quality measurement domain currently being developed aims to support defining additional data specifications for quality measurement that harmonize, where possible, with other Federal agency data needs and inform supplemental standards necessary to support quality measurement, including the needs of programs supporting quality measurement for long-term and post-acute care.

The 21st Century Cures Act (Cures Act) (Pub. L. 114–255, enacted December 13, 2016) required HHS and ONC to take steps to promote adoption and use of electronic health record (EHR) technology. Specifically, section 4003(b) of the Cures Act required ONC to take steps to advance interoperability through the development of a Trusted Exchange Framework and Common Agreement aimed at establishing full network-to network exchange of health information nationally. On January 18, 2022, ONC announced a significant milestone by releasing the Trusted Exchange Framework and Common Agreement Version 1. The Trusted Exchange Framework is a set of non-binding principles for health information exchange, and the Common Agreement is a contract that advances those principles. The Common Agreement and the Qualified Health Information Network Technical Framework Version 1 (incorporated by reference into the Common Agreement) establish the technical infrastructure model and governing approach for different health information networks and their users to securely share clinical information with each other, all under commonly agreed to terms. The technical and policy architecture of how exchange occurs under the Common Agreement follows a network-of-networks structure, which allows for connections at different levels and is inclusive of many different types of entities at those different levels, such as health information networks, healthcare practices, hospitals, public health agencies, and Individual Access Services (IAS) Providers. On February 13, 2023, HHS marked a new milestone during an event at HHS headquarters, which recognized the first set of applicants accepted for onboarding to the Common Agreement as Qualified Health Information Networks (QHINs). QHINs will be entities that will connect directly to each other to serve as the core for nationwide interoperability. For more information, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.

We invite providers to learn more about these important developments and how they are likely to affect SNFs.

II. Background on SNF PPS

A. Statutory Basis and Scope

As amended by section 4432 of the Balanced Budget Act of 1997 (BBA 1997) (Pub. L. 105–33, enacted August 5, 1997), section 1888(e) of the Act provides for the implementation of a PPS for SNFs. This methodology uses prospective, case-mix adjusted per diem payment rates applicable to all covered SNF services defined in section 1888(e)(2)(A) of the Act. The SNF PPS is effective for cost reporting periods beginning on or after July 1, 1998, and covers virtually all costs of furnishing covered SNF services (routine, ancillary, and capital-related costs) other than costs associated with approved educational activities and bad debts. Under section 1888(e)(2)(A)(i) of the Act, covered SNF services include post-hospital extended care services for which benefits are provided under Part A, as well as those items and services (other than a small number of excluded services, such as physicians' services) for which payment may otherwise be made under Part B and which are furnished to Medicare beneficiaries who are residents in a SNF during a covered Part A stay. A comprehensive discussion of these provisions appears in the May 12, 1998 interim final rule (63 FR 26252). In addition, a detailed discussion of the legislative history of the SNF PPS is available online at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf.

Section 215(a) of the Protecting Access to Medicare Act of 2014 (PAMA) (Pub. L. 113–93, enacted April 1, 2014) added section 1888(g) to the Act requiring the Secretary to specify an all-cause all-condition hospital readmission measure and an all-condition risk-adjusted potentially preventable hospital readmission measure for the SNF setting. Additionally, section 215(b) of PAMA added section 1888(h) to the Act requiring the Secretary to implement a VBP program for SNFs. Finally, section 2(c)(4) of the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 (Pub. L. 113–185, enacted October 6, 2014) amended section 1888(e)(6) of the Act, which requires the Secretary to implement a QRP for SNFs under which SNFs report data on measures and resident assessment data. Finally, section 111 of the Consolidated Appropriations Act, 2021 (CAA, 2021) amended section 1888(h) of the Act, authorizing the Secretary to apply up to nine additional measures to the VBP program for SNFs.

B. Initial Transition for the SNF PPS

Under sections 1888(e)(1)(A) and (e)(11) of the Act, the SNF PPS included an initial, three-phase transition that blended a facility-specific rate (reflecting the individual facility's historical cost experience) with the Federal case-mix adjusted rate. The transition extended through the facility's first 3 cost reporting periods under the PPS, up to and including the one that began in FY 2001. Thus, the SNF PPS is no longer operating under the transition, as all facilities have been paid at the full Federal rate effective with cost reporting periods beginning in FY 2002. As we now base payments for SNFs entirely on the adjusted Federal per diem rates, we no longer include adjustment factors under the transition related to facility-specific rates for the upcoming FY.

C. Required Annual Rate Updates

Section 1888(e)(4)(E) of the Act requires the SNF PPS payment rates to be updated annually. The most recent annual update occurred in a final rule that set forth updates to the SNF PPS payment rates for FY 2023 (87 FR 47502, August 3, 2022).

Section 1888(e)(4)(H) of the Act specifies that we provide for publication annually in the Federal Register the following:

• The unadjusted Federal per diem rates to be applied to days of covered SNF services furnished during the upcoming FY.
• The case-mix classification system to be applied for these services during the upcoming FY.
• The factors to be applied in making the area wage adjustment for these services.

Along with other revisions discussed later in this preamble, this final rule provides the required annual updates to the per diem payment rates for SNFs for FY 2024.

III. Analysis and Responses to Public Comments on the FY 2024 SNF PPS Proposed Rule

In response to the publication of the FY 2024 SNF PPS proposed rule, we received 81 public comments from individuals, providers, corporations, government agencies, private citizens, trade associations, and major organizations. The following are brief summaries of each proposed provision, a summary of the public comments that we received related to that proposal, and our responses to the comments.

A. General Comments on the FY 2024 SNF PPS Proposed Rule

In addition to the comments we received on specific proposals contained within the proposed rule (which we address later in this final rule), commenters also submitted the following, more general, observations on the SNF PPS and SNF care generally. A discussion of these comments, along with our responses, appears below.

Comment: Several commenters raised concerns with therapy treatment under PDPM, specifically reductions in the amount of therapy furnished to SNF patients since PDPM was implemented. Some of these commenters stated that CMS should revise the existing limit on concurrent and group therapy to provide a financial penalty in cases where the facility exceeds this limit. These commenters also recommended that CMS direct its review contractors to examine the practices of facilities that changed their therapy service provision after PDPM was implemented. Additionally, commenters want CMS to release the results of any monitoring efforts around therapy provision. Finally, several commenters recommended that CMS reinstate a more frequent assessment schedule to discourage gaming.

Response: We appreciate commenters raising these concerns around therapy provision under PDPM, as compared the RUG–IV. We agree with commenters that the amount of therapy that is furnished to patients under PDPM is less than that delivered under RUG–IV. As we stated in the FY 2020 SNF PPS final rule, we believe that close, real-time monitoring is essential to identifying any adverse trends under PDPM. While we have identified the same reduction in therapy services and therapy staff, we believe that these findings must be considered within the context of patient outcomes. To the extent that facilities are able to maintain or improve patient outcomes, we believe that this supersedes changes in service provision, whether this be in the amount of therapy furnished or the mode in which it is furnished. We continue to monitor all aspects of PDPM and advise our review contractors on any adverse trends.

With regard to implementing a specific penalty for exceeding the group and concurrent therapy threshold, based on our current data, we have not identified any widespread misuse of this limit. Should we identify such misuse, either at a provider-level or at a broader level, we will pursue an appropriate course of action.

Finally, with regard to the recommendation that we reinstate something akin to the assessment schedule that was in effect under RUG–IV, given that PDPM does not reimburse on the basis of therapy minutes, we do not believe that such an increase in administrative burden on providers would have an impact on therapy provision. That being said, we strongly encourage interested parties to continue to provide suggestions on how to ensure that SNF patients receive the care they need based on their unique characteristics and goals.

Comment: One commenter stated that CMS should undertake an analysis of the impact of waiving the 3-day stay requirement during the PHE as compared to the impact on patient cost and outcomes once the requirement has been reinstated. This commenter requests that CMS release the results of such an analysis.

Response: We appreciate this suggestion. We have previously conducted analyses of the associated cost of removing the 3-day stay requirement and found that it would significantly increase Medicare outlays. We have not yet been able to perform such an analysis which would compare the impact of waiving this requirement during the PHE to the impact of it being re-implemented, but we believe it would likely lead to the same result.

Comment: One commenter requested that we consider including recreational therapy time provided to SNF residents by recreational therapists into the case-mix adjusted therapy component of PDPM, rather than having it be considered part of the nursing component. This commenter further suggested that CMS begin collecting data, as part of a demonstration project, on the utilization of recreational therapy, as a distinct and separate service, and its impact on patient care cost and quality.

Response: We appreciate the commenter raising this issue, but we do not believe there is sufficient evidence at this time regarding the efficacy of recreational therapy interventions or, more notably, data which would substantiate a determination of the effect on payment of such interventions, as such services were not considered separately, as were physical, occupational and speech-language pathology services, when the PDPM was being developed. That being said, we would note that Medicare Part A originally paid for institutional care in various provider settings, including SNF, on a reasonable cost basis, but now makes payment using PPS methodologies, such as the SNF PPS. To the extent that one of these SNFs furnished recreational therapy to its inpatients under the previous, reasonable cost methodology, the cost of the services would have been included in the base payments when SNF PPS payment rates were derived. Under the PPS methodology, Part A makes a comprehensive payment for the bundled package of items and services that the facility furnishes during the course of a Medicare-covered stay. This package encompasses nearly all services that the beneficiary receives during the course of the stay—including any medically necessary recreational therapy—and payment for such services is included within the facility's comprehensive SNF PPS payment for the covered Part A stay itself. With regard to developing a demonstration project focused on this particular service, we do not believe that creating such a project would substantially improve the accuracy of the SNF PPS payment rates. Moreover, in light of comments discussed above on the impact of PDPM implementation on therapy provision more generally, we believe that carving out recreational therapy as a separate discipline will not have a significant impact on access to recreational therapy services for SNF patients.

Comment: One commenter raised concerns regarding the perceived lack of adequate financial reporting and cost report auditing. This commenter stated that CMS does not do enough to ensure that the funds paid to providers under the SNF PPS are used appropriately for patient care. Further, this commenter suggested that CMS impose penalties for inaccurate, incomplete and fraudulent SNF ownership and cost data. Finally, this commenter urged CMS to establish a medical-loss ratio for SNFs to ensure that Medicare funds are used for patient care.

Response: We appreciate the commenter raising these concerns. With regard to the need for regulation and penalties associated with incomplete and fraudulent ownership and cost data, we would contend that there are consequences for providers when they are found to have incomplete cost reports or if the data they are reporting to CMS is found to be fraudulent. That being said, we focus on patient outcomes as the basis for assessing if the care provided to SNF patients is appropriate, as well as the Medicare funding used as the basis for that care. Ultimately, it is the responsibility of each SNF provider to ensure that the care provided to their patients, using the funds provided under the SNF PPS, is appropriate and sufficient to meet the unique needs, goals and characteristics of each patient. We encourage interested parties to provide future recommendations and suggestions for how to use SNF cost reports and other data sources to improve CMS auditing and enforcement activities.

IV. SNF PPS Rate Setting Methodology and FY 2024 Update

A. Federal Base Rates

Under section 1888(e)(4) of the Act, the SNF PPS uses per diem Federal payment rates based on mean SNF costs in a base year (FY 1995) updated for inflation to the first effective period of the PPS. We developed the Federal payment rates using allowable costs from hospital-based and freestanding SNF cost reports for reporting periods beginning in FY 1995. The data used in developing the Federal rates also incorporated a Part B add-on, which is an estimate of the amounts that, prior to the SNF PPS, would be payable under Part B for covered SNF services furnished to individuals during the course of a covered Part A stay in a SNF.

In developing the rates for the initial period, we updated costs to the first effective year of the PPS (the 15-month period beginning July 1, 1998) using a SNF market basket, and then standardized for geographic variations in wages and for the costs of facility differences in case-mix. In compiling the database used to compute the Federal payment rates, we excluded those providers that received new provider exemptions from the routine cost limits, as well as costs related to payments for exceptions to the routine cost limits. Using the formula that the BBA 1997 prescribed, we set the Federal rates at a level equal to the weighted mean of freestanding costs plus 50 percent of the difference between the freestanding mean and weighted mean of all SNF costs (hospital-based and freestanding) combined. We computed and applied separately the payment rates for facilities located in urban and rural areas and adjusted the portion of the Federal rate attributable to wage-related costs by a wage index to reflect geographic variations in wages.

B. SNF Market Basket Update

1. SNF Market Basket

Section 1888(e)(5)(A) of the Act requires us to establish a SNF market basket that reflects changes over time in the prices of an appropriate mix of goods and services included in covered SNF services. Accordingly, we have developed a SNF market basket that encompasses the most commonly used cost categories for SNF routine services, ancillary services, and capital-related expenses. In the SNF PPS final rule for FY 2018 (82 FR 36548 through 36566), we rebased and revised the SNF market basket, which included updating the base year from FY 2010 to 2014. In the SNF PPS final rule for FY 2022 (86 FR 42444 through 42463), we rebased and revised the SNF market basket, which included updating the base year from 2014 to 2018.

The SNF market basket is used to compute the market basket percentage increase that is used to update the SNF Federal rates on an annual basis, as required by section 1888(e)(4)(E)(ii)(IV) of the Act. This market basket percentage increase is adjusted by a forecast error adjustment, if applicable, and then further adjusted by the application of a productivity adjustment as required by section 1888(e)(5)(B)(ii) of the Act and described in section IV.B.4. of this final rule.

As outlined in the proposed rule, we proposed a FY 2024 SNF market basket percentage increase of 2.7 percent based on IHS Global Inc.'s (IGI's) fourth quarter 2022 forecast of the 2018-based SNF market basket (before application of the forecast error adjustment and productivity adjustment). We also proposed that if more recent data subsequently became available (for example, a more recent estimate of the market basket and/or the productivity adjustment), we would use such data, if appropriate, to determine the FY 2024 SNF market basket percentage increase, labor-related share relative importance, forecast error adjustment, or productivity adjustment in the SNF PPS final rule.

Since the proposed rule, we have updated the FY 2024 market basket percentage increase based on IGI's second quarter 2023 forecast with historical data through the first quarter of 2023. The FY 2024 growth rate of the 2018-based SNF market basket is estimated to be 3.0 percent.

2. Market Basket Update Factor for FY 2024

Section 1888(e)(5)(B) of the Act defines the SNF market basket percentage increase as the percentage change in the SNF market basket from the midpoint of the previous FY to the midpoint of the current FY. For the Federal rates outlined in this final rule, we use the percentage change in the SNF market basket to compute the update factor for FY 2024. This factor is based on the FY 2024 percentage increase in the 2018-based SNF market basket reflecting routine, ancillary, and capital-related expenses. Sections 1888(e)(4)(E)(ii)(IV) and (e)(5)(B)(i) of the Act require that the update factor used to establish the FY 2024 unadjusted Federal rates be at a level equal to the SNF market basket percentage increase. Accordingly, we determined the total growth from the average market basket level for the period of October 1, 2022 through September 30, 2023 to the average market basket level for the period of October 1, 2023 through September 30, 2024. As outlined in the proposed rule, we proposed a FY 2024 SNF market basket percentage increase of 2.7 percent. For this final rule, based on IGI's second quarter 2023 forecast with historical data through the first quarter of 2023, the FY 2024 growth rate of the 2018-based SNF market basket is estimated to be 3.0 percent.

As further explained in section IV.B.3. of this final rule, as applicable, we adjust the percentage increase by the forecast error adjustment from the most recently available FY for which there is final data and apply this adjustment whenever the difference between the forecasted and actual percentage increase in the market basket exceeds a 0.5 percentage point threshold in absolute terms. Additionally, section 1888(e)(5)(B)(ii) of the Act requires us to reduce the market basket percentage increase by the productivity adjustment (the 10-year moving average of changes in annual economy-wide private nonfarm business total factor productivity (TFP) for the period ending September 30, 2024) which is estimated to be 0.2 percentage point, as described in section IV.B.4. of this final rule.

We also note that section 1888(e)(6)(A)(i) of the Act provides that, beginning with FY 2018, SNFs that fail to submit data, as applicable, in accordance with sections 1888(e)(6)(B)(i)(II) and (III) of the Act for a fiscal year will receive a 2.0 percentage point reduction to their market basket update for the fiscal year involved, after application of section 1888(e)(5)(B)(ii) of the Act (the productivity adjustment) and section 1888(e)(5)(B)(iii) of the Act (the market basket increase). In addition, section 1888(e)(6)(A)(ii) of the Act states that application of the 2.0 percentage point reduction (after application of section 1888(e)(5)(B)(ii) and (iii) of the Act) may result in the market basket percentage change being less than zero for a fiscal year and may result in payment rates for a fiscal year being less than such payment rates for the preceding fiscal year. Section 1888(e)(6)(A)(iii) of the Act further specifies that the 2.0 percentage point reduction is applied in a noncumulative manner, so that any reduction made under section 1888(e)(6)(A)(i) of the Act applies only to the fiscal year involved, and that the reduction cannot be taken into account in computing the payment amount for a subsequent fiscal year.

3. Forecast Error Adjustment

As discussed in the June 10, 2003 supplemental proposed rule (68 FR 34768) and finalized in the August 4, 2003 final rule (68 FR 46057 through 46059), § 413.337(d)(2) provides for an adjustment to account for market basket forecast error. The initial adjustment for market basket forecast error applied to the update of the FY 2003 rate for FY 2004 and took into account the cumulative forecast error for the period from FY 2000 through FY 2002, resulting in an increase of 3.26 percent to the FY 2004 update. Subsequent adjustments in succeeding FYs take into account the forecast error from the most recently available FY for which there is final data and apply the difference between the forecasted and actual change in the market basket when the difference exceeds a specified threshold. We originally used a 0.25 percentage point threshold for this purpose; however, for the reasons specified in the FY 2008 SNF PPS final rule (72 FR 43425), we adopted a 0.5 percentage point threshold effective for FY 2008 and subsequent FYs. As we stated in the final rule for FY 2004 that first issued the market basket forecast error adjustment (68 FR 46058), the adjustment will reflect both upward and downward adjustments, as appropriate.

For FY 2022 (the most recently available FY for which there is final data), the forecasted or estimated increase in the SNF market basket was 2.7 percent, and the actual increase for FY 2022 is 6.3 percent, resulting in the actual increase being 3.6 percentage points higher than the estimated increase. Accordingly, as the difference between the estimated and actual amount of change in the market basket exceeds the 0.5 percentage point threshold, under the policy previously described (comparing the forecasted and actual market basket percentage increase), the FY 2024 market basket percentage increase of 3.0 percent would be adjusted upward to account for the forecast error adjustment of 3.6 percentage points, resulting in a SNF market basket percentage increase of 6.6 percent, which is then reduced by the productivity adjustment of 0.2 percentage point, discussed in section IV.B.4. of this final rule. This results in a SNF market basket update for FY 2024 of 6.4 percent.

Table 2 shows the forecasted and actual market basket increases for FY 2022.

4. Productivity Adjustment

Section 1888(e)(5)(B)(ii) of the Act, as added by section 3401(b) of the Patient Protection and Affordable Care Act (Affordable Care Act) (Pub. L. 111–148, enacted March 23, 2010) requires that, in FY 2012 and in subsequent FYs, the market basket percentage under the SNF payment system (as described in section 1888(e)(5)(B)(i) of the Act) is to be reduced annually by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Section 1886(b)(3)(B)(xi)(II) of the Act, in turn, defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide, private nonfarm business multifactor productivity (MFP) (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost-reporting period, or other annual period).

The U.S. Department of Labor's Bureau of Labor Statistics (BLS) publishes the official measure of productivity for the U.S. We note that previously the productivity measure referenced at section 1886(b)(3)(B)(xi)(II) of the Act was published by BLS as private nonfarm business multifactor productivity. Beginning with the November 18, 2021 release of productivity data, BLS replaced the term MFP with TFP. BLS noted that this is a change in terminology only and will not affect the data or methodology. As a result of the BLS name change, the productivity measure referenced in section 1886(b)(3)(B)(xi)(II) of the Act is now published by BLS as private nonfarm business total factor productivity. We refer readers to the BLS website at www.bls.gov for the BLS historical published TFP data. A complete description of the TFP projection methodology is available on our website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch. In addition, in the FY 2022 SNF final rule (86 FR 42429) we noted that, effective with FY 2022 and forward, we changed the name of this adjustment to refer to it as the “productivity adjustment,” rather than the “MFP adjustment.”

Per section 1888(e)(5)(A) of the Act, the Secretary shall establish a SNF market basket that reflects changes over time in the prices of an appropriate mix of goods and services included in covered SNF services. Section 1888(e)(5)(B)(ii) of the Act, added by section 3401(b) of the Affordable Care Act, requires that for FY 2012 and each subsequent FY, after determining the market basket percentage described in section 1888(e)(5)(B)(i) of the Act, the Secretary shall reduce such percentage by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Section 1888(e)(5)(B)(ii) of the Act further states that the reduction of the market basket percentage by the productivity adjustment may result in the market basket percentage being less than zero for a FY and may result in payment rates under section 1888(e) of the Act being less than such payment rates for the preceding fiscal year. Thus, if the application of the productivity adjustment to the market basket percentage calculated under section 1888(e)(5)(B)(i) of the Act results in a productivity-adjusted market basket percentage that is less than zero, then the annual update to the unadjusted Federal per diem rates under section 1888(e)(4)(E)(ii) of the Act would be negative, and such rates would decrease relative to the prior FY.

Based on the data available for the FY 2024 SNF PPS proposed rule, the proposed productivity adjustment (the 10-year moving average of changes in annual economy-wide private nonfarm business TFP for the period ending September 30, 2024) was projected to be 0.2 percentage point. We note that, as we typically do, we have updated our data between the FY 2024 SNF PPS proposed rule and this final rule. Based on IGI's second quarter 2023 forecast, the estimated 10-year moving average of changes in annual economy-wide private nonfarm business TFP for the period ending September 30, 2024 is estimated to be 0.2 percentage point.

Consistent with section 1888(e)(5)(B)(i) of the Act and § 413.337(d)(2), and as discussed previously in section IV.B.1. of this final rule, the market basket percentage for FY 2024 for the SNF PPS is based on IGI's second quarter 2023 forecast of the SNF market basket percentage increase, which is estimated to be 3.0 percent. This market basket update is then increased by 3.6 percentage points, due to application of the forecast error adjustment discussed earlier in section IV.B.3. of this final rule. Finally, as discussed earlier in section IV.B.4. of this final rule, we are applying a 0.2 percentage point productivity adjustment to the FY 2024 SNF market basket percentage increase. Therefore, the resulting productivity-adjusted FY 2024 SNF market basket update is equal to 6.4 percent, which reflects a market basket percentage increase of 3.0 percent, plus the 3.6 percentage points forecast error adjustment, and less the 0.2 percentage point productivity adjustment. Thus, we apply a net SNF market basket update factor of 6.4 percent in our determination of the FY 2024 SNF PPS unadjusted Federal per diem rates.

A discussion of the public comments received on the FY 2024 SNF market basket percentage increase to the SNF PPS rates, along with our responses, can be found below.

Comment: One commenter suggested CMS consider allowing SNFs to use different labor percentages for geographic areas with wage indexes less than or greater than 1, similar to IPPS hospitals. They believe this methodological change would allow for the wage index adjustment to match more closely with the provider's costs.

Response: We continue to believe it is technically appropriate and consistent with our interpretation of the statute to use the market basket cost weights, reflecting the national average of SNF costs, to determine the labor-related share applicable for all SNFs. In addition, our analysis of the 2018 SNF Medicare cost report data used to determine the 2018-based SNF market basket cost weights, shows that the compensation cost weights for urban (accounting for about 70 percent of freestanding SNF costs) and rural SNFs, in aggregate, are both 60 percent—consistent with the 2018-based SNF market basket compensation cost weight.

Comment: One commenter requested that CMS work with interested parties to explore updates to the SNF market basket methodology, potentially with new proxies or alternative data. One commenter identified a few detailed methodological issues for CMS to consider regarding the SNF market basket.

Response: We welcome commenters' input on the SNF market basket and appreciate the suggestions provided. We will consider them for future rulemaking when we propose to rebase and revise the SNF market basket.

Comment: One commenter appreciated the forecast error adjustments during the last two rulemaking cycles but stated that the current methodology may not capture impacts such as the entirety of the cost changes during times of high healthcare resource utilization (for example, during COVID–19 pandemic). The commenter further noted that applying the forecast error adjustment to future payments does not account for inflation that can alter the time-value of money. The commenter requested that CMS consider ways to evaluate the impact of addressing these potential shortcomings of the forecast error adjustment. One commenter recommended that CMS strongly consider including additional labor and cost data into the market basket updates prospectively, rather than retroactively, to adjust for the market basket projections' inability to accurately project rate increases during high inflation periods. One commenter (MedPAC) noted that CMS is not required by statute to make automatic forecast error corrections and in this instance the forecast error correction results in making a larger payment increase in addition to the statutory increases for FY 2024.

Response: The SNF market basket is a price index that measures the change in price, over time, of the same mix of goods and services purchased in the base period. As noted by the commenter, due to the availability of data and rates being set by CMS on a prospective basis, there is a 2-year lag between the forecast error adjustment and its application to the payment rate. For example, as stated in section IV.B.3. of this final rule, the FY 2024 SNF PPS payment rate update includes an adjustment for the FY 2022 market basket forecast error.

Subsequent to the initial cumulative adjustment implemented in FY 2004, the forecast error adjustment has been based on the forecast error from the most recently available FY for which there is final data, and the difference between the forecasted and actual change in the market basket is applied when the difference exceeds a specified threshold. The forecast error adjustment (when it exceeds the threshold of 0.5 percentage point (in absolute terms)) is intended to adjust for when historical price changes differ substantially from the forecasted price changes in order to appropriately pay providers for services provided, rather than typical minor variances that are inherent in statistical measurements. The forecast error adjustment is specifically defined to only account for errors in price forecasts and would appropriately not take into account differences in non-price factors affecting costs.

Therefore, we disagree with the commenter that the CMS forecast error adjustment is inadequate or that it should reflect other factors (such as changes in utilization due to case mix or other non-price factors or the time value of money). We use the most complete and available data for purposes of determining the market basket forecast, forecast error adjustment, and productivity adjustment as well as the most recent claims data when determining the SNF PPS payment rates. We do not forecast changes in the case-mix index.

Comment: Several commenters supported the net payment update of 3.7 percent reflecting a 2.7 percent market basket update. Numerous commenters also recommended that CMS use the most recently available data when determining the market basket update for the final rule.

Several commenters stated that the proposed 3.7 percent net payment update is inadequate when considering the financial hardship and increased costs many health care providers are facing as a result of the PHE and labor shortages. They recommended that CMS use data that better reflects the input price inflation that SNFs have experienced and are projected to experience in 2024. They believe CMS should reassess market basket data and how it weighs wage and benefits data, as they do not believe the updates to the market basket data reasonably reflect the reality of these associated costs. Similarly, one commenter stated that they believe the 2018-based SNF market basket alone no longer serves as an appropriate price proxy due to the growing expenditures in labor, which has driven a recent disproportionate increase in the labor share portion of the market basket. They recommended that CMS use more recent and supplemental labor cost data to accurately reflect a recent increase of the market basket's labor.

One commenter cited a report stating that the average hourly nursing wage increased over 17 percent from 2019 to 2022 as reported on the Medicare cost reports. They stated that the Medicare market basket update had only increased per-stay payments by less than 6 percent during that same time period. The commenter acknowledged that CMS will refresh the market basket update in the final rule with more recent data but expressed concern that the revised update will still be insufficient relative to input cost inflation as illustrated by the discrepancy between input costs and the market basket update in FY 2022.

Several commenters requested CMS exercise its existing authority or conditional funding opportunities to revise the proposed update to annual rates (either though an updated market basket or other allowable means) to account for the rapid rise of costs.

Response: We recognize the various comments on the proposed net payment update of 3.7 percent. Section 1888(e)(5)(A) of the Act states the Secretary shall establish a skilled nursing facility market basket index that reflects changes over time in the prices of an appropriate mix of goods and services included in covered skilled nursing facility services. The 2018-based SNF market basket is a fixed-weight, Laspeyres-type price index that measures the change in price, over time, of the same mix of goods and services purchased in the base period. Any changes in the quantity or mix of goods and services (that is, intensity) purchased over time relative to a base period that would determine change in costs are not measured. For the compensation cost weight in the 2018-based SNF market basket (which includes salaried and contract labor employees), we use the Employment Cost Indexes (ECIs) for wages and salaries and benefits for private industry workers in nursing care facilities to proxy the price increase of SNF labor. The ECI (published by the Bureau of Labor Statistics, or BLS) measures the change in the hourly labor cost to employers, independent of the influence of employment shifts among occupations and industry categories. Therefore, we believe the ECI for private industry workers in nursing care facilities, which only reflects the price change associated with the labor used to provide SNF care and appropriately does not reflect other factors that might affect labor costs, is an appropriate measure to use in the SNF market basket.

We disagree with the commenter's statement that the 2018-based SNF market basket is not adequately reflecting growing expenditures in labor, which has driven a recent disproportionate increase in the labor share portion of the market basket. Our preliminary analysis of the 2021 Medicare cost report data shows the compensation cost weight for freestanding SNFs is 59.9 percent—relatively unchanged from 2018 with 60.2 percent as increases in the contract labor cost weight were accompanied by decreasing wages and salaries and benefit cost weights. We will continue to analyze more recent freestanding skilled nursing Medicare cost report data to assess whether the SNF market basket should be rebased and revised. Any changes to the SNF market basket will be proposed in future rulemaking.

While the forecasted productivity-adjusted market basket update was 2.4 percent in FY 2020, 2.2 percent in FY 2021, and 2.0 percent in FY 2022, the increases in FY 2023 and FY 2024 reflect additional increases from forecast errors over this period (CMS provided a forecast error adjustment for FY 2021 of 1.5 percentage points in the FY 2023 SNF net payment update and a forecast error adjustment for FY 2022 of 3.6 percentage points, which is being applied to the FY 2024 SNF net payment update in this final rule).

While the average hourly wage for nursing from the reported SNF Medicare cost report data increased roughly 17 percent from 2019 to 2021 (the most complete data available), the hourly wages of nearly all other medical occupational categories, which make up approximately 15 percent of wages and salaries, have not increased by nearly as much. We found that the combined average wage for all other medical occupational categories, weighted by each occupation's percentage of total Adjusted Salaries as indicated on Worksheet S–3, Part V, Column 3 of the Medicare cost report, increased by less than 1 percent over the same time period. The compensation price proxy used in the SNF market basket would reflect trends in all occupations combined, which would partly explain why the ECI for wages and salaries for private industry workers in nursing care facilities has not increased at the pace of nursing wages alone.

As proposed, for this final rule, we are updating the SNF market basket percentage increase to reflect more recent data. Based on IGI's second quarter 2023 forecast with historical data through the first quarter of 2023, we are finalizing a 2018-based SNF market basket percentage increase of 3.0 percent which reflects a projected increase in compensation prices of 3.4 percent. This is faster projected price growth compared to the proposed FY 2024 market basket increase of 2.7 percent, which reflected a 3.0 percent compensation price growth. Both of the final FY 2024 increases are faster than the 10-year historical average price growth (2.6 percent for the 2018-based SNF market basket, with compensation prices increasing 2.7 percent).

As noted previously, section 1888(e)(5)(A) of the Act requires us to establish a SNF market basket index that reflects changes over time in the prices of an appropriate mix of goods and services included in covered SNF services. This market basket percentage update is adjusted by a forecast error correction, if applicable, and then further adjusted by the application of a productivity adjustment as required by section 1888(e)(5)(B)(ii) of the Act. Section 1888(e)(5)(A) of the Act does not provide the Secretary with the authority to apply a different update factor to SNF PPS payment rates for FY 2024. Additionally, MedPAC annually conducts an analysis of payment adequacy for SNF providers. In its March 2023 Report to Congress ( https://www.medpac.gov/document/march-2023-report-to-the-congress-medicare-payment-policy/) MedPAC noted the combination of Federal relief policies and the implementation of the new case-mix system resulted in overall improved financial performance for SNFs and recommended a 3 percent reduction to the SNF base payment rates.

Comment: Given that CMS is required by statute to implement a productivity adjustment to the market basket update, several commenters urged CMS to closely monitor the impact of such productivity adjustments and requested that the agency work with Congress to permanently eliminate or offset this reduction to SNF payments. Further, they requested that CMS use its exceptions authority under section 1888(e)(3)(A) of the Act to remove the productivity adjustment for any fiscal year that was covered under PHE determination (that is, 2020 (0.4 percent), 2021 (0.0 percent), 2022 (0.7 percent), and 2023 (0.3 percent)) from the calculation of the market basket for FY 2024 and any year thereafter.

Response: Section 1888(e)(5)(B)(ii) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(xi)(II) of the Act to the SNF PPS market basket increase factor. As required by statute, the FY 2024 productivity adjustment is derived based on the 10-year moving average growth in economy-wide productivity for the period ending in FY 2024. We recognize the concerns of the commenters regarding the appropriateness of the productivity adjustment; however, we are required pursuant to section 1888(e)(5)(B)(ii) of the Act to apply the specific productivity adjustment described here.

Comment: MedPAC commented that while they understand that CMS is required to implement the statutory payment update, the combination of Federal relief policies and the implementation of the new case-mix system resulted in overall improved financial performance for SNFs. Thus, they recommended a 3 percent reduction to the SNF base payment rates.

Response: We thank the commenter for their recommendation. However, we are required to update SNF PPS payments by the market basket percentage increase, as directed by section 1888(e)(4)(E)(ii)(IV) of the Act. This market basket percentage increase is adjusted by a forecast error correction, if applicable, and then further adjusted by the application of a productivity adjustment as required by section 1888(e)(5)(B)(ii) of the Act.

Comment: While many commenters were appreciative of the forecast error adjustment, one commenter noted that the application of the forecast error correction results in making a larger payment increase in addition to the statutory increase for FY 2024, even though the aggregate Medicare margin for SNFs is already high.

Response: As most recently discussed in the FY 2023 SNF PPS final rule (87 FR 47502), forecast error adjustments for the SNF market basket were introduced in the FY 2004 SNF PPS final rule (68 FR 46035), with the intended goal “to pay the appropriate amount, to the correct provider, for the proper service, at the right time”. We note that since implementation, forecast errors have generally been relatively small and clustered near zero and that for FY 2008 and subsequent years, we increased the threshold at which adjustments are triggered from 0.25 to 0.5 percentage

point. Our intent in raising the threshold was to distinguish typical statistical variances from more major unanticipated impacts and unforeseen disruptions of the economy (such as the recent PHE), or unexpected inflationary patterns (either at lower or higher than anticipated rates).

Comment: One commenter suggested that the forecast error adjustment be adopted and utilized across every CMS payment program.

Response: We appreciate the commenter's suggestion and will share this recommendation with our colleagues in other settings.

5. Unadjusted Federal Per Diem Rates for FY 2024

As discussed in the FY 2019 SNF PPS final rule (83 FR 39162), in FY 2020 we implemented a new case-mix classification system to classify SNF patients under the SNF PPS, the PDPM. As discussed in section V.B.1. of that final rule (83 FR 39189), under PDPM, the unadjusted Federal per diem rates are divided into six components, five of which are case-mix adjusted components (Physical Therapy (PT), Occupational Therapy (OT), Speech-Language Pathology (SLP), Nursing, and Non-Therapy Ancillaries (NTA)), and one of which is a non-case-mix component, as existed under the previous RUG–IV model. We proposed to use the SNF market basket, adjusted as described previously in sections IV.B.1. through IV.B.4. of this final rule, to adjust each per diem component of the Federal rates forward to reflect the change in the average prices for FY 2024 from the average prices for FY 2023. We also proposed to further adjust the rates by a wage index budget neutrality factor, described in section IV.D. of this final rule.

Further, in the past, we used the revised Office of Management and Budget (OMB) delineations adopted in the FY 2015 SNF PPS final rule (79 FR 45632, 45634), with updates as reflected in OMB Bulletin Nos. 15–01 and 17–01, to identify a facility's urban or rural status for the purpose of determining which set of rate tables would apply to the facility. As discussed in the FY 2021 SNF PPS proposed and final rules, we adopted the revised OMB delineations identified in OMB Bulletin No. 18–04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) to identify a facility's urban or rural status effective beginning with FY 2021.

Tables 3 and 4 reflect the updated unadjusted Federal rates for FY 2024, prior to adjustment for case-mix.

C. Case-Mix Adjustment

Under section 1888(e)(4)(G)(i) of the Act, the Federal rate also incorporates an adjustment to account for facility case-mix, using a classification system that accounts for the relative resource utilization of different patient types. The statute specifies that the adjustment is to reflect both a resident classification system that the Secretary establishes to account for the relative resource use of different patient types, as well as resident assessment data and other data that the Secretary considers appropriate. In the FY 2019 final rule (83 FR 39162, August 8, 2018), we finalized a new case-mix classification model, the PDPM, which took effect beginning October 1, 2019. The previous RUG–IV model classified most patients into a therapy payment group and primarily used the volume of therapy services provided to the patient as the basis for payment classification, thus creating an incentive for SNFs to furnish therapy regardless of the individual patient's unique characteristics, goals, or needs. PDPM eliminates this incentive and improves the overall accuracy and appropriateness of SNF payments by classifying patients into payment groups based on specific, data-driven patient characteristics, while simultaneously reducing the administrative burden on SNFs.

The PDPM uses clinical data from the MDS to assign case-mix classifiers to each patient that are then used to calculate a per diem payment under the SNF PPS, consistent with the provisions of section 1888(e)(4)(G)(i) of the Act. As discussed in section V.A. of this final rule, the clinical orientation of the case-mix classification system supports the SNF PPS's use of an administrative presumption that considers a beneficiary's initial case-mix classification to assist in making certain SNF level of care determinations. Further, because the MDS is used as a basis for payment, as well as a clinical assessment, we have provided extensive training on proper coding and the timeframes for MDS completion in our Resident Assessment Instrument (RAI) Manual. As we have stated in prior rules, for an MDS to be considered valid for use in determining payment, the MDS assessment should be completed in compliance with the instructions in the RAI Manual in effect at the time the assessment is completed. For payment and quality monitoring purposes, the RAI Manual consists of both the Manual instructions and the interpretive guidance and policy clarifications posted on the appropriate MDS website at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/MDS30RAIManual.html.

Under section 1888(e)(4)(H) of the Act, each update of the payment rates must include the case-mix classification methodology applicable for the upcoming FY. The FY 2024 payment rates set forth in this final rule reflect the use of the PDPM case-mix classification system from October 1, 2023, through September 30, 2024. The case-mix adjusted PDPM payment rates for FY 2024 are listed separately for urban and rural SNFs, in Tables 5 and 6 with corresponding case-mix values.

Given the differences between the previous RUG–IV model and PDPM in terms of patient classification and billing, it was important that the format of Tables 5 and 6 reflect these differences. More specifically, under both RUG–IV and PDPM, providers use a Health Insurance Prospective Payment System (HIPPS) code on a claim to bill for covered SNF services. Under RUG–IV, the HIPPS code included the three-character RUG–IV group into which the patient classified, as well as a two-character assessment indicator code that represented the assessment used to generate this code. Under PDPM, while providers still use a HIPPS code, the characters in that code represent different things. For example, the first character represents the PT and OT group into which the patient classifies. If the patient is classified into the PT and OT group “TA”, then the first character in the patient's HIPPS code would be an A. Similarly, if the patient is classified into the SLP group “SB”, then the second character in the patient's HIPPS code would be a B. The third character represents the Nursing group into which the patient classifies. The fourth character represents the NTA group into which the patient classifies. Finally, the fifth character represents the assessment used to generate the HIPPS code.

Tables 5 and 6 reflect the PDPM's structure. Accordingly, Column 1 of Tables 5 and 6 represents the character in the HIPPS code associated with a given PDPM component. Columns 2 and 3 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant PT group. Columns 4 and 5 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant OT group. Columns 6 and 7 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant SLP group. Column 8 provides the nursing case-mix group (CMG) that is connected with a given PDPM HIPPS character. For example, if the patient qualified for the nursing group CBC1, then the third character in the patient's HIPPS code would be a “P.” Columns 9 and 10 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant nursing group. Finally, columns 11 and 12 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant NTA group.

Tables 5 and 6 do not reflect adjustments which may be made to the SNF PPS rates as a result of the SNF VBP Program, discussed in section VII. of this final rule, or other adjustments, such as the variable per diem adjustment. Further, in the past, we used the revised OMB delineations adopted in the FY 2015 SNF PPS final rule (79 FR 45632, 45634), with updates as reflected in OMB Bulletin Nos, 15–01 and 17–01, to identify a facility's urban or rural status for the purpose of determining which set of rate tables would apply to the facility. As discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we adopted the revised OMB delineations identified in OMB Bulletin No. 18–04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) to identify a facility's urban or rural status effective beginning with FY 2021.

In the FY 2023 SNF PPS final rule (87 FR 47502), we finalized a proposal to recalibrate the PDPM parity adjustment over 2 years starting in FY 2023, which means that, for each of the PDPM case-mix adjusted components, we lowered the PDPM parity adjustment factor from 46 percent to 42 percent in FY 2023 and we will further lower the PDPM parity adjustment factor from 42 percent to 38 percent in FY 2024. Following this methodology, which is further described in the FY 2023 SNF PPS final rule (87 FR 47525 through 47534), Tables 5 and 6 incorporate the second phase of the PDPM parity adjustment recalibration.

Commenters submitted the following comments related to the proposed Federal per diem rates for FY 2024. A discussion of these comments, along with our responses, appears below.

Comment: One commenter stated that the case-mix adjusted rates for PT, OT, SLP, and nursing categories are higher in urban areas than in rural areas, which exacerbate inequalities between rural and urban SNFs.

Response: We disagree with the commenter's statement that the case-mix adjusted rates for the PT, OT and SLP components are higher in urban than rural areas as shown in Tables 5 and 6. As most recently noted in the FY 2023 SNF PPS final rule (87 FR 47502), the Federal per diem rates were established separately for urban and rural areas using allowable costs from FY 1995 cost reports, and therefore, account for and reflect the relative costs differences between urban and rural facilities. We note that the SNF PPS payment rates are updated annually by an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered SNF services and a portion of these rates are further adjusted by a wage index to reflect geographic variations in wages. We will continue to monitor our SNF payment policies to ensure they reflect as accurately as possible the current costs of care in the SNF setting.

Comment: One commenter was appreciative of the increase in payment for FY 2024 and encouraged CMS to maximize support for rural SNFs.

Response: We thank the commenter for their support of the payment rate update for FY 2024 and note that rural SNFs are expected to experience, on average, a 3.3 percent increase in payments compared with FY 2023.

Comment: Commenters encouraged CMS to continue to monitor the impact of the PDPM on beneficiaries' access to appropriate SNF services, including therapy services to address any emerging problems affecting SNF residents.

Response: We thank the commenter for their suggestion. We will continue to monitor the impact of the PDPM implementation on patient outcomes and other metrics to identify any adverse trends accompanying the revisions to the PPS.

Comment: Commenters generally expressed appreciation that the parity adjustment was phased in over 2 years but expressed concern that there would be a reduction to the SNF payment rates for FY 2024 due to this adjustment. A few commenters requested that the PDPM parity adjustment be delayed, reduced, cancelled or be phased in over an additional 2 years. One commenter indicated that they support implementing the remainder of the recalibrated parity adjustment in FY 2024 to prevent continued SNF payments in excess of the intended budget neutral implementation of the PDPM.

Response: We thank the commenters for their support of the phase in of the parity adjustment. We believe the 2-year phase-in was sufficient to mitigate adverse payment impacts while also ensuring that payment rates for all SNFs are set accurately and appropriately. As such, we do not believe it would be appropriate to expand the phase-in period beyond than what was finalized in the FY 2023 SNF PPS final rule. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47502), for a full discussion of the rationale related to the implementation of this policy.

D. Wage Index Adjustment

Section 1888(e)(4)(G)(ii) of the Act requires that we adjust the Federal rates to account for differences in area wage levels, using a wage index that the Secretary determines appropriate. Since the inception of the SNF PPS, we have used hospital inpatient wage data in developing a wage index to be applied to SNFs. We will continue this practice for FY 2024, as we continue to believe that in the absence of SNF-specific wage data, using the hospital inpatient wage index data is appropriate and reasonable for the SNF PPS. As explained in the update notice for FY 2005 (69 FR 45786), the SNF PPS does not use the hospital area wage index's occupational mix adjustment, as this adjustment serves specifically to define the occupational categories more clearly in a hospital setting; moreover, the collection of the occupational wage data under the inpatient prospective payment system (IPPS) also excludes any wage data related to SNFs. Therefore, we believe that using the updated wage data exclusive of the occupational mix adjustment continues to be appropriate for SNF payments. As in previous years, we would continue to use the pre-reclassified IPPS hospital wage data, without applying the occupational mix, rural floor, or outmigration adjustment, as the basis for the SNF PPS wage index. For FY 2024, the updated wage data are for hospital cost reporting periods beginning on or after October 1, 2019 and before October 1, 2020 (FY 2020 cost report data).

We note that section 315 of the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106–554, enacted December 21, 2000) gave the Secretary the discretion to establish a geographic reclassification procedure specific to SNFs, but only after collecting the data necessary to establish a SNF PPS wage index that is based on wage data from nursing homes. To date, this has proven to be unfeasible due to the volatility of existing SNF wage data and the significant amount of resources that would be required to improve the quality of the data. More specifically, auditing all SNF cost reports, similar to the process used to audit inpatient hospital cost reports for purposes of the IPPS wage index, would place a burden on providers in terms of recordkeeping and completion of the cost report worksheet. Adopting such an approach would require a significant commitment of resources by CMS and the Medicare Administrative Contractors (MACs), potentially far in excess of those required under the IPPS, given that there are nearly five times as many SNFs as there are inpatient hospitals. While we continue to believe that the development of such an audit process could improve SNF cost reports, which is determined to be adequately accurate for cost development purposes, in such a manner as to permit us to establish a SNF-specific wage index, we do not believe this undertaking is feasible.

In addition, we will continue to use the same methodology discussed in the SNF PPS final rule for FY 2008 (72 FR 43423) to address those geographic areas in which there are no hospitals, and thus, no hospital wage index data on which to base the calculation of the FY 2022 SNF PPS wage index. For rural geographic areas that do not have hospitals and, therefore, lack hospital wage data on which to base an area wage adjustment, we will continue using the average wage index from all contiguous Core-Based Statistical Areas (CBSAs) as a reasonable proxy. For FY 2024, there are no rural geographic areas that do not have hospitals, and thus, this methodology will not be applied. For rural Puerto Rico, we will not apply this methodology due to the distinct economic circumstances there; due to the close proximity of almost all of Puerto Rico's various urban and non-urban areas, this methodology will produce a wage index for rural Puerto Rico that is higher than that in half of its urban areas. Instead, we will continue using the most recent wage index previously available for that area. For urban areas without specific hospital wage index data, we will continue using the average wage indexes of all urban areas within the State to serve as a reasonable proxy for the wage index of that urban CBSA. For FY 2024, the only urban area without wage index data available is CBSA 25980, Hinesville-Fort Stewart, GA.

In the SNF PPS final rule for FY 2006 (70 FR 45026, August 4, 2005), we adopted the changes discussed in OMB Bulletin No. 03–04 (June 6, 2003), which announced revised definitions for MSAs and the creation of micropolitan statistical areas and combined statistical areas. In adopting the CBSA geographic designations, we provided for a 1-year transition in FY 2006 with a blended wage index for all providers. For FY 2006, the wage index for each provider consisted of a blend of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both using FY 2002 hospital data). We referred to the blended wage index as the FY 2006 SNF PPS transition wage index. As discussed in the SNF PPS final rule for FY 2006 (70 FR 45041), after the expiration of this 1-year transition on September 30, 2006, we used the full CBSA-based wage index values.

In the FY 2015 SNF PPS final rule (79 FR 45644 through 45646), we finalized changes to the SNF PPS wage index based on the newest OMB delineations, as described in OMB Bulletin No. 13–01, beginning in FY 2015, including a 1-year transition with a blended wage index for FY 2015. OMB Bulletin No. 13–01 established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas in the United States and Puerto Rico based on the 2010 Census, and provided guidance on the use of the delineations of these statistical areas using standards published in the June 28, 2010 Federal Register (75 FR 37246 through 37252). Subsequently, on July 15, 2015, OMB issued OMB Bulletin No. 15–01, which provided minor updates to and superseded OMB Bulletin No. 13–01 that was issued on February 28, 2013. The attachment to OMB Bulletin No. 15–01 provided detailed information on the update to statistical areas since February 28, 2013. The updates provided in OMB Bulletin No. 15–01 were based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2012 and July 1, 2013 and were adopted under the SNF PPS in the FY 2017 SNF PPS final rule (81 FR 51983, August 5, 2016). In addition, on August 15, 2017, OMB issued Bulletin No. 17–01 which announced a new urban CBSA, Twin Falls, Idaho (CBSA 46300) which was adopted in the SNF PPS final rule for FY 2019 (83 FR 39173, August 8, 2018).

As discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we adopted the revised OMB delineations identified in OMB Bulletin No. 18–04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) beginning October 1, 2020, including a 1-year transition for FY 2021 under which we applied a 5 percent cap on any decrease in a hospital's wage index compared to its wage index for the prior fiscal year (FY 2020). The updated OMB delineations more accurately reflect the contemporary urban and rural nature of areas across the country, and the use of such delineations allows us to determine more accurately the appropriate wage index and rate tables to apply under the SNF PPS.

In the FY 2023 SNF PPS final rule (87 FR 47521 through 47525), we finalized a policy to apply a permanent 5 percent cap on any decreases to a provider's wage index from its wage index in the prior year, regardless of the circumstances causing the decline. Additionally, we finalized a policy that a new SNF would be paid the wage index for the area in which it is geographically located for its first full or partial FY with no cap applied because a new SNF would not have a wage index in the prior FY. We amended the SNF PPS regulations at 42 CFR 413.337(b)(4)(ii) to reflect this permanent cap on wage index decreases. A full discussion of the adoption of this policy is found in the FY 2023 SNF PPS final rule.

As we previously stated in the FY 2008 SNF PPS proposed and final rules (72 FR 25538 through 25539, and 72 FR 43423), this and all subsequent SNF PPS rules and notices are considered to incorporate any updates and revisions set forth in the most recent OMB bulletin that applies to the hospital wage data used to determine the current SNF PPS wage index. OMB issued further revised CBSA delineations in OMB Bulletin No. 20–01, on March 6, 2020 (available on the web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). However, we determined that the changes in OMB Bulletin No. 20–01 do not impact the CBSA-based labor market area delineations adopted in FY 2021. Therefore, we did not propose to adopt the revised OMB delineations identified in OMB Bulletin No. 20 01 for FY 2022 or 2023, and for these reasons we are likewise not making such a requirement for FY 2024. The wage index applicable to FY 2024 is set forth in Tables A and B available on the CMS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.

Once calculated, we will apply the wage index adjustment to the labor-related portion of the Federal rate. Each year, we calculate a labor-related share, based on the relative importance of labor-related cost categories (that is, those cost categories that are labor-intensive and vary with the local labor market) in the input price index. In the SNF PPS final rule for FY 2022 (86 FR 42437), we finalized a proposal to revise the labor-related share to reflect the relative importance of the 2018-based SNF market basket cost weights for the following cost categories: Wages and Salaries; Employee Benefits; Professional Fees: Labor-Related; Administrative and Facilities Support services; Installation, Maintenance, and Repair Services; All Other: Labor-Related Services; and a proportion of Capital-Related expenses. The methodology for calculating the labor-related portion beginning in FY 2022 is discussed in detail in the FY 2022 SNF PPS final rule (86 FR 42461 through 42463).

We calculate the labor-related relative importance from the SNF market basket, and it approximates the labor-related portion of the total costs after taking into account historical and projected price changes between the base year and FY 2024. The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these changes. Accordingly, the relative importance figure more closely reflects the cost share weights for FY 2024 than the base year weights from the SNF market basket. We calculate the labor-related relative importance for FY 2024 in four steps. First, we compute the FY 2024 price index level for the total market basket and each cost category of the market basket. Second, we calculate a ratio for each cost category by dividing the FY 2024 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2024 relative importance for each cost category by multiplying this ratio by the base year (2018) weight. Finally, we add the FY 2024 relative importance for each of the labor-related cost categories (Wages and Salaries; Employee Benefits; Professional Fees: Labor-Related; Administrative and Facilities Support Services; Installation, Maintenance, and Repair Services; All Other: Labor-Related Services; and a portion of Capital-Related expenses) to produce the FY 2024 labor-related relative importance.

For the proposed rule, the labor-related share for FY 2024 was based on IGI's fourth quarter 2022 forecast of the 2018-based SNF market basket with historical data through the third quarter of 2022. As outlined in the proposed rule, we noted that if more recent data became available (for example, a more recent estimate of the labor-related share relative importance) we would use such data, if appropriate, for the SNF final rule. For this final rule, we base the labor-related share for FY 2024 on IGI's second quarter 2023 forecast, with historical data through the first quarter of 2023 of the 2018-based SNF market basket.

Table 7 summarizes the labor-related share for FY 2024, based on IGI's second quarter 2023 forecast of the 2018-based SNF market basket, compared to the labor-related share that was used for the FY 2023 SNF PPS final rule.

To calculate the labor portion of the case-mix adjusted per diem rate, we will multiply the total case-mix adjusted per diem rate, which is the sum of all five case-mix adjusted components into which a patient classifies, and the non-case-mix component rate, by the FY 2024 labor-related share percentage provided in Table 7. The remaining portion of the rate would be the non-labor portion. Under the previous RUG–IV model, we included tables which provided the case-mix adjusted RUG–IV rates, by RUG–IV group, broken out by total rate, labor portion and non-labor portion, such as Table 9 of the FY 2019 SNF PPS final rule (83 FR 39175). However, as we discussed in the FY 2020 final rule (84 FR 38738), under PDPM, as the total rate is calculated as a combination of six different component rates, five of which are case-mix adjusted, and given the sheer volume of possible combinations of these five case-mix adjusted components, it is not feasible to provide tables similar to those that existed in the prior rulemaking.

Therefore, to aid interested parties in understanding the effect of the wage index on the calculation of the SNF per diem rate, we have included a hypothetical rate calculation in Table 9.

Section 1888(e)(4)(G)(ii) of the Act also requires that we apply this wage index in a manner that does not result in aggregate payments under the SNF PPS that are greater or less than would otherwise be made if the wage adjustment had not been made. For FY 2024 (Federal rates effective October 1, 2023), we apply an adjustment to fulfill the budget neutrality requirement. We meet this requirement by multiplying each of the components of the unadjusted Federal rates by a budget neutrality factor, equal to the ratio of the weighted average wage adjustment factor for FY 2023 to the weighted average wage adjustment factor for FY 2024. For this calculation, we will use the same FY 2022 claims utilization data for both the numerator and denominator of this ratio. We define the wage adjustment factor used in this calculation as the labor portion of the rate component multiplied by the wage index plus the non-labor portion of the rate component. The finalized budget neutrality factor for FY 2024 is 0.9997.

We note that if more recent data become available (for example, revised wage data), we would use such data, as appropriate, to determine the wage index budget neutrality factor in the SNF PPS final rule.

We solicited public comment on the proposed SNF wage adjustment for FY 2024. The following is a summary of the comments we received and our responses.

Comment: One commenter did not support any increases in the labor-related share as any facility that has a wage index less than 1.0 will suffer financially from a rise in the labor-related share. They stated that across the country, there is a growing disparity between the high-wage and low-wage States.

Response: We appreciate the commenter's concern. However, each year we calculate a labor-related share based on the relative importance of labor-related cost categories, to account historical and projected price changes between the base year and the payment year (FY 2024 in this rule). The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these changes. As shown in Table 7, the slight increase in the labor-related share is due to an increase in the wages and salaries relative importance cost weight, reflecting the faster wage prices compared to other nonwage prices in the SNF market basket. This increase is consistent with comments we have received during this rulemaking about faster wage prices.

As discussed above, based on IGI's second quarter 2023 forecast with historical data through the first quarter of 2023, we are finalizing the FY 2024 labor-related share of 71.1 percent based on the relative importance of each of the labor-related cost categories in the 2018-based SNF market basket.

Comment: Commenters stated support of the permanent 5-percent cap on wage index decreases. One commenter encouraged CMS to implement these caps in a non-budget neutral manner to stabilize provider reimbursement and avoid further unexpected reductions for other providers.

Response: We appreciate the commenters' support of the permanent cap on wage index decreases. As for budget neutrality, we do not believe that the permanent 5-percent cap policy for the SNF wage index should be applied in a non-budget-neutral manner. The statute at section 1888(e)(4)(G)(ii) of the Act requires that adjustments for geographic variations in labor costs for a FY are made in a budget-neutral. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47521 through 47523) for a detailed discussion and for responses to these and other comments relating to the wage index cap policy.

Comment: While commenters support the current wage index methodology for FY 2024, including not requiring the commitment of resources needed to do audits on cost reports at this time, others encourage CMS to continue to reform the wage index policies (for example, SNF-specific wage index utilizing SNF audited cost report and nursing wage data).

Response: We appreciate the commenters' support of the proposed wage index policies for FY 2024. In the absence of a SNF-specific wage index, we believe the use of the pre-reclassified and pre-floor hospital wage data (without the occupational mix adjustment) continue to be an appropriate and reasonable proxy for the SNF PPS. For a detailed discussion of the rationale for our current wage index policies and for responses to these recurring comments, we refer readers to the FY 2023 SNF PPS final rule (87 FR 47513 through 47516) and the FY 2016 SNF PPS final rule (80 FR 46401 through 46402).

Comment: One commenter recommended that CMS should, as a matter of policy, require that SNFs provide wages on parity with hospitals for nursing staff. This commenter stated that, given that the SNF wage index is based on hospital wages, CMS should require that SNFs pay the same wages as the hospitals for nursing staff.

Response: We appreciate the commenter's suggestion. While we continue to believe that the pre-reclassified and pre-floor hospital wage index serves as an appropriate proxy for the SNF PPS, we do not believe that it would be appropriate for us to require SNFs to pay a certain amount to their staff. How a SNF chooses to reimburse their staff is a private financial arrangement between the facility and its staff, which means that we believe it would be inappropriate to establish regulations that govern this matter since there is no statutory authority present.

After consideration of public comments, we are finalizing our proposal regarding the wage index adjustment for FY 2024.

E. SNF Value-Based Purchasing Program

Beginning with payment for services furnished on October 1, 2018, section 1888(h) of the Act requires the Secretary to reduce the adjusted Federal per diem rate determined under section 1888(e)(4)(G) of the Act otherwise applicable to a SNF for services furnished during a fiscal year by 2 percent, and to adjust the resulting rate for a SNF by the value-based incentive payment amount earned by the SNF based on the SNF's performance score for that fiscal year under the SNF VBP Program. To implement these requirements, we finalized in the FY 2019 SNF PPS final rule the addition of § 413.337(f) to our regulations (83 FR 39178).

Please see section VIII. of this final rule for further discussion of the updates we are finalizing for the SNF VBP Program.

F. Adjusted Rate Computation Example

Tables 8 through 10 provide examples generally illustrating payment calculations during FY 2024 under PDPM for a hypothetical 30-day SNF stay, involving the hypothetical SNF XYZ, located in Frederick, MD (Urban CBSA 23224), for a hypothetical patient who is classified into such groups that the patient's HIPPS code is NHNC1. Table 8 shows the adjustments made to the Federal per diem rates (prior to application of any adjustments under the SNF VBP Program as discussed previously and taking into account the second phase of the parity adjustment recalibration discussed in section IV.C. of this final rule) to compute the provider's case-mix adjusted per diem rate for FY 2024, based on the patient's PDPM classification, as well as how the variable per diem (VPD) adjustment factor affects calculation of the per diem rate for a given day of the stay. Table 9 shows the adjustments made to the case-mix adjusted per diem rate from Table 8 to account for the provider's wage index. The wage index used in this example is based on the FY 2024 SNF PPS wage index that appears in Table A available on the CMS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html. Finally, Table 10 provides the case-mix and wage index adjusted per-diem rate for this patient for each day of the 30-day stay, as well as the total payment for this stay. Table 10 also includes the VPD adjustment factors for each day of the patient's stay, to clarify why the patient's per diem rate changes for certain days of the stay. As illustrated in Table 10, SNF XYZ's total PPS payment for this particular patient's stay would equal $21,717.98.

V. Additional Aspects of the SNF PPS

A. SNF Level of Care—Administrative Presumption

The establishment of the SNF PPS did not change Medicare's fundamental requirements for SNF coverage. However, because the case-mix classification is based, in part, on the beneficiary's need for skilled nursing care and therapy, we have attempted, where possible, to coordinate claims review procedures with the existing resident assessment process and case-mix classification system discussed in section III.C. of the FY 2024 SNF PPS proposed rule. This approach includes an administrative presumption that utilizes a beneficiary's correct assignment, at the outset of the SNF stay, of one of the case-mix classifiers designated for this purpose to assist in making certain SNF level of care determinations.

In accordance with § 413.345, we include in each update of the Federal payment rates in the Federal Register a discussion of the resident classification system that provides the basis for case-mix adjustment. We also designate those specific classifiers under the case-mix classification system that represent the required SNF level of care, as provided in 42 CFR 409.30. This designation reflects an administrative presumption that those beneficiaries who are correctly assigned one of the designated case-mix classifiers on the initial Medicare assessment are automatically classified as meeting the SNF level of care definition up to and including the assessment reference date (ARD) for that assessment.

A beneficiary who does not qualify for the presumption is not automatically classified as either meeting or not meeting the level of care definition, but instead receives an individual determination on this point using the existing administrative criteria. This presumption recognizes the strong likelihood that those beneficiaries who are correctly assigned one of the designated case-mix classifiers during the immediate post-hospital period would require a covered level of care, which would be less likely for other beneficiaries.

In the July 30, 1999 final rule (64 FR 41670), we indicated that we would announce any changes to the guidelines for Medicare level of care determinations related to modifications in the case-mix classification structure. The FY 2018 final rule (82 FR 36544) further specified that we would henceforth disseminate the standard description of the administrative presumption's designated groups via the SNF PPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html (where such designations appear in the paragraph entitled “Case Mix Adjustment”), and would publish such designations in rulemaking only to the extent that we actually intend to propose changes in them. Under that approach, the set of case-mix classifiers designated for this purpose under PDPM was finalized in the FY 2019 SNF PPS final rule (83 FR 39253) and is posted on the SNF PPS website ( https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html), in the paragraph entitled “Case Mix Adjustment.”

However, we note that this administrative presumption policy does not supersede the SNF's responsibility to ensure that its decisions relating to level of care are appropriate and timely, including a review to confirm that any services prompting the assignment of one of the designated case-mix classifiers (which, in turn, serves to trigger the administrative presumption) are themselves medically necessary. As we explained in the FY 2000 SNF PPS final rule (64 FR 41667), the administrative presumption is itself rebuttable in those individual cases in which the services actually received by the resident do not meet the basic statutory criterion of being reasonable and necessary to diagnose or treat a beneficiary's condition (according to section 1862(a)(1) of the Act). Accordingly, the presumption would not apply, for example, in those situations where the sole classifier that triggers the presumption is itself assigned through the receipt of services that are subsequently determined to be not reasonable and necessary. Moreover, we want to stress the importance of careful monitoring for changes in each patient's condition to determine the continuing need for Part A SNF benefits after the ARD of the initial Medicare assessment.

B. Consolidated Billing

Sections 1842(b)(6)(E) and 1862(a)(18) of the Act (as added by section 4432(b) of the BBA 1997) require a SNF to submit consolidated Medicare bills to its Medicare Administrative Contractor (MAC) for almost all of the services that its residents receive during the course of a covered Part A stay. In addition, section 1862(a)(18) of the Act places the responsibility with the SNF for billing Medicare for physical therapy, occupational therapy, and speech-language pathology services that the resident receives during a noncovered stay. Section 1888(e)(2)(A) of the Act excludes a small list of services from the consolidated billing provision (primarily those services furnished by physicians and certain other types of practitioners), which remain separately billable under Part B when furnished to a SNF's Part A resident. These excluded service categories are discussed in greater detail in section V.B.2. of the May 12, 1998 interim final rule (63 FR 26295 through 26297).

Effective with services furnished on or after January 1, 2024, section 4121(a)(4) of the CAA, 2023 added marriage and family therapists and mental health counselors to the list of practitioners at section 1888(e)(2)(A)(ii) of the Act whose services are excluded from the consolidated billing provision. We note that there are no rate adjustments required to the per diem to offset these exclusions, as payments for services made under section 1888(e)(2)(A)(ii) of the Act are not specified under the requirement at section 1888(e)(4)(G)(iii) of the Act as services for which the Secretary must “provide for an appropriate proportional reduction . . .equal to the aggregate increase in payments attributable to the exclusion”. See section IV.D. of the FY 2024 SNF PPS proposed rule for a discussion of the proposed regulatory updates implementing this change.

A detailed discussion of the legislative history of the consolidated billing provision is available on the SNF PPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf. In particular, section 103 of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA 1999) (Pub. L. 106–113, enacted November 29, 1999) amended section 1888(e)(2)(A)(iii) of the Act by further excluding a number of individual high-cost, low probability services, identified by HCPCS codes, within several broader categories (chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices) that otherwise remained subject to the provision. We discuss this BBRA 1999 amendment in greater detail in the SNF PPS proposed and final rules for FY 2001 (65 FR 19231 through 19232, April 10, 2000, and 65 FR 46790 through 46795, July 31, 2000), as well as in Program Memorandum AB–00–18 (Change Request #1070), issued March 2000, which is available online at www.cms.gov/transmittals/downloads/ab001860.pdf.

As explained in the FY 2001 proposed rule (65 FR 19232), the amendments enacted in section 103 of the BBRA 1999 not only identified for exclusion from this provision a number of particular service codes within four specified categories (that is, chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices), but also gave the Secretary the authority to designate additional, individual services for exclusion within each of these four specified service categories. In the proposed rule for FY 2001, we also noted that the BBRA 1999 Conference report (H.R. Conf. Rep. No. 106–479 at 854 (1999)) characterizes the individual services that this legislation targets for exclusion as high-cost, low probability events that could have devastating financial impacts because their costs far exceed the payment SNFs receive under the PPS. According to the conferees, section 103(a) of the BBRA 1999 is an attempt to exclude from the PPS certain services and costly items that are provided infrequently in SNFs. By contrast, the amendments enacted in section 103 of the BBRA 1999 do not designate for exclusion any of the remaining services within those four categories (thus, leaving all of those services subject to SNF consolidated billing), because they are relatively inexpensive and are furnished routinely in SNFs.

As we further explained in the final rule for FY 2001 (65 FR 46790), and as is consistent with our longstanding policy, any additional service codes that we might designate for exclusion under our discretionary authority must meet the same statutory criteria used in identifying the original codes excluded from consolidated billing under section 103(a) of the BBRA 1999: they must fall within one of the four service categories specified in the BBRA 1999; and they also must meet the same standards of high cost and low probability in the SNF setting, as discussed in the BBRA 1999 Conference report. Accordingly, we characterized this statutory authority to identify additional service codes for exclusion as essentially affording the flexibility to revise the list of excluded codes in response to changes of major significance that may occur over time (for example, the development of new medical technologies or other advances in the state of medical practice) (65 FR 46791).

Effective with items and services furnished on or after October 1, 2021, section 134 in Division CC of the CAA, 2021 established an additional category of excluded codes in section 1888(e)(2)(A)(iii)(VI) of the Act, for certain blood clotting factors for the treatment of patients with hemophilia and other bleeding disorders along with items and services related to the furnishing of such factors under section 1842(o)(5)(C) of the Act. Like the provisions enacted in the BBRA 1999, section 1888(e)(2)(A)(iii)(VI) of the Act gives the Secretary the authority to designate additional items and services for exclusion within the category of items and services related to blood clotting factors, as described in that section. Finally, as noted previously in this final rule, section 4121(a)(4) of Division FF of CAA, 2023 amended section 1888(e)(2)(A)(ii) of the Act to exclude marriage and family therapist services and mental health counselor services from consolidated billing effective January 1, 2024.

In the proposed rule, we specifically solicited public comments identifying HCPCS codes in any of these five service categories (chemotherapy items, chemotherapy administration services, radioisotope services, customized prosthetic devices, and blood clotting factors) representing recent medical advances that might meet our criteria for exclusion from SNF consolidated billing. We may consider excluding a particular service if it meets our criteria for exclusion as specified previously. We requested that commenters identify in their comments the specific HCPCS code that is associated with the service in question, as well as their rationale for requesting that the identified HCPCS code(s) be excluded.

We note that the original BBRA amendment and the CAA, 2021 identified a set of excluded items and services by means of specifying individual HCPCS codes within the designated categories that were in effect as of a particular date (in the case of the BBRA 1999, July 1, 1999, and in the case of the CAA, 2021, July 1, 2020), as subsequently modified by the Secretary. In addition, as noted in this section of the preamble, the statute (sections 1888(e)(2)(A)(iii)(II) through (VI) of the Act) gives the Secretary authority to identify additional items and services for exclusion within the five specified categories of items and services described in the statute, which are also designated by HCPCS code. Designating the excluded services in this manner makes it possible for us to utilize program issuances as the vehicle for accomplishing routine updates to the excluded codes to reflect any minor revisions that might subsequently occur in the coding system itself, such as the assignment of a different code number to a service already designated as excluded, or the creation of a new code for a type of service that falls within one of the established exclusion categories and meets our criteria for exclusion.

Accordingly, in the event that we identify through the current rulemaking cycle any new services that will actually represent a substantive change in the scope of the exclusions from SNF consolidated billing, we will identify these additional excluded services by means of the HCPCS codes that are in effect as of a specific date (in this case, October 1, 2023). By making any new exclusions in this manner, we can similarly accomplish routine future updates of these additional codes through the issuance of program instructions. The latest list of excluded codes can be found on the SNF Consolidated Billing website at https://www.cms.gov/Medicare/Billing/SNFConsolidatedBilling.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: Several commenters requested that CMS create a new exclusion category that excludes expensive items and services based on a price threshold. Another commenter requested that CMS review the statute and change the statute to provide equal access and payment for DME items for residents in a SNF. Some commenters suggested that CMS exclude expensive antibiotics. Finally, some commenters requested that CMS add clinical social workers to the SNF exclusion list.

Response: As we noted in the proposed rule, sections 1888(e)(2)(A)(iii)(II) through (VI) of the Act give the Secretary authority to identify additional items and services for exclusion only within the categories of items and services described in the statute. Accordingly, it is beyond the statutory authority of CMS to exclude services that do not fit these categories, or to create additional categories of excluded services. The changes requested by these commenters are beyond the scope of CMS authority and would require Congressional action.

Comment: A commenter requested that CMS add Altuviio, a new class of factor VIII therapy for adults and children with hemophilia A, the list of blood clotting factor exclusions. Altuviio is currently billed using the miscellaneous J code—J 7199, Hemophilia Clotting Factor, not otherwise classified, and has not been assigned its own J code.

Response: As we noted in the proposed rule, we are only able to add services to the exclusion list once they have actually been assigned a HCPCS code. The approach that Congress adopted to identify the individual blood clotting factor drugs being designated for exclusion consisted of listing them by HCPCS code in the statute itself (section 1888(e)(2)(A)(iii)(VI) of the Act). Thus, a blood clotting factor drug's assignment to its own specific code serves as the mechanism of designating it for exclusion, as well as the means by which the claims processing system is able to recognize that exclusion. Accordingly, the assignment of a blood clotting factor drug to its own code is a necessary prerequisite to consider that service for exclusion from consolidated billing under the SNF PPS. We cannot add a miscellaneous non-descriptive code such as J7199. When the code is assigned, we will review it as part of our standard review of new HCPCS codes for exclusion.

Comment: Several commenters named specific suggestions of drugs for exclusion in the chemotherapy category, including: Tecvayli; Denosumab, Leuprolide, and Keytruda; Ponatinib, Gilteritinib, Idhifa, Onureg, Midostaurin, Sprycel, Venetoclax, Promacta, Fulphila, Neulasta, Zarxio, Udenyca; Imatinib, Dasatinib, Nilotinib, Cabozantinib, Sunitinib, and Lenalidomide.

Response: For the reasons discussed previously in this final rule as well as prior rulemaking, the particular drugs cited in these comments remain subject to consolidated billing.

In the case of leuprolide acetate and denosumab, we have addressed these when suggested in past rulemaking cycles, most recently in the SNF PPS final rules for FY 2023 (87 FR 47502, August 3, 2022). In those rules, we explained that these drugs are unlikely to meet the criterion of “low probability” specified in the BBRA.

With regard to all other specific drugs mentioned, these are not actually chemotherapy drugs, but rather either immunotherapy or other non-chemotherapy treatments for cancer, or non-chemotherapy services related to or used in conjunction with chemotherapy or in treatment of chemotherapy symptoms. As such, these services do not fit the chemotherapy category or any existing exclusion categories. As we noted in the proposed rule, sections 1888(e)(2)(A)(iii)(II) through (VI) of the Act give the Secretary authority to identify additional items and services for exclusion only within the categories of items and services described in the statute. Accordingly, it is beyond the statutory authority of CMS to exclude services that do not fit these categories, or to create additional categories of excluded services. Such changes would require Congressional action. Additionally, some of these drugs do not have unique HCPCS codes assigned, which as we explained in the preceding comment, is a necessary prerequisite to consider that service for exclusion from consolidated billing under the SNF PPS.

Comment: A commenter noted that CMS website and manual materials contain out of date material with regard to the exclusion of blood clotting factors enacted in the Consolidated Appropriations Act (CAA) of 2021 and implemented by the FY 2022 SNF Final Rule (86 FR 42442).

Response: We appreciate the commenter bringing this to our attention and will update our online materials accordingly.

Comment: One commenter requested a copy of the consolidated billing exclusion list or instructions on how to find it. The statutory language specifying exclusion categories is set out in sections 1888(e)(2)(A)(ii) and (iii) of the Act.

Response: The consolidated billing exclusion list is available online at: https://www.cms.gov/Medicare/Billing/SNFConsolidatedBilling.

C. Payment for SNF-Level Swing-Bed Services

Section 1883 of the Act permits certain small, rural hospitals to enter into a Medicare swing-bed agreement, under which the hospital can use its beds to provide either acute- or SNF-level care, as needed. For critical access hospitals (CAHs), Part A pays on a reasonable cost basis for SNF-level services furnished under a swing-bed agreement. However, in accordance with section 1888(e)(7) of the Act, SNF-level services furnished by non-CAH rural hospitals are paid under the SNF PPS, effective with cost reporting periods beginning on or after July 1, 2002. As explained in the FY 2002 final rule (66 FR 39562), this effective date is consistent with the statutory provision to integrate swing-bed rural hospitals into the SNF PPS by the end of the transition period, June 30, 2002.

Accordingly, all non-CAH swing-bed rural hospitals have now come under the SNF PPS. Therefore, all rates and wage indexes outlined in earlier sections of this final rule for the SNF PPS also apply to all non-CAH swing-bed rural hospitals. As finalized in the FY 2010 SNF PPS final rule (74 FR 40356 through 40357), effective October 1, 2010, non-CAH swing-bed rural hospitals are required to complete an MDS 3.0 swing-bed assessment which is limited to the required demographic, payment, and quality items. As discussed in the FY 2019 SNF PPS final rule (83 FR 39235), revisions were made to the swing bed assessment to support implementation of PDPM, effective October 1, 2019. A discussion of the assessment schedule and the MDS effective beginning FY 2020 appears in the FY 2019 SNF PPS final rule (83 FR 39229 through 39237). The latest changes in the MDS for swing-bed rural hospitals appear on the SNF PPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html.

D. Revisions to the Regulation Text

We proposed to make the following revisions in the regulation text. Section 4121(a)(4) of Division FF of the CAA, 2023 requires Medicare to exclude marriage and family therapist (MFT) services and mental health counselor services (MHC) from SNF consolidated billing for services furnished on or after January 1, 2024. Exclusion from consolidated billing allows these services to be billed separately by the performing clinician rather than being included in the SNF payment. To reflect the recently-enacted exclusion of MFT services and MHC services from SNF consolidated billing at section 1888(e)(2)(A)(ii) of the Act (as discussed in section V.B of the proposed rule), we proposed to redesignate current § 411.15(p)(2)(vi) through (xviii) as § 411.15(p)(2)(viii) through (xx), respectively. In addition, we proposed to redesignate § 489.20(s)(6) through (18) as § 489.20(s)(8) through (20), respectively. We also proposed to add new regulation text at §§ 411.15(p)(2)(vi) and (vii) and 489.20(s)(6) and (7). Specifically, proposed new §§ 411.15(p)(2)(vi) and 489.20(s)(6) would reflect the exclusion of services performed by an MFT, as defined in section 1861(lll)(2) of the Act. Proposed new §§ 411.15(p)(2)(vii) and 489.20(s)(7) would reflect the exclusion of services performed by an MHC, as defined in section 1861(lll)(4) of the Act.

Subsequently, we identified the need for additional conforming changes to the regulatory text. In addition to adding the two new exclusions themselves to the regulation text as set forth in the proposed rule, the existing exclusion for certain telehealth services will need to be revised as well, because it cross-refers to subparagraphs that are now being renumbered as a result of adding the new exclusions. Specifically, a conforming change is needed in the consolidated billing exclusion provision on telehealth services at existing § 411.15(p)(2)(xii) (which, as a result of the other regulation text changes finalized in this rule, will be redesignated § 411.15(p)(2)(xiv)) and in the parallel provider agreement provision on telehealth services at existing § 489.20(s)(12) (which, as a result of the other regulation text changes finalized in this rule, will be redesignated § 489.20(s)(14)). As these additional conforming edits serve to ensure effective implementation of this new exclusion, and because these new conforming edits additionally serve to expand access to telehealth services, we are confident in making these additional changes in this final rule.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: Commenters agreed and appreciated the new exclusion of MFT and MHC services. A few commenters stated that, in light of the exclusion of MFT and MHC services, CMS should consider also excluding services furnished by clinical social workers (CSW). One commenter cited a recent nursing home study which recommended that nursing homes should retain more clinical social workers and CMS should allow for Medicare reimbursement for services furnished by these practitioners.

Response: We appreciate the support that we received in relation to the proposed regulatory text changes. With regard to the additional exclusion of CSW services, we would note that unlike the services of certain other types of practitioners (such as physicians and clinical psychologists), CSW services do not appear in the list of services that the law specifies in section 1888(e)(2)(A)(ii) through (iv) of the Act as being excluded from the consolidated billing requirement. Adding CSW services to the statutory list of services that are excluded from SNF consolidated billing would require legislation by Congress to amend the law itself.

In light of the comments received on this issue, we are finalizing the additions as proposed, with the additional conforming edits that we identified during the comment period.

VI. Other SNF PPS Issues

A. Technical Updates to the PDPM ICD–10 Mappings

1. Background

In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the implementation of the Patient Driven Payment Model (PDPM), effective October 1, 2019. The PDPM utilizes the International Classification of Diseases, 10th Revision, Clinical Modification (ICD–10–CM, hereafter referred to as ICD–10) codes in several ways, including using the patient's primary diagnosis to assign patients to clinical categories under several PDPM components, specifically the PT, OT, SLP, and NTA components. While other ICD–10 codes may be reported as secondary diagnoses and designated as additional comorbidities, the PDPM does not use secondary diagnoses to assign patients to clinical categories. The PDPM ICD–10 code to clinical category mapping, ICD–10 code to SLP comorbidity mapping, and ICD–10 code to NTA comorbidity mapping (hereafter collectively referred to as the PDPM ICD–10 code mappings) are available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM.

In the FY 2020 SNF PPS final rule (84 FR 38750), we outlined the process by which we maintain and update the PDPM ICD–10 code mappings, as well as the SNF Grouper software and other such products related to patient classification and billing, to ensure that they reflect the most up to date codes. Beginning with the updates for FY 2020, we apply nonsubstantive changes to the PDPM ICD–10 code mappings through a subregulatory process consisting of posting the updated PDPM ICD–10 code mappings on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. Such nonsubstantive changes are limited to those specific changes that are necessary to maintain consistency with the most current PDPM ICD–10 code mappings.

On the other hand, substantive changes that go beyond the intention of maintaining consistency with the most current PDPM ICD–10 code mappings, such as changes to the assignment of a code to a clinical category or comorbidity list, would be through notice and comment rulemaking because they are changes that affect policy. We note that, in the case of any diagnoses that are either currently mapped to Return to Provider or that we are finalizing to classify into this category, this is not intended to reflect any judgment on the importance of recognizing and treating these conditions. Rather, we believe that there are more specific or appropriate diagnoses that would better serve as the primary diagnosis for a Part-A covered SNF stay.

2. Clinical Category Changes for New ICD–10 Codes for FY 2023

Each year, we review the clinical category assigned to new ICD–10 diagnosis codes and propose changing the assignment to another clinical category if warranted. This year, we proposed changing the clinical category assignment for the following five new ICD–10 codes that were effective on October 1, 2022:

• D75.84 Other platelet-activating anti-platelet factor 4 (PF4) disorders was mapped to the clinical category of Return to Provider. Patients with anti-PF4 disorders have blood clotting disorders. Examples of disorders to be classified with D75.84 are spontaneous heparin-induced thrombocytopenia (without heparin exposure), thrombosis with thrombocytopenia syndrome, and vaccine-induced thrombotic thrombocytopenia. Due to the similarity of this code to other anti-PF4 disorders, we proposed changing the assignment to Medical Management.

• F43.81 Prolonged grief disorder and F43.89 Other reactions to severe stress were mapped to the clinical category of Medical Management. However, while we believe that SNFs serve an important role in providing services to those beneficiaries suffering from mental illness, the SNF setting is not the setting that would be most beneficial to treat a patient for whom these diagnoses are coded as the patient's primary diagnosis. For this reason, we proposed changing the clinical category of both codes to Return to Provider. We would encourage providers to continue reporting these codes as secondary diagnoses, to ensure that we are able to identify these patients and that they are receiving appropriate care.

• G90.A Postural orthostatic tachycardia syndrome (POTS) was mapped to the clinical category of Acute Neurologic. POTS is a type of orthostatic intolerance that causes the heart to beat faster than normal when transitioning from sitting or lying down to standing up, causing changes in blood pressure, increase in heart rate, and lightheadedness. The treatment for POTS involves hydration, physical therapy, and vasoconstrictor medications, which are also treatments for codes such as E86.0 Dehydration and E86.1 Hypovolemia that are mapped to the Medical Management category. Since the medical interventions are similar, we proposed changing the assignment for POTS to Medical Management.

• K76.82 Hepatic encephalopathy was mapped to the clinical category of Return to Provider. Hepatic encephalopathy is a condition resulting from severe liver disease, where toxins build up in the blood that can affect brain function and lead to a change in medical status. Prior to the development of this code, multiple codes were used to characterize this condition such as K76.6 Portal hypertension, K76.7 Hepatorenal syndrome, and K76.89 Other unspecified diseases of liver, which are mapped to the Medical Management category. Since these codes describe similar liver conditions, we proposed changing the assignment to Medical Management.

We solicited comments on the proposed substantive changes to the PDPM ICD–10 code mappings discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: Several commenters stated that they appreciate the ongoing refinements to the PDPM ICD–10 code mappings and the opportunity to provide input to the proposals. Some commenters stated that they would like CMS to identify effective dates on the PDPM website along with educational materials and resources.

Response: We appreciate the positive comments that we received supporting our efforts to map diagnoses more accurately under the PDPM. We also appreciate the suggestion to develop additional educational materials and resources, which we will consider as we update the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM.

Comment: Some commenters did not support the proposal to change the assignment of F43.81 Prolonged grief disorder and F43.89 Other reactions to severe stress to Return to Provider instead of Medical Management. Their rationale was that a subset of SNFs that specialize in behavioral and mental health treatment may require use of these two new diagnosis codes as the primary diagnosis codes to meet beneficiary needs.

Response: We believe that even in such cases as the commenters described, there are many other behavioral and mental health diagnoses available that would serve as a more appropriate primary diagnosis for a SNF stay and, therefore, assigning these two codes to Return to Provider would not impede access to care for beneficiaries.

Comment: Several commenters suggested additional changes to the PDPM ICD–10 code mappings that were outside the scope of this rulemaking. Specifically, they requested that we consider changing M62.81 Muscle weakness (generalized) from Return to Provider to the Non-surgical orthopedic/musculoskeletal clinical category; adding several dysphasia codes to the SLP comorbidity mapping (namely, R13.14 Dysphagia, pharyngoesophageal phase, R13.11 Dysphagia, oral phase, R13.12 Dysphagia, oropharyngeal phase, R13.13 Dysphagia, pharyngeal phase, and R13.19 Other dysphagia); and adding a range of ICD–10 codes from J00 Acute nasopharyngitis [common cold] to J06.9 Acute upper respiratory infection, unspecified to the SLP comorbidity mapping.

Response: We note that the changes suggested by these commenters are outside the scope of this rulemaking, and will not be addressed in this rule. We will further consider the suggested changes to the ICD–10 code mappings and may implement them in the future as appropriate. To the extent that such changes are non-substantive, we may issue them in a future subregulatory update if appropriate; however, if such changes are substantive changes, in accordance with the update process established in the FY 2020 SNF PPS final rule, such changes must undergo full notice and comment rulemaking, and thus may be included in future rulemaking. See the discussion of the update process for the ICD–10 code mappings in the FY 2020 SNF PPS final rule (84 FR 38750) for more information.

After consideration of public comments, we are finalizing the changes as proposed.

3. Clinical Category Changes for Unspecified Substance Use Disorder Codes

Effective with stays beginning on and after October 1, 2022, ICD–10 diagnosis codes F10.90 Alcohol use, unspecified, uncomplicated, F10.91 Alcohol use, unspecified, in remission, F11.91 Opioid use, unspecified, in remission, F12.91 Cannabis use, unspecified, in remission, F13.91 Sedative, hypnotic or anxiolytic use, unspecified, in remission, and F14.91 Cocaine use, unspecified, in remission went into effect and were mapped to the clinical category of Medical Management. We reviewed these 6 new substance use disorder (SUD) codes and changed the assignment from Medical Management to Return to Provider because the codes are not specific as to if they refer to abuse or dependence, and there are other specific codes available for each of these conditions that would be more appropriate as a primary diagnosis for a SNF stay. For example, diagnosis code F10.90 Alcohol use, unspecified, uncomplicated is not specific as to whether the patient has alcohol abuse or alcohol dependence. There are more specific codes that could be used instead, such as F10.10 Alcohol abuse, uncomplicated or F10.20 Alcohol dependence, uncomplicated, that may serve as the primary diagnosis for a SNF stay and are appropriately mapped to the clinical category of Medical Management.

Moreover, we believe that increased accuracy of coding a patient's primary diagnosis aligns with CMS' broader efforts to ensure better quality of care. Therefore, we reviewed all 458 ICD–10 SUD codes from code categories F10 to F19 and finalized reassigning 162 additional unspecified SUD codes to Return to Provider from Medical Management because the codes are not specific as to if they refer to abuse or dependence. We would note that this policy change would not affect a large number of SNF stays. Our data from FY 2021 show that the 162 unspecified SUD codes were used as primary diagnoses for only 323 SNF stays (0.02 percent) and as secondary diagnoses for 9,537 SNF stays (0.54 percent). The purpose of enacting this policy is to continue an ongoing effort to refine the PDPM ICD–10 code mappings each year to ensure more accurate coding of primary diagnoses. We would encourage providers to continue reporting these codes as secondary diagnoses, to ensure that we are able to identify these patients and that they are receiving appropriate care.

Table 1, Proposed Clinical Category Changes for Unspecified Substance Use Disorder Codes, which lists all 168 codes included in this proposal, was posted on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. We solicited comments on the proposed substantive changes to the PDPM ICD–10 code mappings discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: Commenters supported the PDPM clinical category changes for unspecified SUD codes as proposed. However, several commenters did not agree with the use of F10.10 Alcohol abuse, uncomplicated or F10.20 Alcohol dependence, uncomplicated, as these examples do not align with the ICD–10–CM Official Guidelines for Coding and Reporting and the SNF provider would not be able to assign a code such as F10.10 or F10.20 without physician documentation to support that alcohol abuse or dependence was present.

Response: We appreciate the positive comments that we received supporting our efforts to map SUD diagnoses more accurately under the PDPM. We would note that the examples provided for alcohol abuse and dependence diagnosis were not intended to be diagnostic guidance, and the facility should assess the patient to identify the specific primary diagnosis that requires daily skilled care.

Comment: Some commenters opposed the PDPM clinical category changes for unspecified SUD codes due to concerns about administrative burden. While they acknowledged that there are more appropriate codes that can be used to indicate whether the patient has substance abuse or dependence, they believe that it is the responsibility of the referring physician to code at the highest level of specificity, and query rules make it complex for SNFs to recommend more specific codes to the physician.

Response: We appreciate that commenters agree there are more appropriate codes that can be used to indicate whether the patient has substance abuse or dependence. We continue to believe that appropriate treatment requires specificity in the coding of the diagnoses, which aligns with CMS' broader efforts to ensure better quality of care. Moreover, we believe that the plan of care for a patient should not only depend upon the diagnoses of the referring physician, but also on the assessment of the SNF care team, which includes the clinicians caring for the patient at the facility.

After consideration of public comments, we are finalizing the changes as proposed.

4. Clinical Category Changes for Certain Subcategory Fracture Codes

Each year, we solicit comments on additional substantive and nonsubstantive changes that commenters believe are necessary to the PDPM ICD–10 code mappings. In the FY 2023 final rule (87 FR 47524), we described how one commenter recommended that CMS consider revising the PDPM ICD–10 code mappings to reclassify certain subcategory S42.2—humeral fracture codes. The commenter highlighted that certain encounter codes for humeral fractures, such as those ending in the 7th character of A for an initial encounter for fracture, are permitted the option to be mapped to a surgical clinical category, denoted on the PDPM ICD–10 code mappings as May be Eligible for One of the Two Orthopedic Surgery Categories (that is, major joint replacement or spinal surgery, or orthopedic surgery) if the patient had a major procedure during the prior inpatient stay that impacts the SNF care plan. However, the commenter noted that other encounter codes within the same code family, such as those ending in the 7th character of D for subsequent encounter for fracture with routine healing, are mapped to the Non-Surgical Orthopedic/Musculoskeletal without the surgical option. The commenter requested that we review all subcategory S42.2—fracture codes to ensure that the appropriate surgical clinical category could be selected for joint aftercare. Since then, the commenter has also contacted CMS with a similar suggestion for M84.552D Pathological fracture in neoplastic disease, left femur, subsequent encounter for fracture with routine healing.

We have since reviewed the suggested code subcategories to determine the most efficient manner for addressing this discrepancy. We proposed adding the surgical option that allows 45 subcategory S42.2—codes for displaced fractures to be eligible for one of two orthopedic surgery categories. However, we noted that this does not extend to subcategory S42.2—codes for nondisplaced fractures, which typically do not require surgery. We also proposed adding the surgical option to subcategory 46 M84.5—codes for pathological fractures to certain major weight-bearing bones to be eligible for one of two orthopedic surgery categories.

Table 2, Proposed Clinical Category Changes for S42.2 and M84.5 Fracture Codes, which lists all 91 codes included in this proposal, was posted on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. We solicited comments on the proposed substantive changes to the PDPM ICD–10 code mappings discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

We did not receive public comments on this provision, and therefore, we are finalizing the changes as proposed.

5. Clinical Category Changes for Unacceptable Principal Diagnosis Codes

In the FY 2023 final rule (87 FR 47525), we described how several commenters referred to instances when SNF claims were denied for including a primary diagnosis code that was listed on the PDPM ICD–10 code mappings as a valid code, but was not accepted by some Medicare Administrative Contractors (MACs) that use the Hospital Inpatient Prospective Payment System (IPPS) Medicare Code Editor (MCE) lists when evaluating the primary diagnosis codes listed on SNF claims. In the IPPS, a patient's diagnosis is entered into the Medicare claims processing systems and subjected to a series of automated screens called the MCE. The MCE lists are designed to identify cases that require further review before classification into an MS–DRG. We noted that all codes on the MCE lists are able to be reported; however, a code edit may be triggered that the MAC may either choose to bypass or return to the provider to resubmit. Updates to the MCE lists are proposed on an annual basis and discussed through IPPS rulemaking when new codes or policies involving existing codes are introduced.

Commenters recommended that CMS seek to align the PDPM ICD–10 code mappings with the MCE in treating diagnoses that are Return to Provider, specifically referring to the Unacceptable Principal Diagnosis edit code list in the Definition of Medicare Code Edits, which was posted on the CMS website at https://www.cms.gov/medicare/medicare-fee-for-service-payment/acuteinpatientpps/ms-drg-classifications-and-software. The Unacceptable Principal Diagnosis edit code list contains selected codes that describe a circumstance that influences an individual's health status but not a current illness or injury, or codes that are not specific manifestations but may be due to an underlying cause, and which are considered unacceptable as a principal diagnosis.

We identified 95 codes from the MCE Unacceptable Principal Diagnosis edit code list that were mapped to a valid clinical category on the PDPM ICD–10 code mappings, and that were coded as primary diagnoses for 14,808 SNF stays (0.84 percent) in FY 2021. Table 3, Proposed Clinical Category Changes for Unacceptable Principal Diagnosis Codes, which lists all 95 codes included in this proposal, was posted on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. As stated previously in this section of this final rule, we note that reporting these codes as a primary diagnosis for a SNF stay may trigger an edit that the MAC may either choose to bypass or return to the provider to resubmit, and therefore not all of these 14,808 stays were denied by the MACs.

After clinical review, we concurred that the 95 codes listed in Table 3 on the CMS website should be assigned to Return to Provider. For the diagnosis codes listed in Table 3 on the CMS website that are from the category B95 to B97 range and contain the suffix “as the cause of diseases classified elsewhere”, the ICD–10 coding convention for such etiology and manifestation codes, where certain conditions have both an underlying etiology and multiple body system manifestations due to the underlying etiology, dictates that the underlying condition should be sequenced first, followed by the manifestation. The ICD–10 coding guidelines also state that codes from subcategory G92.0— Immune effector cell-associated neurotoxicity syndrome, subcategory R40.2— Coma scale, and subcategory S06.A— Traumatic brain injury should only be reported as secondary diagnoses, as there are more specific codes that should be sequenced first. Additionally, the ICD–10 coding guidelines state that diagnosis codes in categories Z90 and Z98 are status codes, indicating that a patient is either a carrier of a disease or has the sequelae or residual of a past disease or condition, and are not reasons for a patient to be admitted to a SNF. Lastly, our clinicians determined that diagnosis code Z43.9 Encounter for attention to unspecified artificial opening should be assigned to the clinical category Return to Provider because there are more specific codes that identify the site for the artificial opening.

Therefore, we proposed to reassign the 95 codes listed in Table 3 on the CMS website from the current default clinical category on the PDPM ICD–10 code mappings to Return to Provider. We also proposed to make future updates to align the PDPM ICD–10 code mappings with the MCE Unacceptable Principal Diagnosis edit code list on a subregulatory basis going forward. Moreover, we solicited comment on aligning with the MCE Manifestation codes not allowed as principal diagnosis edit code list, which contains diagnosis codes that are the manifestation of an underlying disease, not the disease itself, and therefore should not be used as a principal diagnosis, and the Questionable admission codes edit code list, which contains diagnoses codes that are not usually sufficient justification for admission to an acute care hospital. While these MCE lists were not mentioned by commenters, we believed that some MACs may be applying these edit lists to SNF claims and this could cause continued differences between the PDPM ICD–10 code mappings and the IPPS MCE. Finally, we proposed to make future updates to align the PDPM ICD–10 code mappings with the MCE Manifestation codes not allowed as principal diagnosis edit code list and the Questionable admission codes edit code list on a subregulatory basis going forward.

We solicited comments on the proposed substantive changes to the PDPM ICD–10 code mappings discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary. We did not receive public comments on this provision, and therefore, we are finalizing as proposed.

VII. Skilled Nursing Facility Quality Reporting Program (SNF QRP)

A. Background and Statutory Authority

The Skilled Nursing Facility Quality Reporting Program (SNF QRP) is authorized by section 1888(e)(6) of the Act, and it applies to freestanding SNFs, SNFs affiliated with acute care facilities, and all non-critical access hospital (CAH) swing-bed rural hospitals. Section 1888(e)(6)(A)(i) of the Act requires the Secretary to reduce by 2 percentage points the annual market basket percentage increase described in section 1888(e)(5)(B)(i) of the Act applicable to a SNF for a fiscal year (FY), after application of section 1888(e)(5)(B)(ii) of the Act (the productivity adjustment) and section 1888(e)(5)(B)(iii) of the Act, in the case of a SNF that does not submit data in accordance with sections 1888(e)(6)(B)(i)(II) and (III) of the Act for that FY. Section 1890A of the Act requires that the Secretary establish and follow a pre-rulemaking process, in coordination with the consensus-based entity (CBE) with a contract under section 1890(a) of the Act, to solicit input from certain groups regarding the selection of quality and efficiency measures for the SNF QRP. We have codified our program requirements in our regulations at 42 CFR part 413.

In the proposed rule, we proposed to adopt three new measures, remove three existing measures, and modify one existing measure. Second, we sought information on principles we could use to select and prioritize SNF QRP quality measures in future years. Third, we provided an update on our health equity efforts. Fourth, we proposed several administrative changes, including a change to the SNF QRP data completion thresholds and a new data submission method for the proposed CoreQ: Short Stay Discharge questionnaire. Finally, we proposed to begin the public reporting of four measures.

B. General Considerations Used for the Selection of Measures for the SNF QRP

For a detailed discussion of the considerations we use for the selection of SNF QRP quality, resource use, or other measures, we refer readers to the FY 2016 SNF PPS final rule (80 FR 46429 through 46431).

1. Quality Measures Currently Adopted for the FY 2024 SNF QRP

The SNF QRP currently has 16 measures for the FY 2024 SNF QRP, which are listed in Table C1. For a discussion of the factors used to evaluate whether a measure should be removed from the SNF QRP, we refer readers to § 413.360(b)(2).

C. SNF QRP Quality Measure Updates

In the proposed rule, we included SNF QRP proposals for the FY 2025 and FY 2026 program years. We proposed to add new measures to the SNF QRP as well as remove measures from the SNF QRP. Beginning with the FY 2025 SNF QRP, we proposed to (1) modify the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) measure, (2) adopt the Discharge Function Score measure, which we specified under section 1888(e)(6)(B)(i) of the Act, and (3) remove three current measures: (i) the Application of Percent of Long-Term Care Hospital (LTCH) Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function measure, (ii) the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure, and (iii) the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure.

We also proposed two new measures beginning with the FY 2026 SNF QRP: (i) the CoreQ: Short Stay Discharge measure which we are specifying under section 1899B(d)(1) of the Act, and (ii) the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure, which we are specifying under section 1899B(d)(1) of the Act.

1. SNF QRP Quality Measure Updates Beginning With the FY 2025 SNF QRP

a. Modification of the COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP) Measure Beginning With the FY 2025 SNF QRP

(1) Background

On January 31, 2020, the Secretary declared a public health emergency (PHE) for the United States in response to the global outbreak of SARS–CoV–2, a novel (new) coronavirus that causes a disease named “coronavirus disease 2019” (COVID–19). Subsequently, in the FY 2022 SNF PPS final rule (86 FR 42480 through 42489), we adopted the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) (HCP COVID–19 Vaccine) measure for the SNF QRP. The HCP COVID–19 Vaccine measure requires each SNF to submit data on the percentage of HCP eligible to work in the SNF for at least one day during the reporting period, excluding persons with contraindications to FDA-authorized or -approved COVID–19 vaccines, who have received a complete vaccination course against SARS–CoV–2. Since that time, COVID–19 has continued to spread domestically and around the world with more than 103.9 million cases and 1.13 million deaths in the United States as of June 19, 2023. In recognition of the ongoing significance and complexity of COVID–19, the Secretary has renewed the PHE on April 21, 2020, July 23, 2020, October 2, 2020, January 7, 2021, April 15, 2021, July 19, 2021, October 15, 2021, January 14, 2022, April 12, 2022, July 15, 2022, October 13, 2022, January 11, 2023, and February 9, 2023. The Department of Health and Human Services (HHS) let the PHE expire on May 11, 2023. However, HHS stated that the public health response to COVID–19 remains a public health priority with a whole of government approach to combating the virus, including through vaccination efforts.

In the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) and in the Revised Guidance for Staff Vaccination Requirements, we stated that vaccination is a critical part of the nation's strategy to effectively counter the spread of COVID–19. We continue to believe it is important to incentivize and track HCP vaccination in SNFs through quality measurement in order to protect HCP, residents, and caregivers, and to help sustain the ability of SNFs to continue serving their communities after the PHE. At the time we issued the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) where we adopted the HCP COVID–19 Vaccine measure, the Food and Drug Administration (FDA) had issued emergency use authorizations (EUAs) for COVID–19 vaccines manufactured by Pfizer-BioNTech, Moderna, and Janssen. The Pfizer-BioNTech vaccine was authorized for ages 12 and older and the Moderna and Janssen vaccines for ages 18 and older. Shortly following the publication of the FY 2022 SNF PPS final rule, on August 23, 2021, the FDA issued an approval for the Pfizer-BioNTech vaccine, marketed as Comirnaty. The FDA issued approval for the Moderna vaccine, marketed as Spikevax, on January 31, 2022 and an EUA for the Novavax vaccine, on July 13, 2022. The FDA also issued EUAs for single booster doses of the then authorized COVID–19 vaccines. As of November 19, 2021 a single booster dose of each COVID–19 vaccine was authorized for all eligible individuals 18 years of age and older. EUAs were subsequently issued for a second booster dose of the Pfizer-BioNTech and Moderna vaccines in certain populations in March 2022. FDA first authorized the use of a booster dose of bivalent or “updated” COVID–19 vaccines from Pfizer-BioNTech and Moderna in August 2022.

(a) Measure Importance

While the impact of COVID–19 vaccines on asymptomatic infection and transmission is not yet fully known, there are now robust data available on COVID–19 vaccine effectiveness across multiple populations against severe illness, hospitalization, and death. Two-dose COVID–19 vaccines from Pfizer-BioNTech and Moderna were found to be 88 percent and 93 percent effective against hospitalization for COVID–19, respectively, over 6 months for adults over age 18 without immunocompromising conditions. During a SARS–CoV–2 surge in the spring and summer of 2021, 92 percent of COVID–19 hospitalizations and 91 percent of COVID–19-associated deaths were reported among persons not fully vaccinated. Real-world studies of population-level vaccine effectiveness indicated similarly high rates of efficacy in preventing SARS–CoV–2 infection among frontline workers in multiple industries, with a 90 percent effectiveness in preventing symptomatic and asymptomatic infection from December 2020 through August 2021. Vaccines have also been highly effective in real-world conditions at preventing COVID–19 in HCP with up to 96 percent efficacy for fully vaccinated HCP, including those at risk for severe infection and those in racial and ethnic groups disproportionately affected by COVID–19. In the presence of high community prevalence of COVID–19, residents of nursing homes with low staff vaccination coverage had cases of COVID–19 related deaths 195 percent higher than those among residents of nursing homes with high staff vaccination coverage. Overall, data demonstrate that COVID–19 vaccines are effective and prevent severe disease, hospitalization, and death.

As SARS–CoV–2 persists and evolves, our COVID–19 vaccination strategy must remain responsive. When we adopted the HCP COVID–19 Vaccine measure in the FY 2022 SNF PPS final rule, we stated that the need for booster doses of COVID–19 vaccine had not been established and no additional doses had been recommended (86 FR 42484 through 42485). We also stated that we believed the numerator was sufficiently broad to include potential future boosters as part of a “complete vaccination course” and that the measure was sufficiently specified to address boosters (86 FR 42485). Since we adopted the HCP COVID–19 Vaccine measure in the FY 2022 SNF PPS final rule, new variants of SARS–CoV–2 have emerged around the world and within the United States. Specifically, the Omicron variant (and its related subvariants) is listed as a variant of concern by the Centers for Disease Control and Prevention (CDC) because it spreads more easily than earlier variants. Vaccine manufacturers have responded to the Omicron variant by developing bivalent COVID–19 vaccines, which include a component of the original virus strain, to provide broad protection against COVID–19 and a component of the Omicron variant, to provide better protection against COVID–19 caused by the Omicron variant. These booster doses of the bivalent COVID–19 vaccines have been shown to increase immune response to SARS–CoV–2 variants, including Omicron, particularly in individuals that are more than 6 months removed from receipt of their primary series. The FDA issued EUAs for booster doses of two bivalent COVID–19 vaccines, one from Pfizer-BioNTech and one from Moderna, and strongly encourages anyone who is eligible to consider receiving a booster dose with a bivalent COVID–19 vaccine to provide better protection against currently circulating variants. COVID–19 booster doses are associated with a greater reduction in infections among HCP relative to those who only received primary series vaccination, with a rate of breakthrough infections among HCP who received only a two-dose regimen of 21.4 percent compared to a rate of 0.7 percent among boosted HCP.

We believe that vaccination remains the most effective means to prevent the severe consequences of COVID–19, including severe illness, hospitalization, and death. Given the availability of vaccine efficacy data, EUAs issued by the FDA for bivalent boosters, the continued presence of SARS–CoV–2 in the United States, and variance among rates of booster dose vaccination, it is important to update the specifications of the HCP COVID–19 Vaccine measure to refer to HCP who receive primary series and booster doses in a timely manner. Given the persistent spread of COVID–19, we continue to believe that monitoring and surveillance of vaccination rates among HCP are important and provides residents, beneficiaries, and their caregivers with information to support informed decision making. Beginning with the FY 2025 SNF QRP, we proposed to modify the HCP COVID–19 Vaccine measure to replace the term “complete vaccination course” with the term “up to date” in the HCP vaccination definition. We also proposed to update the numerator to specify the time frames within which an HCP is considered up to date with recommended COVID–19 vaccines, including booster doses, beginning with the FY 2025 SNF QRP.

(b) Measure Testing

The CDC conducted beta testing of the modified HCP COVID–19 Vaccine measure by assessing if the collection of information on booster doses received by HCP was feasible, as information on receipt of booster doses is required for determining if HCP are up to date with the current COVID–19 vaccination. Feasibility was assessed by calculating the proportion of facilities that reported booster doses of the COVID–19 vaccine. The assessment was conducted in various facility types, including SNFs, using vaccine coverage data for the first quarter of calendar year (CY) 2022 (January to March), which was reported through the CDC's National Healthcare Safety Network (NHSN). Feasibility of reporting booster doses is evident by the fact that 99.2 percent of SNFs reported vaccination booster dose coverage data to the NHSN for the first quarter of 2022. Additionally, HCP COVID–19 Vaccine measure scores calculated using January 1 to March 31, 2022 data had a median of 31.8 percent and an interquartile range of 18.9 to 49.7 percent, indicating a measure performance gap as there are clinically significant differences in booster dose vaccination coverage rates among SNFs.

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act be endorsed by a consensus-based entity (CBE) with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

The current version of the HCP COVID–19 Vaccine measure recently received endorsement by the CBE on July 26, 2022 under the name “Quarterly Reporting of COVID–19 Vaccination Coverage Among Healthcare Personnel.” However, this measure received endorsement based on its specifications depicted in the FY 2022 SNF PPS final rule (86 FR 42480 through 42489), and does not capture information about whether HCP are up to date with their COVID–19 vaccinations. The proposed modification of this measure utilizes the term up to date in the HCP vaccination definition and updates the numerator to specify the time frames within which an HCP is considered up to date with recommended COVID–19 vaccines. We are unable to identify any measures endorsed or adopted by a consensus organization for SNFs that captured information on whether HCP are up to date with their COVID–19 vaccinations, and we found no other feasible and practical measure on this topic.

Therefore, after consideration of other available measures, we found that the exception under section 1899B(e)(2)(B) of the Act applies and proposed the modified measure, HCP COVID–19 Vaccine, beginning with the FY 2025 SNF QRP. The CDC, the measure developer, is pursuing CBE endorsement for the modified version of the measure.

(3) Measure Applications Partnership (MAP) Review

We refer readers to the FY 2022 SNF PPS final rule (86 FR 42482) for more information on the initial review of the HCP COVID–19 Vaccine measure by the Measure Applications Partnership (MAP).

In accordance with section 1890A of the Act, the pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the Measures Under Consideration (MUC) List, that the Secretary is considering adopting for use in the Medicare program(s), including our quality reporting programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the MUC List. We submitted the updated version of the HCP COVID–19 Vaccine measure on the MUC List entitled “List of Measures under Consideration for December 1, 2022” for the 2022 to 2023 pre-rulemaking cycle for consideration by the MAP. Interested parties submitted four comments to the MAP during the pre-rulemaking process on the proposed modifications of the HCP COVID–19 Vaccine measure. Three commenters noted that it is important that HCP be vaccinated against COVID–19 and supported measurement and reporting as an important strategy to help healthcare organizations assess their performance in achieving high rates of up to date vaccination of their HCP. One of these commenters noted that the measure would provide valuable information to the government as part of its ongoing response to the pandemic. The other two commenters do not believe it should be used in a pay-for-performance program, and one raised concerns of potential unintended consequences, such as frequency of reporting and the potential State regulations with which such a requirement might conflict. One commenter did not support the measure, raising several concerns with the measure, including that the data have never been tested for validity or reliability. Finally, three of the four commenters raised concern about the difficulty of defining up to date for purposes of the modified measure.

Shortly after publication of the MUC List, several MAP workgroups met to provide input on the measure. First, the MAP Health Equity Advisory Group convened on December 6 to 7, 2022. The MAP Health Equity Advisory Group questioned whether the measure excludes residents with contraindications to FDA authorized or approved COVID–19 vaccines, and whether the measure will be stratified by demographic factors. The measure developer (that is, the CDC) confirmed that HCP with contraindications to the vaccines are excluded from the measure denominator, but the measure will not be stratified since the data are submitted at an aggregate rather than an individual level.

The MAP Rural Health Advisory Group met on December 8 to 9, 2022, during which a few members expressed concerns about data collection burden, given that small rural hospitals may not have employee health software. The measure developer acknowledged the challenge of getting adequate documentation and emphasized their goal is to ensure the measures do not present a burden on the provider. The measure developer also noted that the model used for the HCP COVID–19 Vaccine measure is based on the Influenza Vaccination Coverage among HCP measure (CBE #0431), and it intends to utilize a similar approach to the modified HCP COVID–19 Vaccine measure if vaccination strategy becomes seasonal. The measure developer acknowledged that if COVID–19 becomes seasonal, the measure model could evolve to capture seasonal vaccination.

Next, the MAP Post-Acute Care/Long-Term Care (PAC/LTC) workgroup met on December 12, 2022 and provided input on the proposed modification for the HCP COVID–19 Vaccine measure. The MAP PAC/LTC workgroup noted that the previous version of the measure received endorsement from the CBE (CBE #3636), and that the CDC intends to submit the updated measure for endorsement. The PAC/LTC workgroup voted to support the staff recommendation of conditional support for rulemaking pending testing indicating the measure is reliable and valid, and endorsement by the CBE.

Following the PAC/LTC workgroup meeting, a public comment period was held in which interested parties commented on the PAC/LTC workgroup's preliminary recommendations, and the MAP received three comments. Two supported the update to the measure, one of which strongly supported the vaccination of HCP against COVID–19. Although these commenters supported the measure, one commenter recommended CBE endorsement for the updated measure, and encouraged us to monitor any unintended consequences from the measure. Two commenters noted the challenges associated with the measure's specifications. Specifically, one noted the broad definition of the denominator and another recommended a vaccination exclusion or exception due to religious beliefs. Finally, one commenter raised issues related to the time lag between data collection and public reporting on Care Compare and encouraged us to provide information as to whether the measure is reflecting vaccination rates accurately and encouraging HCP vaccination.

The MAP Coordinating Committee convened on January 24 to 25, 2023, during which the measure was placed on the consent calendar and received a final recommendation of conditional support for rulemaking pending testing indicating the measure is reliable and valid, and endorsement by the CBE. We refer readers to the final MAP recommendations, titled 2022–2023 MAP Final Recommendations.

(4) Quality Measure Calculation

The HCP COVID–19 Vaccine measure is a process measure developed by the CDC to track COVID–19 vaccination coverage among HCP in facilities such as SNFs. The HCP COVID–19 Vaccine measure is a process measure and is not risk-adjusted.

The denominator would be the number of HCP eligible to work in the facility for at least one day during the reporting period, excluding persons with contraindications to COVID–19 vaccination that are described by the CDC. SNFs report the following four categories of HCP to NHSN, and the first three categories are included in the measure denominator:

• Employees: This includes all persons who receive a direct paycheck from the reporting facility (that is, on the facility's payroll), regardless of clinical responsibility or patient contact.

• Licensed independent practitioners (LIPs): This includes physicians (MD, DO), advanced practice nurses, and physician assistants who are affiliated with the reporting facility, but are not directly employed by it (that is, they do not receive a paycheck from the facility), regardless of clinical responsibility or patient contact. Post-residency fellows are also included in this category if they are not on the facility's payroll.

• Adult students/trainees and volunteers: This includes all medical, nursing, or other health professional students, interns, medical residents, or volunteers aged 18 or over who are affiliated with the healthcare facility, but are not directly employed by it (that is, they do not receive a direct paycheck from the facility), regardless of clinical responsibility or patient contact.

• Other contract personnel: Contract personnel are defined as persons providing care, treatment, or services at the facility through a contract who do not fall into any of the above- mentioned denominator categories. This also includes vendors providing care, treatment, or services at the facility who may or may not be paid through a contract. Facilities are required to enter data on other contract personnel for submission in the NHSN application, but data from this category are not included in the HCP COVID–19 Vaccine measure.

The denominator excludes denominator-eligible individuals with contraindications as defined by the CDC. We did not propose any changes to the denominator exclusions.

We proposed the numerator would be the cumulative number of HCP in the denominator population who are considered up to date with CDC recommended COVID–19 vaccines. Providers would refer to the definition of up to date as of the first day of the applicable reporting quarter, which can be found at https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. For example, HCP would have been considered up to date during quarter 4 of the CY 2022 reporting period for the SNF QRP if they met one of the following criteria:

1. Individuals who received an updated bivalent booster dose, or

2a. Individuals who received their last booster dose less than 2 months ago, or

2b. Individuals who completed their primary series less than 2 months ago.

We refer readers to https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-rev-2023-508.pdf for more details on the measure specifications.

While we did not propose any changes to the data submission or reporting process for the HCP COVID–19 Vaccine measure, we proposed that for purposes of meeting FY 2025 SNF QRP compliance, SNFs would report HCP who are up to date beginning in quarter 4 of CY 2023. Under the data submission and reporting process, SNFs would collect the numerator and denominator for the modified HCP COVID–19 Vaccine measure for at least one self-selected week during each month of the reporting quarter and submit the data to the NHSN Long-Term Care Facility (LTCF) Component before the quarterly deadline. In the FY 2024 SNF PPS proposed rule (88 FR 21337), we incorrectly stated that SNFs would submit data to the NHSN Healthcare Personnel Safety (HPS) Component. We clarify that SNFs submit the data for this measure to the NHSN LTCF Component. We highlight that SNFs already submit data to the LTCF component of the NHSN for reporting of the HCP COVID–19 Vaccine measure. If a SNF submits more than 1 week of data in a month, the most recent week's data would be used to calculate the measure. Each quarter, the CDC would calculate a single quarterly HCP COVID–19 vaccination coverage rate for each SNF, which would be calculated by taking the average of the data from the 3 weekly rates submitted by the SNF for that quarter. Beginning with the FY 2026 SNF QRP, we proposed SNFs would be required to submit data for the entire calendar year. We also proposed that public reporting of the modified version of the HCP COVID–19 Vaccine measure would begin with the October 2024 Care Compare refresh or as soon as technically feasible.

We solicited public comment on our proposal to modify the HCP COVID–19 Vaccine measure beginning with the FY 2025 SNF QRP. We received several comments from interested parties who support vaccination of HCP and communities against COVID–19. They also agreed with our rationale underlying the proposal to adopt the modified measure in the SNF QRP because updating the measure numerator definition reflected the current science. However, many of these same commenters did not support the proposal itself for various reasons, including the lack of CBE endorsement, the perceived burden associated with collecting the data, and the definition of up to date. The following is a summary of the comments we received on our proposal to modify the HCP COVID–19 Vaccine measure beginning with the FY 2025 SNF QRP and our responses.

Comment: We received several supportive comments for our proposal to modify the numerator definition for the HCP COVID–19 Vaccine measure and to update the numerator to specify the time frames within which an HCP is considered up to date with recommended COVID–19 vaccines. Commenters note that nursing home residents have been disproportionately vulnerable throughout the COVID–19 pandemic, and although the PHE has ended, adherence to infection prevention and control measures is essential to the health, safety, and well-being of residents. Some commenters noted that access to transparent, complete, and easily understandable information is essential for residents to make informed decisions, and that public display of the vaccination rates on Care Compare provides vital information for residents and their caregivers. Other commenters also noted that despite CMS's withdrawal of the Omnibus COVID–19 Health Care Staff Vaccination Requirements, ⁵⁴ vaccinations are still one of the most effective infection prevention tools to protect staff, residents, and visitors against severe illness, hospitalization, and death.

Response: We thank the commenters for their support. We agree that vaccination plays a critical part in the nation's strategy to effectively counter the spread of COVID–19. We continue to believe it is important to incentivize and track HCP vaccination through quality measurement across care settings, including SNFs, in order to protect HCP, residents, and caregivers, and to help sustain the ability of HCP in SNFs to continue serving their communities.

Comment: Three commenters opposed the proposed modification and expressed concern that the modified version of the measure was not submitted for endorsement by a CBE before it was proposed for the SNF QRP. As a result, one of these commenters is concerned that the measure has not received a full evaluation of a range of issues affecting measure reliability, accuracy, and feasibility. This commenter also stated that the current version of the measure never went through a CBE endorsement process, and therefore, it has not yet had a holistic evaluation regarding whether the measure is working as intended.

Response: We refer the commenter to section VII.C.1.a.2. of this final rule, where we point out that the current version of the HCP COVID–19 Vaccine measure received endorsement by the CBE on July 26, 2022 under the name “Quarterly Reporting of COVID–19 Vaccination Coverage among Healthcare Personnel.” We note, however, that the measure received endorsement based on its specifications in the FY 2022 SNF PPS final rule (86 FR 42480 through 42489). Even though the current, endorsed version does not capture information about whether HCP are up to date with their COVID–19 vaccinations, we believe its previous endorsement speaks to the quality of the measure design for the proposed modified version, since many components of the previous measure remain intact in this modified version. Since we were unable to identify any CBE endorsed measures for SNFs that captured information on whether HCP are up to date with their COVID–19 vaccinations, and we found no other feasible and practical measure on this topic, we find the modification to the HCP COVID–19 Vaccine measure reasonable for SNF QRP adoption and implementation. The CDC, the measure developer, is pursuing CBE endorsement for the modified version of the HCP COVID–19 Vaccine measure.

In terms of measure testing, as mentioned in section VII.C.1.a.1.b. of this final rule, we reiterate that the CDC conducted beta testing of the modified HCP COVID–19 Vaccine measure and concluded that the collection of information on booster doses received by HCP was feasible with a high reporting rate and the measure score displayed a performance gap indicating clinically significant differences in booster dose vaccination coverage rates among SNFs. We will continue to monitor the measure to identify any concerning trends as part of our routine monitoring activities to regularly assess measure performance, reliability, and reportability for all data submitted for the SNF QRP.

Comment: A number of commenters expressed concerns with the evolving nature of the measure's definition of up to date. Commenters suggested that the definition will quickly and frequently become outdated, and that a measure with a “moving set of goalposts” is challenging for HCP to understand. As a result, these changes to the definition could result in an inaccurate reporting of HCPs' up to date vaccination rates. Another commenter was concerned that any inconsistencies in the up to date definitions and potential inaccuracies associated with the rapid translation of complex vaccination recommendations may cause confusion among SNFs and negatively impact vaccine uptake. Finally, one commenter suggested that without a regular cadence of boosters or a defined COVID–19 “season,” like influenza, modifying the numerator definition to up to date is premature.

Response: We recognize that the up to date COVID–19 vaccination definition may evolve due to the changing nature of the virus, but we are also confident in HCPs' ability to understand these changes as they have been at the front lines of managing COVID–19 since the beginning of the pandemic. Since the adoption of the current version of the measure, the public health response to COVID–19 has necessarily adapted to respond to the changing nature of the virus's transmission and community spread. As mentioned in the FY 2022 SNF PPS final rule (86 FR 42481 through 42482), we received several public comments during the measure's pre-rulemaking process encouraging us to continue to update the measure as new evidence on COVID–19 continues to arise and we stated our intention to continue to work with our partners, including the FDA and CDC, to consider any updates to the measure in future rulemaking as appropriate. We believe that the proposed modification to this measure aligns with our responsive approach to COVID–19 and will continue to support vaccination as the most effective means to prevent the worst consequences of COVID–19, including severe illness, hospitalization, and death.

Comment: One commenter who supported the proposal to modify the HCP COVID–19 Vaccine numerator definition also recommended that the measure should explicitly specify for HCP to receive primary series and booster vaccine doses to align with the recommendations on bivalent booster doses, including being up to date.

Response: We agree with the commenter, and highlight that the proposed modification to the HCP COVID–19 Vaccine measure numerator is in alignment with CDC recommendations as found on the following CDC NHSN web page: https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. At the beginning of each reporting period and before collecting or submitting data on this modified measure, SNFs must refer to the aforementioned document to determine the then-applicable definition of up to date to apply when collecting data on the vaccination status of HCP for that quarterly reporting period.

Comment: One commenter noted that CDC's vaccination guidance suggests that some individuals with certain risk factors should consider receiving a booster dose within 4 months of receiving their first bivalent dose. The commenter noted that SNFs usually do not have routine access to data to know which of their HCPs may need a booster dose. The commenter was concerned that, to collect accurate data, SNFs would have to obtain permission to inquire and obtain information on each individual HCP's underlying health risk factors and a mechanism to keep the data fully secure. As a result, they expressed concern that the resource intensiveness of collecting data under the CDC's proposed modified definition for the HCP COVID–19 Vaccine measure may outweigh its value.

Response: SNFs have been engaging with their staff for almost 2 years to obtain information on their COVID–19 vaccination status. The proposed modification to the HCP COVID–19 Vaccine measure should not require any changes to how SNFs currently engage with their staff and administer a comprehensive vaccine administration strategy. We are also confident in SNF's ability to utilize the available CDC resources to keep themselves informed as they have been at the front lines of managing COVID–19 since the beginning of the pandemic. Specifically, we note that considerations for immunocompromised persons are not impacted by the modification proposed to this measure as these considerations are present with the primary vaccination series for the current HCP COVID–19 Vaccine measure. As emphasized in the CDC NHSN “COVID–19 Vaccination Modules: Understanding Key Terms and Up to Date Vaccination” web page https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf referred to in section VII.C.1.a.4. of this final rule, the NHSN surveillance definition for up to date is currently the same for all HCP regardless of immunocompromised status.

Comment: Two commenters expressed concern that modifications to the HCP COVID–19 Vaccine measure may exacerbate workforce shortages. One commenter noted that while the measure does not mandate up to date COVID–19 vaccinations for HCP, it may affect how SNFs approach vaccination requirements. One of these commenters mentioned that HCP may choose to work in other health care settings where such a mandate or quality measure does not exist, and the other commenter suggested they will choose to work in other areas of commerce.

Response: We disagree that the proposed modification to the numerator definition of the HCP COVID–19 Vaccine measure may exacerbate workforce shortages. We believe that the risks associated with COVID–19 warrant direct attention, especially because HCP are working directly with, and in close proximity to, residents. We clarify that the HCP COVID–19 Vaccine measure does not require SNFs to adopt mandatory vaccination policies, and it is a SNF's responsibility to determine their own personnel policies. To support a comprehensive vaccine administration strategy, we encourage SNFs to voluntarily engage in the provision of appropriate and accessible education and vaccine-offering activities. Many SNFs across the country are educating staff, residents, and residents' representatives, participating in vaccine distribution programs, and reporting up to date vaccine administration. The CDC has a number of resources available to SNFs to assist in building vaccine confidence. CMS also has a web page to help providers, including SNFs, find resources related to the COVID–19 vaccines. There are several toolkits and videos SNFs can use to stay informed and to educate their HCP, residents and communities about the COVID–19 vaccines.

Comment: Several commenters expressed concern with the measure's administrative burden, especially with having to track whether HCP meet the new requirements when the up to date definition changes. Another commenter suggested that because SNFs do not currently report booster doses to the NHSN, the proposal will require facility staff to spend more time tracking this information which will redirect resources away from direct resident care, particularly for smaller facilities without sophisticated software. Finally, one commenter expressed conditional support for the modification to the HCP COVID–19 measure but requested CMS reduce the reporting burden associated with the measure. This commenter requested that CMS and the CDC work with SNFs to identify opportunities to simplify and streamline any reporting burdens associated with the measure.

Response: We appreciate commenters' concerns regarding the reporting of the measure. SNFs have been reporting the current version of the measure since the measure's initial data submission period (October 1, 2021 through December 31, 2021), and we believe that there has been sufficient time to allocate the necessary resources required to report this measure. We note that the CDC used the up to date numerator definition during the Quarter 4 2022 surveillance period (September 26, 2022 through December 25, 2022) for purposes of NHSN surveillance, and SNFs have been successfully reporting the measure in alignment with the proposed modifications since that time. To assess the burden of reporting booster doses, the CDC conducted feasibility analysis of the modified HCP COVID–19 Vaccine measure by calculating the proportion of facilities that reported booster doses of the COVID–19 vaccine. As mentioned in section VII.C.1.a.1.b. of this final rule, feasibility of reporting booster doses of vaccine is evident by the fact that 99.2 percent of SNFs reported vaccination booster dose coverage data to the NHSN for the first quarter of 2022. Based on the high reportability, we do not believe the proposed change would impose overwhelming burden.

The CDC provides frequent communications and education to support SNFs' understanding of the latest guidelines. CDC posts an updated document approximately 2 weeks before the start of a new reporting quarter. If there are any changes to the definition, forms, etc., CDC will host a webinar in the 1–2 weeks before the beginning of a new reporting quarter. If SNFs have any concerns they would like to address regarding the data submission of this measure, they can voice their concerns during CMS' SNF/LTC Open Door Forums (ODFs). For more information on ODFs and to sign up for email notifications, we refer readers to the following CMS web page: https://www.cms.gov/outreach-and-education/outreach/opendoorforums/odf_snfltc.

Comment: One commenter emphasized that the reporting burden stems from the high frequency reporting cadence as well as the number of individuals included in the measure denominator. The same commenter stated that up to date COVID–19 vaccination data would not be easy to track, requires multiple processes, and frequent multiple software applications.

Response: We emphasize that we proposed no changes to the measure's reporting frequency, reporting method, or denominator population. SNFs have been successfully reporting at this cadence on the same HCP population since October 1, 2021.

Comment: Two commenters recommended the HCP COVID–19 Vaccine measure should be voluntary until there is a stable definition for up to date.

Response: The HCP COVID–19 Vaccine measure was adopted into the SNF QRP in the FY 2022 SNF PPS Final Rule (86 FR 42480 through 42489). We proposed to modify the definition of the measure numerator and the time frames for reporting and did not make any proposed changes to the measure denominator or the minimum reporting threshold for compliance. Therefore, successful reporting of the measure is still part of the SNF QRP reporting requirements.

Comment: One commenter raised concerns with the potential inaccuracy of the measure because the term up to date may continue to evolve with new vaccines and vaccine formulations.

Response: In response to the commenter's concerns that the up to date numerator definition may evolve, we refer commenters to section VII.C.1.a.4. of this final rule where we discuss how SNFs would refer to the definition of up to date as of the first day of the quarter, which can be found at the following CDC NHSN web page at https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. The CDC notes that this document will be updated quarterly to reflect any changes as COVID–19 guidance evolves, and notes that SNFs would use the definitions for the reporting period associated with the reporting weeks included in data submission. As such, the up to date vaccination definition that would be applicable during a particular reporting period would not change, which addresses any concern that there would not be a single consistent resource for reporting instructions when the definition of up to date is revised. If the requirements do change from one quarter to the next, SNFs would have the up to date definition at the beginning of the quarter (using the aforementioned CDC NHSN web page), and have a minimum of three weeks to assess whether their HCP meet the definition of up to date before submitting HCP COVID–19 Vaccine measure data during the self-selected week of a corresponding month.

Comment: A number of commenters stated that while they support COVID–19 vaccination as one of the strongest measures for preventing serious illness and/or death from COVID–19, they do not believe the HCP COVID–19 Vaccine measure is an indicator of whether a SNF provides high quality of care to residents. Commenters noted that the measure, as currently written, reflects personal choice and represents outcomes over which SNFs have no control. Another commenter stated that staff acceptance of the COVID–19 vaccine reflects the community in which they reside, their own culture and beliefs, as well as their own health status. This commenter urged CMS to withdraw the HCP COVID–19 Vaccine measure from the SNF QRP and instead create a process measure to collect data on the outreach and education efforts that SNFs have undertaken to encourage up to date vaccination among staff. One commenter noted that differences in vaccine uptake are often deeply rooted in culture, religion, ethnicity, socioeconomic status, and more. Therefore, they believe that while SNFs will continue to educate their staff and encourage employee vaccinations, they should not be used to measure a SNF's ability to provide a safe environment. Finally, one commenter requested that CMS remind the public that vaccination is not mandatory for HCP, and as a result, the reported vaccination rate performance may vary based on local vaccine hesitancy barriers rather than provider effort at encouraging all HCP to be vaccinated.

Response: We disagree with the commenters and believe that the HCP COVID–19 Vaccine measure is an indicator of the quality of care in a SNF. We direct readers to section VII.C.1.a.1.a. of this final rule where we provide information illustrating that in the presence of a high community prevalence of COVID–19, residents of facilities with low staff vaccination coverage had cases of COVID–19-related deaths 195 percent higher than those among residents of facilities with high vaccination coverage. Therefore, we find that a SNF's HCP COVID–19 vaccination rate, including booster doses, is an important quality indicator. We acknowledge that vaccination rates may be influenced by staff's culture, beliefs, community, and geographic areas, but we also know that HCP may come into contact with SNF residents, increasing the risk for HCP-to-resident transmission of infection. Therefore, we believe the measure as proposed has the potential to generate actionable data on up to date HCP COVID–19 vaccination rates that can be used to target quality improvement among SNFs, including increasing up to date HCP COVID–19 vaccination coverage in SNFs, while also promoting resident safety and increasing the transparency of quality of care in the SNF setting. Furthermore, we appreciate the suggestion for a quality measure to collect data on the outreach and education efforts that SNFs have undertaken to encourage up to date vaccination among staff and will use this input to inform our future measure development efforts. Finally, in relation to the commenter requesting us to remind the public that HCP vaccination is not mandatory, we assume that the commenter is recommending adding this reminder to the Care Compare web page. We appreciate the commenter's suggestion and will consider it when the modified HCP COVID–19 Vaccine measure is publicly reported on Care Compare.

Comment: One commenter opposed the measure's modified numerator definition because the FDA has not fully authorized the bivalent booster, rather it remains available under an Emergency Use Authorization (EUA).

Response: We note that, on August 31, 2022, the FDA amended the EUAs for the Moderna COVID–19 vaccine and the Pfizer-BioNTech COVID–19 vaccine to authorize bivalent formulations of the vaccines for use as a single booster dose at least two months following primary or booster vaccination. See more details in section VII.C.1.a.1. of this final rule. We would like to refer readers to the FDA website for additional information related to FDA process for evaluating an EUA request at https://www.fda.gov/vaccines-blood-biologics/vaccines/emergency-use-authorization-vaccines-explained. In addition, we emphasize that the FDA is closely monitoring the safety of the COVID–19 vaccines authorized for emergency use. We believe that due to the ongoing risk of infection transmissions in the SNF population, the benefits of finalizing the modified up to date definition of the measure in this year's final rule is essential for patient safety.

Comment: Several commenters opposed the proposed modifications to the HCP COVID–19 Vaccine measure, and the most frequently cited reason was that the COVID–19 PHE ended on May 11, 2023 and CMS subsequently lifted staff vaccination requirements established under § 483.80(i). One commenter was concerned that the data reporting requirements associated with the measure will divert already stretched resources from resident care to administrative processes. Another commenter thought it was counter-intuitive for CMS to end vaccination mandates for HCP while seeking to amend the numerator for this measure. One commenter called for an elimination of the HCP COVID–19 Vaccine measure in the SNF QRP, while another commenter stated that they were comfortable with continuing to report on the measure during 2024 as the Administration and the broader healthcare ecosystem continue to assess what COVID–19 looks like moving forward. This commenter encouraged CMS to continue to evaluate and revisit the measure's requirements.

Response: We do not agree with commenters suggesting that because the PHE ended, and we lifted the staff vaccination requirements, that there is no value in retaining the HCP COVID–19 Vaccine measure in the SNF QRP. We believe this measure continues to align with our goals to promote wellness and disease prevention. Under CMS' Meaningful Measures Framework 2.0, the HCP COVID–19 Vaccine measure addresses the quality priorities of “Immunizations” and “Public Health” through the Meaningful Measures Area of ` “Wellness and Prevention.” Under the National Quality Strategy, the measure addresses the goal of Safety under the priority area Safety and Resiliency. While the end of the PHE may result in removing vaccination requirements from the LTC Conditions of Participation, we note that the reporting requirements of the SNF QRP for the proposed modified version of the HCP COVID–19 Vaccine measure are distinct from those cited by the commenter. Specifically, the SNF QRP is a pay-for-reporting program, and therefore the inclusion of this measure in the SNF QRP does not require that HCP actually receive these booster vaccine doses in order for the SNF to successfully participate in the SNF QRP. Our continued response to COVID–19 is not fully dependent on the emergency declaration for the COVID–19 PHE, and even beyond the end of the COVID–19 PHE, we will continue to work to protect individuals and communities from the virus and its worst impacts by supporting access to COVID–19 vaccines, treatments, and tests.

Comment: One additional commenter requested clarification on whether the White House's announcement to end COVID–19 vaccination requirements and/or “mandates” will impact the adoption or use of the proposed HCP COVID–19 Vaccine measure in the SNF QRP.

Response: We clarify that the vaccination requirements under § 483.80(i) (which have now been lifted) are separate from SNF QRP requirements to report HCP COVID–19 vaccination data. Even though the PHE has ended, and vaccination requirements have been lifted, CMS intends to encourage ongoing COVID–19 vaccination through use of its quality reporting programs (88 FR 36487). One way to encourage resident safety and COVID–19 vaccination is through adoption of the modified up to date numerator definition of the HCP COVID–19 Vaccine measure. Despite the White House's announcement, the SNF QRP still requires data submission of the HCP COVID–19 Vaccine measure to the NHSN for SNFs to remain in compliance with the SNF QRP reporting requirements. However, since the SNF QRP is a pay-for-reporting program, HCP receiving COVID–19 vaccination is not mandated by this measure.

Comment: One commenter noted the proposed rule stated that data will be submitted through the Healthcare Personnel Safety (HPS) component of NHSN (88 FR 21337), and they point out that the data are actually submitted through the Long-Term Care Facility (LTCF) component as part of the SNF regulatorily required reporting.

Response: We thank the commenter and acknowledge that in the FY 2024 SNF PPS proposed rule (88 FR 21337), we incorrectly stated that SNFs would submit data to the NHSN HPS component. We clarify that, in alignment with the current version of the measure established in the FY 2022 SNF PPS final rule, SNFs will continue to submit HCP COVID–19 Vaccine data under this modified measure to the LTCF component of the CDC's NHSN before the quarterly deadline. We refer readers to section VII.C.1.a.4. of this final rule, where we have remediated this error.

Comment: One commenter questioned why CMS would delay the modification to the HCP COVID–19 Vaccine measure to 2025, rather than implementing it now. They stated a delay may prove unnecessary given the uncertain future of COVID–19 and the efficacy and availability of COVID–19 vaccines over time.

Response: We refer the commenter to section VII.C.1.a.4 of this final rule where we proposed SNFs would report individuals who are up to date beginning in quarter four of CY 2023. To clarify, data reported in CY 2023 comply with the requirements for the FY 2025 SNF QRP.

Comment: One commenter questioned why CMS has prioritized use of the NHSN over State-run Immunization Information Systems (IIS) for data reporting. This commenter noted that IIS are more robust and allow for greater clarity on vaccination status as healthcare professionals and individuals transition throughout the health care system.

Response: We did not propose to modify the method of data submission for the HCP COVID–19 Vaccine measure. As we stated in the FY 2022 SNF PPS Final Rule (86 FR 42494), we understand IIS to be confidential, population-based, computerized databases that record immunization doses administered by participating providers to persons residing within a given geopolitical area, but these systems are not standardized across all SNFs. HHS has an Immunization Information Systems Support Branch (IISSB) that facilitates the development, implementation, and acceptance of these systems, but they are overseen by the States and/or organizations who develop them. In the FY 2022 SNF PPS final rule (86 FR 42493), we adopted the use of the NHSN COVID–19 Modules for tracking HCP COVID–19 vaccination rates across all sites of service, including SNFs, because most of the state IIS do not include the information needed to calculate the HCP COVID–19 Vaccine measure. Since SNFs have successfully reported HCP COVID–19 vaccination rates since the measure's initial data submission period (October 1, 2021 through December 31, 2021), we will continue using the CDC's NHSN as the measure's data submission platform.

Comment: One commenter expressed concerns with the validity of any COVID–19 vaccination measure that uses self-reported data from SNFs and their HCP and encouraged CMS to develop data sources beyond those that are self-reported. This commenter recommends that CMS develop and implement auditing and penalty systems to detect and respond to inaccurate or falsified data.

Response: We emphasize that we currently implement multiple processes to ensure self-reported data are accurate. As part of our measure monitoring and compliance determination processes, we scrutinize provider data submission for all SNF QRP measures, including those for NHSN measures. We look for any performance gaps or discordant performance in measures that may indicate issues with data submission.

Comment: One commenter suggested that if the measure continues to be included in the SNF QRP, CMS should reduce the burden of gathering data from all personnel captured within the measure's denominator population.

Response: We did not propose changes to the measure denominator and disagree that the denominator criteria should be loosened. We emphasize that any HCP working in the facility for at least one working day during the reporting period, meeting denominator eligibility criteria, may come into contact with SNF residents, increasing the risk for HCP-to-resident transmission of infection. Therefore, we believe the measure as proposed has the potential to increase up to date COVID–19 vaccination coverage in SNFs, promote resident safety, and increase the transparency of quality of care in the SNF setting.

Comment: One commenter urged CMS to expand the criteria of HCP that are exempted beyond those with contraindications as defined by the CDC because there are numerous reasons HCP may decide whether to be up to date on vaccinations. One commenter specifically took issue with the measure's lack of religious exemptions. Another commenter was concerned that a SNF could be unfairly penalized for following CDC guidelines while delivering care that focuses on supporting individuals' ability to choose the recommended vaccine option that best suits their needs and preferences. This commenter suggested alignment of the HCP COVID–19 Vaccine measure's up to date definition with that of the Advisory Committee on Immunization Practices (ACIP) and recommended that the measure allow HCP to choose the vaccine option that best suits their needs and preferences.

Response: We acknowledge that numerous factors may impact an individual's decision to receive up to date vaccinations, such as sincerely held religious beliefs, observances, or practices. However, we emphasize that any HCP may come into contact with SNF residents, increasing the risk for HCP-to-resident transmission of infection. Therefore, we believe the measure as proposed has the potential to increase up to date HCP COVID–19 vaccination coverage in SNFs, promote resident safety, and increase the transparency of quality of care in the SNF setting. Additionally, we want to reiterate that neither the current version nor the proposed modified version of the measure mandate that HCP be up to date on their COVID–19 vaccine. The HCP COVID–19 Vaccine measure only requires reporting of vaccination rates for a SNF to successfully participate in the SNF QRP. Therefore, this measure is not preventing anyone from choosing a vaccine option that best suits their beliefs or preferences. In regard to the comment about aligning the measure's up to date definition with that of ACIP, the CDC's and ACIP's definitions are currently aligned. Additionally, we note that recommendations made by the ACIP are reviewed by the CDC and published as the official CDC recommendation if adopted.

Comment: One commenter stated that the CDC maintains guidance that receiving a dose of the COVID–19 vaccine may or should be delayed if a person has recently had the COVID–19 infection. This may impact the timing of an employee's up to date vaccine dosage.

Response: The CDC recommends that individuals who recently had a COVID–19 infection should still stay up to date with vaccines; however, individuals may consider delaying their next vaccine dose by three months from when (i) symptoms began, or (ii) initial receipt of a positive COVID–19 test. The CDC reiterates that certain factors could be reasons for individuals to receive up to date vaccinations sooner rather than later, including (i) personal risk of severe disease, (ii) risk of disease among close contacts, (iii) local COVID–19 hospital admission level, and (iv) the most common COVID–19 variant currently causing illness. Since the CDC recommends that individuals stay up to date on vaccines regardless of recent COVID–19 infection, and since HCP often come into close contact with individuals at risk of disease, we do not agree that a recent COVID–19 infection would prevent HCP from receiving up to date COVID–19 vaccinations.

Comment: One commenter recommended that the measure should be revised to cover all CDC-recommended vaccines, and that the measure can be revised periodically as CDC guidance changes.

Response: We thank the commenter for this suggestion and will use this input to inform our future measure development efforts.

Comment: One commenter requested CMS mandate that all SNF HCP receive an up to date COVID–19 vaccination.

Response: Staff COVID–19 vaccination is no longer required under § 483.80(i). We continue to encourage ongoing COVID–19 vaccination through our quality reporting and value-based incentive programs. We emphasize that the proposed modifications to the HCP COVID–19 Vaccine measure for the SNF QRP do not mandate HCP COVID–19 vaccination.

Comment: Although generally supportive of the HCP COVID–19 Vaccine modifications to the up to date numerator definition, a few commenters recommended that CMS revise the measure to only require annual reporting, which would align with reporting requirements for the HCP Influenza Vaccine measure.

Response: As we stated in the FY 2024 SNF PPS proposed rule (88 FR 21336), the measure developer, the CDC, noted that the model used for this measure is based on the Influenza Vaccination Coverage among HCP measure (CBE #0431), and it intends to utilize a similar approach for the HCP COVID–19 Vaccine measure if the vaccination strategy becomes seasonal. We continue to monitor COVID–19 as part of our public health response and will consider these data to inform any potential action that may address seasonality in future rulemaking.

We also received comments related to the public reporting of the modified HCP COVID–19 Vaccine measure.

Comment: One commenter emphasized the importance of publicly reporting the HCP COVID–19 Vaccine measure on Care Compare, and recommended CMS coordinate public display of the HCP COVID–19 vaccine with existing measures of staff and resident COVID–19 vaccination and rates to avoid confusion or duplication. This commenter also suggested CMS include demographic information in the public display of the data in order to highlight potential disparities similar to those already uncovered about COVID–19 variation within facilities and among residents. Finally, this commenter stated CMS should give strong consideration to providing results to facilities that are stratified for race, ethnicity, and other social risk factors based on information submitted by facilities.

Response: We thank the commenter for their suggestions. However, as described in section VII.C.1.a.3. of this final rule, the measure developer (CDC) stated that the measure could not be stratified by demographic factors since the data are submitted at an aggregate rather than an individual level. We will continue to assess methods of incorporating health equity into the SNF QRP. In response to the commenter's recommendation to align the way in which measures of staff vaccination are presented on Care Compare, we appreciate this suggestion and will take it into consideration.

Comment: Several commenters were concerned with the delay between data submission via the NHSN and public reporting on Care Compare. One commenter emphasized that staff in SNFs may change over time so publicly reported measure data will become outdated quickly. Another commenter stated the delay between when the information is collected and when it is actually publicly reported could cause confusion and damage the public's trust and confidence in the quality of care delivered in their community if the rate of up to date HCP vaccination is low due to the data lag.

Response: We agree that it is important to make the most up to date data available to beneficiaries and ensure timely display of publicly reported data. Therefore, as mentioned in the FY 2022 SNF PPS final rule (86 FR 42496 through 42497), we revised our public reporting policy for this measure to use quarterly reporting, which allows the most recent quarter of data to be displayed, as opposed to an average of four rolling quarters. Additionally, the public display schedule of the HCP COVID–19 Vaccine measure aligns with SNF QRP public display policies finalized in the FY 2017 SNF PPS final rule (81 FR 52041), which allows SNFs to submit their SNF QRP data up to 4.5 months after the end of the reporting quarter. A number of administrative tasks must then occur in sequential order between the time SNF QRP data are submitted and reported in Care Compare to ensure the validity of data and to allow SNFs sufficient time to request a review of their data during the preview period if they believe the quality measure scores that are displayed within their Preview Reports are inaccurate. We believe this reporting schedule, outlined in section VII.C.1.a.4. of this final rule is reasonable, and expediting this schedule may establish undue burden on SNFs and jeopardize the integrity of the data.

Additionally, in response to the comment that staff in SNFs may change over time, we emphasize that it is precisely because staff in SNF's change that monitoring COVID–19 up to date vaccination rates over time is important.

Comment: One commenter pointed out that it may mean that HCPs who count as up to date in one quarter may no longer be up to date in the next quarter and CMS needs to clearly communicate what publicly reported data reflect.

Response: We agree with the commenter that pointed out that HCP who count as up to date in one quarter may no longer be up to date in the next quarter. We note that each provider will be measured against the same criteria within the same quarter, and the guideline for each quarter will be shared through the CDC's website ahead of each quarter. Regarding the data collection period used for public reporting, this information can be retrieved through the Care Compare site through “View Quality Measures,” and then clicking on “Get current data collection period.”

Comment: One commenter noted that changing CDC definitions are challenging for healthcare professionals, and they do not believe that this information can be articulated in a manner for residents to fully digest in order to make meaningful healthcare decisions.

Response: We believe residents will be able to understand what changes to the up to date definition mean on Care Compare. We note that the public has been using the information displayed on Care Compare for the current HCP COVID–19 Vaccine measure since it was first publicly reported in 2022. We work closely with our Office of Communications and consumer groups when onboarding measures to the Care Compare websites, and we will do the same with the modified HCP COVID–19 Vaccine measure to ensure that the measure description on Care Compare is clear and understandable for the general public.

After careful consideration of the public comments we received, we are finalizing our proposal to modify the HCP COVID–19 Vaccine measure beginning with the FY 2025 SNF QRP as proposed.

b. Discharge Function Score Measure Beginning With the FY 2025 SNF QRP

(1) Background

SNFs provide short-term skilled nursing care and rehabilitation services, including physical and occupational therapy and speech-language pathology services. The most common resident conditions are septicemia, joint replacement, heart failure and shock, hip and femur procedures (not including major joint replacement), and pneumonia. Septicemia progressing to sepsis is often associated with long-term functional deficits and increased mortality in survivors. Rehabilitation of function, however, has been shown to be effective and is associated with reducing mortality and improving quality of life.

Section 1888(e)(6)(B)(i) of the Act, cross-referencing subsections (b), (c), and (d) of section 1899B of the Act, requires us to develop and implement standardized quality measures from five quality measure domains, including the domain of functional status, cognitive function, and changes in function and cognitive function across the post-acute care (PAC) settings, including SNFs. To satisfy this requirement, we adopted the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) measure, for the SNF QRP in the FY 2016 SNF PPS final rule (80 FR 46444 through 46453). While this process measure allowed for the standardization of functional assessments across assessment instruments and facilitated cross-setting data collection, quality measurement, and interoperable data exchange, we believe it is now topped out and proposed to remove it in the FY 2024 SNF PPS proposed rule (88 FR 21342). While there are other outcome measures addressing functional status that can reliably distinguish performance among providers in the SNF QRP, these outcome measures are not cross-setting in nature because they rely on functional status items not collected in all PAC settings. In contrast, a cross-setting functional outcome measure would align measure specifications across settings, including the use of a common set of standardized functional assessment data elements.

(a) Measure Importance

Maintenance or improvement of physical function among older adults is increasingly an important focus of health care. Adults age 65 years and older constitute the most rapidly growing population in the United States, and functional capacity in physical (non-psychological) domains has been shown to decline with age. Moreover, impaired functional capacity is associated with poorer quality of life and an increased risk of all-cause mortality, postoperative complications, and cognitive impairment, the latter of which can complicate the return of a resident to the community from post-acute care. Nonetheless, evidence suggests that physical functional abilities, including mobility and self-care, are modifiable predictors of resident outcomes across PAC settings, including functional recovery or decline after post-acute care,^{73 74 75} rehospitalization rates, discharge to community, and falls.

The implementation of interventions that improve residents' functional outcomes and reduce the risks of associated undesirable outcomes as a part of a resident-centered care plan is essential to maximizing functional improvement. For many people, the overall goals of SNF care may include optimizing functional improvement, returning to a previous level of independence, maintaining functional abilities, or avoiding institutionalization. Studies have suggested that rehabilitation services provided in SNFs can improve residents' mobility and functional independence for residents with various diagnoses, including cardiovascular and pulmonary conditions, orthopedic conditions, and stroke. Moreover, studies found an association between the level of therapy intensity and better functional improvement, suggesting that assessment of functional status as a health outcome in SNFs can provide valuable information in determining treatment decisions throughout the care continuum, such as the need for rehabilitation services, and discharge planning, as well as provide information to consumers about the effectiveness of skilled nursing services and rehabilitation services delivered. Because evidence shows that older adults experience aging heterogeneously and require individualized and comprehensive health care, functional status can serve as a vital component in informing the provision of health care and thus indicate a SNF's quality of care.

We proposed to adopt the Discharge Function Score (DC Function) measure in the SNF QRP beginning with the FY 2025 SNF QRP. This assessment-based outcome measure evaluates functional status by calculating the percentage of Medicare Part A SNF residents who meet or exceed an expected discharge function score. We also proposed to replace the topped-out Application of Functional Assessment/Care Plan process measure with the DC Function measure. Like the cross-setting process measure we proposed to remove in the FY 2024 SNF PPS proposed rule (88 FR 21342), the DC Function measure is calculated using standardized resident assessment data from the current SNF assessment tool, the Minimum Data Set (MDS).

The DC Function measure supports our current priorities. Specifically, the measure aligns with the Streamline Quality Measurement domain in CMS's Meaningful Measurement 2.0 Framework in two ways. First, the proposed outcome measure would further our objective to prioritize outcome measures by replacing the current cross-setting process measure (see FY 2024 SNF PPS proposed rule 88 FR 21342). This proposed DC Function measure uses a set of cross-setting assessment items which would facilitate data collection, quality measurement, outcome comparison, and interoperable data exchange among PAC settings; existing functional outcome measures do not use a set of cross-setting assessment items. Second, this measure would add no additional provider burden since it would be calculated using data from the MDS that SNFs are already required to collect.

The proposed DC Function measure also follows a calculation approach similar to the existing functional outcome measures, which are CBE endorsed, with some modifications. Specifically, the measure (1) considers two dimensions of function (self-care and mobility activities) and (2) accounts for missing data by using statistical imputation to improve the validity of measure performance. The statistical imputation approach recodes missing functional status data to the most likely value had the status been assessed, whereas the current imputation approach implemented in existing functional outcome measures recodes missing data to the lowest functional status. A benefit of statistical imputation is that it uses resident characteristics to produce an unbiased estimate of the score on each item with a missing value. In contrast, the current approach treats residents with missing values and residents who were coded to the lowest functional status similarly, despite evidence suggesting varying measure performance between the two groups, which can to lead less accurate measure performances.

(b) Measure Testing

Our measure developer conducted testing using FY 2019 data on the DC Function measure to assess validity, reliability, and reportability, all of which informed interested parties' feedback and Technical Expert Panel (TEP) input (see FY 2024 SNF PPS proposed rule 88 FR 21340 through 21341). Validity was assessed for the measure performance, the risk adjustment model, face validity, and statistical imputation models. Validity testing of measure performance entailed determining Spearman's rank correlations between the proposed measure's performance for providers with 20 or more stays and the performance of other publicly reported SNF quality measures. Results indicated that the measure captures the intended outcome based on the directionalities and strengths of correlation coefficients and are further detailed below in Table 12.

Validity testing of the risk adjustment model showed good model discrimination as the measure model has the predictive ability to distinguish residents with low expected functional capabilities from those with high expected functional capabilities. The ratios of observed-to-predicted discharge function score across eligible stays, by deciles of expected functional capabilities, ranged from 0.99 to 1.01. Both the Cross-Setting Discharge Function TEPs and resident-family feedback showed strong support for the face validity and importance of the proposed measure as an indicator of quality of care (see FY 2024 SNF PPS proposed rule 88 FR 21340 through 21341). Lastly, validity testing of the measure's statistical imputation models indicated that the models demonstrate good discrimination and produce more precise and accurate estimates of function scores for items with missing scores when compared to the current imputation approach implemented in SNF QRP functional outcome measures, specifically the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure (Change in Self-Care Score), the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure (Change in Mobility Score), the Application of IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients measure (Discharge Self-Care Score), and the Application of IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients measure (Discharge Mobility Score) measures.

Reliability and reportability testing also yielded results that support the measure's scientific acceptability. Split-half testing revealed the proposed measure's good reliability, indicated by an intraclass correlation coefficient value of 0.81. Reportability testing indicated high reportability (85 percent) of SNFs meeting the public reporting threshold of 20 eligible stays. For additional measure testing details, we refer readers to the document titled Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report.

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act be endorsed by the CBE with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

The proposed DC Function measure is not CBE endorsed, so we considered whether there are other available measures that: (1) assess both functional domains of self-care and mobility in SNFs and (2) satisfy the requirement of the Act to specify quality measures with respect to functional status, cognitive function, and changes in function and cognitive function across the PAC settings. While the Application of Functional Assessment/Care Plan measure assesses both functional domains and satisfies the Act's requirement, this cross-setting process measure is not CBE endorsed and the measure's performance among SNFs is so high and unvarying across most SNFs that the measure no longer offers meaningful distinctions in performance. Additionally, after review of other measures endorsed or adopted by a consensus organization, we were unable to identify any measures endorsed or adopted by a consensus organization for SNFs that meet the aforementioned requirements. While the SNF QRP includes CBE endorsed outcome measures addressing functional status, they each assess a single domain of function, and are not cross-setting in nature because they rely on functional status items not collected in all PAC settings.

Therefore, after consideration of other available measures, we find that the exception under section 1899B(e)(2)(B) of the Act applies and proposed to adopt the DC Function measure, beginning with the FY 2025 SNF QRP. We intend to submit the proposed measure to the CBE for consideration of endorsement when feasible.

(3) Interested Parties and Technical Expert Panel (TEP) Input

In our development and specification of this measure, we employed a transparent process in which we sought input from interested parties and national experts and engaged in a process that allowed for pre-rulemaking input, in accordance with section 1890A of the Act. To meet this requirement, we provided the following opportunities for input from interested parties: a focus group of patient and family/caregiver advocates (PFAs), two TEPs, and public comments through a request for information (RFI).

First, the measure development contractor convened a PFA focus group, during which residents and caregivers provided support for the proposed measure concept. Participants emphasized the importance of measuring functional outcomes and found self-care and mobility to be critical aspects of care. Additionally, they expressed an interest in measures assessing the number of residents discharged from particular facilities with improvements in self-care and mobility, and their views of self-care and mobility aligned with the functional domains captured by the proposed measure. All feedback was used to inform measure development efforts.

The measure development contractor for the DC Function measure subsequently convened TEPs on July 14 to 15, 2021 and January 26 to 27, 2022 to obtain expert input on the development of a cross-setting function measure for use in the SNF QRP. The TEPs consisted of interested parties with a diverse range of expertise, including SNF and PAC subject matter knowledge, clinical expertise, resident and family perspectives, and measure development experience. The TEPs supported the proposed measure concept and provided substantive feedback regarding the measure's specifications and measure testing data.

First, the TEP was asked whether they prefer a cross-setting measure that is modeled after the currently adopted Discharge Mobility Score and Discharge Self-Care Score measures, or one that is modeled after the currently adopted Change in Mobility Score and Change in Self-Care Score measures. With the Discharge Mobility Score and Change in Mobility Score measures and the Discharge Self-Care Score and Change in Self-Care Score measures being both highly correlated and not appearing to measure unique concepts, the TEP favored the Discharge Mobility Score and Discharge Self-Care Score measures over the Change in Mobility Score and Change in Self-Care Score measures and recommended moving forward with utilizing the Discharge Mobility Score and Discharge Self-Care Score measures' concepts for the development of a cross-setting measure.

Second, in deciding the standardized functional assessment data elements to include in the cross-setting measure, the TEP recommended removing redundant data elements. Strong correlations between scores of functional items within the same functional domain suggested that certain items may be redundant in eliciting information about resident function and inclusion of these items could lead to overrepresentation of a particular functional area. Subsequently, our measure development contractor focused on the Discharge Mobility Score measure as a starting point for cross-setting development due to the greater number of cross-setting standardized functional assessment data elements for mobility while also identifying redundant functional items that could be removed from a cross-setting functional measure.

Third, the TEP supported including the cross-setting self-care items such that the cross-setting function measure would capture both self-care and mobility. Panelists agreed that self-care items added value to the measure and are clinically important to function. Lastly, the TEP provided refinements to imputation strategies to more accurately represent functional performance across all PAC settings, including the support of using statistical imputation over the current imputation approach implemented in existing functional outcome measures in the PAC QRPs. We considered all recommendations from the TEPs and we applied their recommendations where technically feasible and appropriate. Summaries of the TEP proceedings titled Technical Expert Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures Summary Report (July 2021 TEP) and Technical Expert Panel (TEP) for Cross-Setting Function Measure Development Summary Report (January 2022 TEP) are available on the CMS Measures Management System (MMS) Hub.

Finally, we solicited feedback from interested parties on the importance, relevance, and applicability of a cross-setting functional outcome measure for SNFs through an RFI in the FY 2023 SNF PPS proposed rule (87 FR 22754). Commenters were supportive of a cross-setting functional outcome measure that is inclusive of both self-care and mobility items, but also provided information related to potential risk-adjustment methodologies, as well as other measures that could be used to capture functional outcomes across PAC settings (87 FR 47553).

(4) Measure Applications Partnership (MAP) Review

In accordance with section 1890A of the Act, our pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the Measures Under Consideration (MUC) List, that the Secretary is considering adopting for use in Medicare programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the list.

We included the DC Function measure under the SNF QRP in the publicly available MUC List for December 1, 2022. After the MUC List was published, the CBE convened MAP received three comments from interested parties in the industry on the 2022 MUC List. Two commenters were supportive of the measure and one was not. Among the commenters in support of the measure, one commenter stated that function scores are the most meaningful outcome measure in the SNF setting, as they not only assess resident outcomes but also can be used for clinical improvement processes. Additionally, this commenter noted the measure's good reliability and validity and that the measure is feasible to implement. The second commenter noted that the DC Function measure is modeled on an CBE endorsed measure and has undergone an extensive formal development process. In addition, the second commenter noted that the DC Function measure improves on the existing functional outcome measures and recommended replacing the existing function measures with the DC Function measure.

One commenter did not support the DC Function measure and raised the following concerns: the “gameability” of the expected discharge score, the measure's complexity, and the difficulty of implementing a composite functional score.

Shortly after, several CBE convened MAP workgroups met to provide input on the DC Function measure. First, the MAP Health Equity Advisory Group convened on December 6 to 7, 2022. The MAP Health Equity Advisory Group did not share any health equity concerns related to the implementation of the DC Function measure, and only requested clarification regarding measure specifications from the measure steward. The MAP Rural Health Advisory Group met on December 8 to 9, 2022, during which some of the group's members provided support for the DC Function measure and other group members did not express rural health concerns regarding the DC Function measure.

The MAP PAC/LTC workgroup met on December 12, 2022 and provided input on the proposed DC Function measure. During this meeting, we were able to address several concerns raised by interested parties after the publication of the MUC List. Specifically, we clarified that the expected discharge scores are not calculated using self-reported functional goals, and are simply calculated by risk-adjusting the observed discharge scores (see FY 2024 SNF PPS proposed rule 88 FR 21342). Therefore, we believe that these scores cannot be “gamed” by reporting less-ambitious functional goals. We also pointed out that the measure is highly usable as it is similar in design and complexity to existing function measures and that the data elements used in this measure are already in use on the MDS submitted by SNFs. Lastly, we clarified that the DC Function measure is intended to supplement, rather than replace, existing SNF QRP measures for self-care and mobility and implements improvements on the existing Discharge Self-Care Score and Discharge Mobility Score measures that make the measure more valid and harder to game.

The MAP PAC/LTC workgroup went on to discuss other concerns with the DC Function measure, including (1) whether the measure is cross-setting due to denominator populations that differ among settings, (2) whether the measure would adequately represent the full picture of function, especially for residents who may have a limited potential for functional gain, and (3) that the range of expected scores was too large to offer a valid facility-level score. We clarified that the denominator population in each measure setting represents the assessed population within the setting and that the measure satisfies the requirement of section 1888(e)(6) of the Act for a cross-setting measure in the functional status domain specified under section 1899B(c)(1) of the Act. Additionally, we noted that the TEP had reviewed the item set and determined that all the self-care and mobility items were suitable for all settings. Further, we clarified that, because the DC Function measure would assess whether a resident met or exceeded their expected discharge score, it accounts for residents who are not expected to improve. Lastly, we noted that the DC Function measure has a high degree of correlation with the existing function measures and that the range of expected scores is consistent with the range of observed scores. The PAC/LTC workgroup voted to support the CBE staff recommendation of conditional support for rulemaking, with the condition that we seek CBE endorsement.

In response to the PAC/LTC workgroup's preliminary recommendation, the CBE received two more comments supporting the recommendation and one comment that did not. Among the commenters in support of the DC Function measure, one supported the measure under the condition that it be reviewed and refined such that its implementation supports resident autonomy and results in care that aligns with residents' personal functional goals. The second commenter supported the DC Function measure under the condition that it produces statistically meaningful information that can inform improvements in care processes. This commenter also expressed concern that the DC Function measure is not truly cross-setting because it utilizes different resident populations and risk- adjustment models with setting-specific covariates across settings. Additionally, this commenter noted that using a single set of cross-setting section GG items is not appropriate since the items in our standardized patient/resident assessment data instruments may not be relevant across varying resident-setting populations. The commenter who did not support the DC Function measure raised concern with the usability of a composite functional score for improving functional performance, and expressed support for using individual measures, such as the current Change in Mobility Score and Change in Self-Care Score measures, to attain this goal.

Finally, the MAP Coordinating Committee convened on January 24 to 25, 2023, during which the CBE received one comment not in support of the PAC/LTC workgroup's preliminary recommendation for conditional support of the DC Function measure. The commenter expressed concern that the DC Function measure competes with existing self-care and mobility measures in the SNF QRP. We noted that we monitor measures to determine if they meet any of the measure removal factors, set forth in § 413.360(b)(2), and when identified, we may remove such measure(s) through the rulemaking process. We noted again that the TEP had reviewed the item set and determined that all self-care and mobility items were suitable for all settings. The MAP Coordinating Committee members expressed support for reviewing existing measures for removal as well as support for the DC Function measure, favoring the implementation of a single, standardized function measure across PAC settings. The MAP Coordinating Committee unanimously upheld the PAC/LTC workgroup recommendation of conditional support for rulemaking. We refer readers to the final MAP recommendations, titled 2022–2023 MAP Final Recommendations.

(5) Quality Measure Calculation

The proposed DC Function measure is an outcome measure that estimates the percentage of Medicare Part A SNF residents who meet or exceed an expected discharge score during the reporting period. The proposed DC Function measure's numerator is the number of SNF stays with an observed discharge function score that is equal to or greater than the calculated expected discharge function score. The observed discharge function score is the sum of individual function items values at discharge. The expected discharge function score is computed by risk-adjusting the observed discharge function score for each SNF stay. Risk adjustment controls for resident characteristics such as admission function score, age, and clinical conditions. The denominator is the total number of SNF stays with an MDS record in the measure target period (four rolling quarters) that do not meet the measure exclusion criteria. For additional details regarding the numerator, denominator, risk adjustment, and exclusion criteria, refer to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report.

The proposed measure implements a statistical imputation approach for handling “missing” standardized functional assessment data elements. The coding guidance for standardized functional assessment data elements allows for using “Activity Not Attempted” (ANA) codes, resulting in “missing” information about a resident's functional ability on at least some items, at admission and/or discharge, for a substantive portion of SNF residents. Currently, functional outcome measures in the SNF QRP use a simple imputation method whereby all ANA codes or otherwise missing scores, on both admission and discharge records, are recoded to “1” or “most dependent.” Statistical imputation, on the other hand, replaces these missing values with a variable based on the values of other, non-missing variables in the assessment and on the values of other assessments which are otherwise similar to the assessment with a missing value. Specifically, the proposed DC Function measure's statistical imputation allows missing values (for example, the ANA codes) to be replaced with any value from 1 to 6, based on a resident's clinical characteristics and codes assigned on other standardized functional assessment data elements. The measure implements separate imputation models for each standardized functional assessment data element used in the construction of the discharge score and the admission score. Relative to the current simple imputation method, this statistical imputation approach increases precision and accuracy and reduces the bias in estimates of missing item values. We refer readers to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report for measure specifications and additional details.

We solicited public comment on our proposal to adopt the Discharge Function Score measure beginning with the FY 2025 SNF QRP. We received a number of comments from interested parties who support the adoption of the proposed measure, and others who supported the concept but encouraged CMS to continue to evaluate the methodology for validity. However, many commenters did not support the proposed measure for various reasons, including the lack of CBE endorsement, the concern that the methodology was replacing clinical judgement, and concerns around how the expected scores were calculated. The following is a summary of the comments we received on our proposal to adopt the DC Function measure, beginning with the FY 2025 SNF QRP, and our responses.

Comment: Several commenters supported the adoption of the proposed measure. Some of these commenters specifically noted that the statistical imputation approach is an improvement over the current imputation approach used in the functional outcome measures already in the SNF QRP.

Response: We thank commenters for their support of the adoption of the DC Function measure and agree that the statistical imputation approach improves upon the approach used in the measures currently in the SNF QRP.

Comment: One commenter who supported the addition of the DC Function measure encouraged continual evaluation of the imputation methodology for validity and any unintended negative consequences.

Response: We reevaluate measures implemented in the SNF QRP on an ongoing basis to ensure they have strong scientific acceptability and appropriately capture the care provided by SNFs. This monitoring includes the appropriateness and performance of both the risk models and imputation models used to calculate the measure.

Comment: One commenter agreed with the proposed statistical imputation approach utilized in the DC Function measure but suggested it might lead to confusion. Specifically, this commenter noted that the statistical imputation approach is only proposed for the DC Function measure and is not used for the Discharge Self-Care Score and Discharge Mobility Score measures, despite the measures being similar. The commenter stated the different approaches may lead to different outcome percentages when looking at the Discharge Self-Care Score and Discharge Mobility Score measures and the DC Function measure.

Response: We thank the commenter for their support of the proposed statistical imputation approach utilized in the DC Function measure. We acknowledge the value of implementing this imputation approach in other measures using section GG items in the MDS, as measure testing has shown that this approach improves the validity of the DC Function measure over the current imputation approach used in existing measures in the SNF QRP. Measures undergo testing and refinement during measure development and maintenance activities, and we will consider testing the statistical imputation methodology in existing and future measures.

The DC Function measure captures information that is distinct from the Discharge Self-Care Score and Discharge Mobility Score measures. Specifically, the DC Function measure considers both dimensions of function (utilizing a subset of self-care and mobility GG items), while the Discharge Self-Care Score and Discharge Mobility Score measures each consider one dimension of function (utilizing all self-care and mobility GG items, respectively). For these same reasons, we expect to see differences in outcome percentages among these three measures for reasons unrelated to the imputation approach.

Comment: Four commenters did not support the adoption of this measure specifically because it lacks CBE endorsement or has not undergone the CBE endorsement process. Two of these commenters noted that the CBE endorsement process provides information on whether the measure provides valuable information that can be used to inform improvements in care.

Response: We direct readers to section VII.C.1.b.2. of this final rule, where we discuss this topic in detail. Despite the current absence of CBE endorsement for this measure, we still believe it is important to adopt the DC Function measure into the SNF QRP because, unlike the Discharge Self-Care Score and Discharge Mobility Score measures, the DC Function measure relies on functional status items collected in all PAC settings, satisfies the requirement of a cross-setting quality measure set forth in sections 1888(e)(6)(B)(i)(II) and 1899B(c)(1)(A) of the Act, and assesses both domains of function. We also direct readers to section VII.C.1.b.1. of this final rule, where we discuss measurement gaps that the DC function measure fulfills in relation to competing and related measures. We also acknowledge the importance of the CBE endorsement process and plan to submit the proposed measure for CBE endorsement in the future. We direct readers to section VII.C.1.b.3. of this final rule and the technical report for detailed measures testing results demonstrating that the measure provides meaningful information which can be used to improve quality of care, and to the TEP report summaries which detail TEP support for the proposed measure concept.

Comment: One commenter opposed the adoption of the DC Function measure due to concern with the proposed imputation approach. This commenter noted that the “Activity Not Attempted” codes allow clinicians to use their professional judgement when certain activities should not or could not be safely attempted by the resident, which may be due to medical reasons. Moreover, this commenter stated that among some residents not able to attempt certain self-care and mobility tasks at the time of admission, the use of ANA codes decreases significantly at the time of discharge, which they believe reflects the functional outcomes achieved during their SNF stay. With these considerations in mind, this commenter does not believe it is appropriate or accurate for CMS to override the clinical judgement of the clinicians who are treating the resident by using statistical imputation to impute a value to a data element where an ANA code was entered. Lastly, the commenter recommended that CMS engage with post-acute care clinicians to address their concerns that ANA codes are not truly reflective of residents' functional abilities and/or deficits.

Response: We acknowledge that the “Activity Not Attempted” (ANA) codes allow clinicians to use their professional judgement when certain activities should not or could not be safely attempted by the resident and that there may be medical reasons that a resident cannot safely attempt a task. However, we want to clarify that utilizing statistical imputation does not override the clinical judgement of clinicians who are expected to continue determining whether certain activities can be safely attempted by the residents when completing the MDS and utilizing the assessment data to determine appropriate goals for SNF residents. Rather, statistical imputation is a component in measure calculation of reported data and improves upon the imputation approach currently adopted in the Discharge Self-Care Score, Discharge Mobility Score, Change in Self-Care Score, and Change in Mobility Score measures by improving measure component validity.

In the Discharge Self-Care Score, Discharge Mobility Score, Change in Self-Care Score, and Change in Mobility Score measures, ANA codes are imputed to 1 (dependent) when calculating the measure scores, regardless of a resident's own clinical and functional information. The imputation approach implemented in the proposed DC Function measure uses each resident's available functional and clinical information to estimate each ANA value had the item been completed. Testing demonstrates that, relative to the current simple imputation method, the statistical imputation approach used in the DC Function measure increases precision and accuracy and reduces bias in estimates of missing item values.

Finally, in regard to the commenter's recommendation that we engage with PAC clinicians about the ANA codes, we have engaged with PAC clinicians on more than one occasion. As described in section VII.C.1.b.3. of this final rule, our measure development contractor convened two TEPs to obtain expert clinician input on the development of the measure. The TEPs consisted of interested parties with a diverse range of expertise, including SNF and other subject matter knowledge and clinical expertise, and measure development experience in PAC settings. As described in the PAC QRP Functions TEP Summary Report—March 2022, panelists agreed that the recode approach used in the already adopted functional outcome measures could be improved upon and reiterated that not all ANAs reflect dependence on a function activity. Based on the extensive testing results presented to the TEP, a majority of panelists favored the statistical imputation over alternative methodologies and an imputation method that is more accurate.

Comment: One commenter expressed concern with the proposed statistical imputation approach utilized in the DC Function measure and suggested it might lead to this measure score varying significantly from the Discharge Self-Care Score and Discharge Mobility Score measures' scores.

Response: The DC Function measure captures information that is distinct from the Discharge Self-Care Score and Discharge Mobility Score measures. Specifically, the DC Function measure considers both dimensions of function (utilizing a subset of self-care and mobility GG items in the MDS), while the Discharge Self-Care Score and Discharge Mobility Score measures each consider one dimension of function (utilizing all self-care and mobility GG items, respectively). For these same reasons, we expect to see differences in outcome percentages among these three measures for reasons unrelated to the imputation approach used.

Comment: Three commenters believe the measure's imputation and risk-adjustment approach are complex and difficult to understand. One of these commenters urged CMS to continuously evaluate the imputation method and its impact across the PAC settings and urged CMS to provide additional coding guidance for ANA use for the GG items in order to better standardize and reduce the use of ANA codes. The other two commenters suggested that CMS provide greater transparency on the “expected” discharge function score and/or the imputation method.

Response: The proposed measure uses imputation methods that are similar in complexity to the CBE endorsed functional outcome measures that have been in the SNF QRP for several years, and will be similarly specified. As such, interpreting measure performance should be no more difficult than understanding current functional outcome measures. We appreciate that statistical imputation adds additional steps to the measure's calculation; however, understanding the technical details of imputation and, separately, the construction of the expected scores, is not needed to correctly interpret the measure scores. For those who are interested in the technical details, the methodology and specifications are available in the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report . As with all other measures, we will routinely monitor this measure's performance, including the statistical imputation approach, to ensure the measure remains valid and reliable. Finally, we would like to clarify that the adoption of this measure does not change how SNFs should complete the GG items. As stated in the MDS Resident Assessment Instrument (RAI) Manual, the ANA codes should only be used if the activity did not occur; that is, the resident did not perform the activity and a helper did not perform that activity for the resident. However, we acknowledge that there will be instances where an ANA code is the most appropriate code to select. We regularly review and update the manual as indicated. Additionally, if SNFs have questions related to the completion of these items, they can submit questions to the SNF QRP Help Desk at SNFQualityQuestions@CMS.hhs.gov.

Comment: Four commenters oppose the adoption of the proposed measure due to their doubt regarding the cross-setting applicability of the measure given the different resident populations served by the various PAC settings and pointed out that the capabilities and goals of residents differ widely by setting. One of these commenters stated that the measure is only “cross-setting” in name and that while the measure attempts to take into account the myriad of differences in the resident populations across settings, the DC Function measure is nevertheless four different measures across four different settings because the differences in resident populations alter the underlying calculation of the cross-setting measure. Three other commenters referenced the Therapy Outcomes in Post-Acute Care Settings study, which found significant differences in function across settings, which dictate differences in treatment.

Response: We acknowledge that different resident populations are served across the PAC settings and the capabilities and goals of these populations differ. However, we would like to clarify that cross-setting measures do not necessarily suggest that facilities can and should be compared across settings. Instead, these measures are intended to compare providers within a specific setting while standardizing measure specifications across settings. The proposed measure does just this, by aligning measure specifications across settings and using a common set of standardized functional assessment data elements.

Comment: Three commenters opposed the proposed DC Function measure because it combines self-care and mobility items from the MDS. Two commenters expressed a preference towards the Discharge Self-Care Score and Discharge Mobility Score measures currently adopted in the SNF QRP because they reflect the two dimensions of function separately, and believe these measures more accurately capture each functional domain over the proposed DC Function measure. One commenter noted that separate measures would allow for better understanding of the optimal interventions and outcomes for residents in each unique PAC setting. One of these commenters additionally asked CMS to introduce two separate DC Function measures for both mobility and self-care.

Response: The DC Function measure is intended to summarize several cross-setting functional assessment items while meeting the requirements of section 1899B(c)(1) of the Act. We agree with the commenters that the individual Discharge Self-Care Score and Discharge Mobility Score measures will continue to be useful to assess care quality in these dimensions. For this reason, the Discharge Self-Care Score and Discharge Mobility Score measures, which include additional self-care and mobility items, are not proposed for removal. SNFs will be able to use information from both the DC Function measure and these “individual function measures” (Discharge Self-Care Score and Discharge Mobility Score measures) when determining which functional areas may be opportunities for improvement, and for this reason, these two measures are not proposed for removal. We routinely reevaluate measures and will consider re-specifying the Discharge Self-Care Score and Discharge Mobility Score measures such that they more closely align with this proposed DC Function measure (for example, using statistical imputation).

Comment: Two commenters disagreed with characterizing items coded with an ANA code (codes 07, 09, 10, and 88) as “missing” data because these ANA codes represent clinical information. Thus, imputing scores for ANA codes would be clinically inappropriate. One of these commenters stated that imputation of these ANA codes based on other function activities would not improve the precision of the score.

Response: We would like to clarify that the use of the term “missing” data refers to codes that are not coded 01, 02, 03, 04, 05, or 06, which represent the amount of (or lack of) helper assistance a resident needed to complete a functional activity. ANA codes are considered “missing” in the context of the measure calculations since the observed discharge score is the sum of 01–06 values from functional assessment items included in the observed discharge score. Regarding the comment stating that imputation of these ANA codes based on other functional activities would not improve the precision of the score, we interpret the commenters to be saying that statistical imputation would not improve the precision of the score of missing item values. However, we disagree that using statistical imputation would not improve the precision of this value. Measure testing showed that the statistical imputation models demonstrate good discrimination and produce more precise and accurate estimates of function scores for items with missing scores when compared to the current imputation approach implemented in SNF QRP functional outcome measures, which recodes all ANAs as most dependent.

Comment: One commenter expressed concern that the proposed measure numerator is not wholly attributed to a SNF's quality of care and that the calculation of the “expected” discharge score is opaque, resulting in difficulty for SNFs to determine the score for which they are striving. This commenter further noted that functional goals are not based on statistical regression and are identified via individual-specific goals related to function, independence, and overall health.

Response: We agree with the commenter that functional goals are identified for each resident as a result of an individual assessment and clinical decisions, rather than statistics. We want to remind commenters that the DC Function measure is not calculated using the goals identified through the clinical process. The “expected” discharge score is calculated by risk-adjusting the observed discharge score (that is, the sum of individual function item values at discharge) for admission functional status, age, and clinical characteristics using an ordinary least squares linear regression model. The model intercept and risk-adjustor coefficients are determined by running the risk-adjustment model on all eligible SNF stays. For more detailed measure specifications, we direct readers to the document titled Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report . The risk-adjustment model for this measure controls for clinical, demographic, and function characteristics to ensure that the score fully reflects a facility's quality of care.

Comment: Three commenters encouraged CMS to provide SNFs a resource to calculate the expected discharge function score in real time, such that SNFs can implement these scores in care planning and monitoring efforts of residents prior to receiving confidential feedback reports. One of these commenters noted that such resources are necessary as calculations of the expected scores are complex and beyond easy comprehension for SNFs. Another commenter encouraged CMS to work with interested parties to develop the tools and educational resources necessary for SNFs to be able to obtain the individual resident's risk-adjusted predicted discharge function score when the assessments are completed. One commenter specifically requested that this information be included in the SNF's Review and Correct reports found in the internet Quality Improvement and Evaluation System (iQIES). Additionally, guidance should be developed and disseminated on how to use that information as a resource to inform and monitor the plan of care, so that necessary reassessments and modifications can be made in a timely manner in the event progress toward the predicted discharge function outcomes appear not to be satisfactory.

Response: We do not expect SNFs to replicate the methodology used to calculate this measure; however, the resources necessary to carry out such calculations will be available in the technical specifications posted on the SNF QRP Measures and Technical Specification website. Additionally, while the measure relies on statistical imputation to impute missing values, the steps used to calculate expected scores based on a given set of assessment items and their values are exactly the same as the Discharge Self-Care Score, Change in Self-Care Score, Discharge Mobility Score, and Change in Mobility Score already adopted in the SNF QRP. Given this, the concept of the expected score is no more complex than the functional outcome measures that have been in use for several years.

With respect to the comment regarding access to expected scores, we want to clarify that expected scores are not intended to be used for care planning; rather, care planning should be based on clinical judgement, assessment of residents' clinical status (including functional abilities and/or deficits), and residents' functional goals. Additionally, we have concerns that providing expected scores in such a real-time manner prior to the end of the data submission period may incentivize some SNFs to modify their scores and/or otherwise influence their coding practices. Given that SNFs have been able to use the current functional outcome measures to improve their care processes without the expected function scores, we maintain that SNFs will be able to similarly do so for the DC Function measure. However, we do appreciate that understanding how individuals' observed scores compared to expected scores can potentially allow SNFs to identify areas for improvement and will consider adding resident-level expected scores to the confidential feedback reports as technically feasible.

Comment: Three commenters expressed concern regarding the validity of reported functional assessment data. Two commenters oppose the adoption of the DC Function measure, stating that provider-reported functional assessment information is not accurate and incomplete, so when measures are calculated, scores are incorrect. With this in mind, two of these commenters recommended CMS improve SNFs' reporting of functional assessment data before adopting this measure. One of these commenters noted that some SNFs code resident function in response to payment incentives and noted that differential coding practices and profitability by case type across SNFs may contribute to differential profitability. Additionally, this commenter stated that the current imputation approach (which recodes all ANAs to 1) would lead to a lower motor score and raise Medicare payment for the stay and supported the proposal to improve the quality of the MDS data by using statistical imputation.

Response: We are aware of the concerns and challenges related to provider-reported data and acknowledge that the coding of GG items may be affected by payment and quality reporting considerations. We actively monitor SNF (and other PAC) coding practices to identify potential threats to the validity, and these analyses ultimately resulted in our development of the proposed DC Function measure. By using all available relevant information to impute ANAs, rather than simply imputing the most dependent value of 1, the statistical imputation approach mitigates payment-related incentives to code ANAs, while improving validity, as demonstrated through the measure's testing results. We acknowledge the importance of utilizing valid assessment data, and we remind commenters that we will be implementing a validation process for MDS-based measures starting in the same FY as the performance period of the measure. We believe that adopting this validation process in parallel with the adoption of the measure will increase the accuracy of the data reported.

With respect to the comment about coding resident function in response to payment incentives, we have processes in place to ensure reported patient data are accurate. The MDS process has multiple regulatory requirements. Our regulations at §§ 483.20(b)(1)(xviii),(g), and (h) require that (1) the assessment must be a comprehensive, accurate assessment of the resident's status, (2) the assessment must accurately reflect the resident's status, (3) a registered nurse and each individual who completes a portion of the assessment must sign and certify the assessment is completed, and (4) the assessment process must include direct observation, as well as communication with the resident.

Comment: Four commenters oppose the adoption of the DC Function measure due to the belief that this measure encourages SNFs to favor residents with the potential for improvement at discharge over those in need of maintenance care. For this reason, three of these commenters believe there needs to be an additional measure reflecting maintenance care and services; otherwise, incorporation of the DC Function measure in the QRP would incentivize SNFs to forgo provision of maintenance services to Medicare beneficiaries.

Response: The DC Function measure does not solely reflect improvement of residents at discharge. The measure estimates the percentage of residents who meet, as well as exceed, an expected discharge function score. In other words, if a resident, based on their own demographic and clinical characteristics, is expected to maintain, as opposed to improve in, function, then they will still meet the numerator criteria for this measure. For many residents, the overall goals of SNF care may include optimizing functional improvement, returning to a previous level of independence, maintaining functional abilities, or avoiding institutionalization. For additional details regarding risk adjustment, please refer to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report .

Comment: One commenter requested CMS provide more clarity on its imputation approach to recoding, specifically contrasting it with a Rasch analysis used in the unified PAC PPS prototype, to ensure transparency and clinical meaningfulness.

Response: The Rasch analysis in the unified PAC PPS prototype produces a single value to which every single ANA is recoded for a given item across all residents and settings. By contrast, under the imputation approach for the DC Function measure, we estimate a different imputed value for each resident, based on their clinical comorbidities, their score on all other GG items, and setting. We believe our approach accounts for several likely effects: setting-specific coding guidance and practice differences; function scores being correlated with clinical comorbidities; and functional scores for a given GG item being correlated with functional codes on other GG items, particularly on “adjacent” (similar) items. Therefore, we believe recoding ANAs based on each resident's specific clinical risk and using all available GG item scores/codes is a more valid approach. For more detailed measure specifications, we direct readers to the document titled Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report .

Comment: Two commenters oppose the adoption of the DC Function measure due to potential negative effects arising from Medicare Advantage (MA) plans focusing on money-saving practices. One commenter stated that if discharge measures only examine a discharge functional score in SNFs rather than a change in functional score in SNF and other PAC settings, MA plans can circumvent measurements of quality by sending difficult rehabilitation candidates to home rehabilitation, even if SNF or IRF rehabilitation would be better for the resident.

Response: We do not understand the connections raised by the commenter between the adoption of the DC Function measure and unintended consequences MA beneficiaries could face. However, if the concern stems from a belief that the DC Function measure would only be adopted in the SNF setting, we would like to clarify that aligned versions of the DC Function measure are also proposed for the IRF, LTCH, and HH QRPs.

Additionally, the Change in Mobility Score and Change in Self-Care Score measures rely on functional status items not yet collected in all settings and utilize a set of items that are not equally applicable across all settings. On the other hand, the DC Function score measure is a cross-setting measure that utilizes a standardized set of self-care and mobility assessment items that are common to all the PAC settings and are aligned in terms of the exclusions and risk models applied (as appropriate and feasible).

Comment: One commenter expressed concern that the measure performance may not adequately demonstrate functional ability improvements across the mobility and selfcare domains during the SNF stay. This commenter noted that the measure only includes a subset of function items from the assessment instrument and is concerned that these items are not necessarily the best indicators of resident functional success when discharged; for example, functional abilities and goals that better reflect self-care included upper body dressing and lower body dressing. This commenter also stated that the functional items captured in this measure seem to be based solely on ensuring cross-setting applicability and less on the accuracy of an expected function score.

Response: We acknowledge that the cross-setting applicability was a motivating factor in determining function items captured in the proposed DC Function measure, and upper body dressing and lower body dressing function items were not available across settings. Nonetheless, the proposed DC Function measure does reflect the progress of a resident across both the mobility and selfcare domains. As stated in section VII.C.1.b.3. of this final rule, the TEP supported the inclusion of both functional domains as self-care items impact mobility items and are clinically relevant to function. Additionally, the proposed measure is meant to supplement, rather than replace, the Discharge Self-Care Score and Discharge Mobility Score measures which implement the remaining self-care and mobility function items not captured in the DC Function measure. High correlations between the proposed measure and the Discharge Self-Care Score and Discharge Mobility Score measures (0.85 and 0.88, respectively) demonstrate that these three measures capture related, but distinct, aspects of provider care in relation to residents' function. The TEP understood these considerations and supported the inclusion of the function items included in the proposed measure.

Comment: One commenter believed that the adoption of the proposed measure would result in additional burden, stating that its adoption will require software updates to implement and monitor the measure's complex calculations prior to CMS publishing results, as well as additional training and education for clinical and administrative personnel. Another commenter noted that to achieve high measure scores, SNFs would require continuing education, time to perform and report assessments, and increased collaboration among clinicians.

Response: We disagree that the adoption of the proposed measure would result in additional burden or require additional training. We are not proposing changes to the number of items required or the reporting frequency of the items reported in the MDS in order to report for this measure. In fact, this measure requires the same set of items that are already reported by SNFs in the MDS. Additionally, we calculate this measure, and provide SNFs with various resources to review and monitor their own performance on this measure, including provider preview reports. Therefore, SNFs are not required to update software to successfully report or monitor performance. Regarding the commenter's concerns about education, we do plan to provide educational resources to SNFs about the DC Function measure.

Comment: Two commenters raised concerns that the measure does not account for cognition and communication. One commenter urged CMS to consider alternative assessments that better incorporate cognition and communication into the measure calculation. The other commenter similarly raised concerns that section GG items insufficiently capture all elements of function and do not adequately capture the outcomes required for safety and independence.

Response: We agree that cognition and communication are critically important and related to the safety and independence of residents. Although not directly assessed for the purpose of measure calculation, this measure does indirectly capture a facility's ability to impact a resident's cognition and communication to the extent that these factors are correlated to improvements in self-care and mobility. That said, we agree that communication and cognition are important to assess directly, and facilities currently do so through completion of the Brief Interview for Mental Status (BIMS), Confusion Assessment Method (CAM^©), and Speech/Communication items in section B of the MDS. Additionally, we regularly assess the measures in the SNF QRP for measurement gaps, and as described in section VII.D. of this final rule, specifically identified cognitive improvement as a possible measurement gap and sought feedback about how to best assess this clinical dimension. We will use feedback from this RFI, as well as discussion with technical experts and empirical analyses to determine how to measure communication and cognition.

Comment: One commenter urged CMS to monitor the impact of COVID–19 and social determinants of health on functional outcomes and address these impacts in measure refinements.

Response: We recognize that COVID–19 and social determinants of health may have an impact on functional outcomes. Testing indicates that adding social determinants of health, such as dual eligibility and race/ethnicity, does not substantively affect provider scores for this measure. However, we will continue to monitor the impact of the above factors, as is feasible, on the measures and incorporate them in measure calculations, as needed, to ensure the measure remains valid and reliable.

After careful consideration of the public comments we received, we are finalizing our proposal to adopt the DC Function measure as an assessment-based outcome measure beginning with the FY 2025 SNF QRP as proposed.

c. Removal of the Application of Percent of Long-Term Care Hospital Patients With an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function Beginning With the FY 2025 SNF QRP

We proposed to remove the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) measure from the SNF QRP beginning with the FY 2025 SNF QRP. Section 413.360(b)(2) of our regulations describes eight factors we consider for measure removal from the SNF QRP, and we believe this measure should be removed because it satisfies two of these factors.

First, the Application of Functional Assessment/Care Plan measure meets the conditions for measure removal factor one: measure performance among SNFs is so high and unvarying that meaningful distinctions in improvements in performance can no longer be made. Second, this measure meets the conditions for measure removal factor six: there is an available measure that is more strongly associated with desired resident functional outcomes. We believe the proposed DC Function measure discussed in the FY 2024 SNF PPS proposed rule (88 FR 21337 through 21342) better measures functional outcomes than the current Application of Functional Assessment/Care Plan measure. We discuss each of these reasons in more detail.

In regard to measure removal factor one, the Application of Functional Assessment/Care Plan measure has become topped out, with average performance rates reaching nearly 100 percent over the past 3 years (ranging from 99.1 percent to 98.9 percent during CYs 2019 through 2021). For the 12-month period of Q3 2020 through Q2 2021 (July 1, 2020 through June 30, 2021), SNFs had an average score for this measure of 98.8 percent, with nearly 70 percent of SNFs scoring 100 percent and for CY 2021, SNFs had an average score of 98.9 percent, with nearly 63 percent of SNFs scoring 100 percent. The proximity of these mean rates to the maximum score of 100 percent suggests a ceiling effect and a lack of variation that restricts distinction among SNFs.

In regard to measure removal factor six, the proposed DC Function measure is more strongly associated with desired resident functional outcomes than this current process measure, the Application of Functional Assessment/Care Plan measure. As described in the FY 2024 SNF PPS proposed rule (88 FR 21339 through 213340), the DC Function measure has the predictive ability to distinguish residents with low expected functional capabilities from those with high expected functional capabilities. We have been collecting standardized functional assessment elements across PAC settings since 2016, which has allowed for the development of the proposed DC Function measure and meets the requirements of the Act to submit standardized patient assessment data and other necessary data with respect to the domain of functional status, cognitive function, and changes in function and cognitive function. In light of this development, this process measure, the Application of Functional Assessment/Care Plan measure, which measures only whether a functional assessment is completed and a functional goal is included in the care plan, is no longer necessary, and can be replaced with a measure that evaluates the SNF's outcome of care on a resident's function.

Because the Application of Functional Assessment/Care Plan measure meets measure removal factors one and six, we proposed to remove it from the SNF QRP beginning with the FY 2025 SNF QRP. We also proposed in the FY 2024 SNF PPS proposed rule (88 FR 21361) that public reporting of the Application of Functional Assessment/Care Plan measure would end by the October 2024 Care Compare refresh or as soon as technically feasible when public reporting of the proposed DC Function measure would begin.

Under our proposal, SNFs would no longer be required to report a Self-Care Discharge Goal (that is, GG0130, Column 2) or a Mobility Discharge Goal (that is, GG0170, Column 2) beginning with residents admitted on or after October 1, 2023. We would remove the items for Self-Care Discharge Goal (that is, GG0130, Column 2) and Mobility Discharge Goal (that is, GG0170, Column 2) with the next release of the MDS. Additionally, these items would not be required to meet SNF QRP requirements beginning with the FY 2025 SNF QRP.

We solicited public comment on our proposal to remove the Application of Functional Assessment/Care Plan measure from the SNF QRP beginning with the FY 2025 SNF QRP. The following is a summary of the comments we received on our proposal to remove the Application of Functional Assessment/Care Plan measure from the SNF QRP beginning with the FY 2025 SNF QRP and our responses.

Comment: Several commenters expressed support for the removal of the Application of Functional Assessment/Care Plan measure. Some of the commenters agreed with the removal of the measure because of the measure's topped out performance and due to the costs associated with tracking duplicate measures. A few of these commenters believe the DC Function measure better reflects the care delivered during a SNF stay.

Response: We thank the commenters for their support and agree that the Application of Functional Assessment/Care Plan measure should be removed due to topped-out performance. Additionally, we agree with the commenters that the DC Function measure better reflects care delivered in SNFs.

After consideration of the public comments we received, we are finalizing our proposal to remove the Application of Functional Assessment/Care Plan measure from the SNF QRP beginning with the FY 2025 SNF QRP as proposed.

d. Removal of the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients and Removal of the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients Beginning With the FY 2025 SNF QRP

We proposed to remove the Application of the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) and the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measures from the SNF QRP beginning with the FY 2025 SNF QRP. Section 413.360(b)(2) of our regulations describe eight factors we consider for measure removal from the SNF QRP, and we proposed removal of this measure because it satisfies measure removal factor eight: the costs associated with a measure outweigh the benefits of its use in the program.

Measure costs are multifaceted and include costs associated with implementing and maintaining the measure. On this basis, we proposed to remove these measures for two reasons. First, the costs to SNFs associated with tracking similar or duplicative measures in the SNF QRP outweigh any benefit that might be associated with the measures. Second, our costs associated with program oversight of the measures, including measure maintenance and public display, outweigh the benefit of information obtained from the measures. We discuss each of these in more detail below.

We adopted the Change in Self-Care Score and Change in Mobility Score measures in the FY 2018 SNF PPS final rule (82 FR 36578 through 36593), under section 1888(e)(6)(B)(i)(II) of the Act because the measures meet the functional status, cognitive function, and changes in function and cognitive function domain under section 1899B(c)(1) of the Act. Two additional measures addressing the functional status, cognitive function, and changes in function and cognitive function domain were adopted in the same program year: the Application of IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients (Discharge Self-Care Score) and the Application of IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients (Discharge Mobility Score) measures. At the time these four outcome measures were adopted, the amount of rehabilitation services received among SNF residents varied. We believed that measuring residents' functional changes across all SNFs on an ongoing basis would permit identification of SNF characteristics associated with better or worse resident risk adjustment outcomes as well as help SNFs target their own quality improvement efforts.

We proposed to remove the Change in Self-Care Score and Change in Mobility Score measures because we believe the SNF costs associated with tracking duplicative measures outweigh any benefit that might be associated with the measures. Since the adoption of these measures in 2018, we have been monitoring the data and found that the scores for the two self-care functional outcome measures, Change in Self-Care Score and Discharge Self-Care Score, are very highly correlated in SNF settings (0.93). Similarly, in the monitoring data, we have found that the scores for the two mobility score measures, Change in Mobility Score and Discharge Mobility Score, are very highly correlated in SNF settings (0.95). The high correlation between these measures suggests that the Change in Self-Care Score and Discharge Self-Care Score and the Change in Mobility Score and the Discharge Mobility Score measures provide almost identical information about this dimension of quality to SNFs and are therefore duplicative.

Our proposal to remove the Change in Self-Care Score and the Change in Mobility Score measures is supported by feedback received from the TEP convened for the Refinement of LTCH, IRF, SNF/NF, and HH Function Measures. As described in the FY 2024 SNF PPS proposed rule (88 FR 21340 through 21341), the TEP panelists were presented with analyses that demonstrated the “Change in Score” and “Discharge Score” measure sets are highly correlated and do not appear to measure unique concepts, and they subsequently articulated that it would be sensible to retire either the “Change in Score” or “Discharge Score” measure sets for both self-care and mobility. Based on responses to the post-TEP survey, the majority of panelists (nine out of 12 respondents) suggested that only one measure set each for self-care and mobility, respectively, is necessary. Of those nine respondents, six preferred retaining the “Discharge Score” measure set over the “Change in Score” measure set.

Additionally, we proposed to remove the Change in Self-Care Score and Change in Mobility Score measures because the program oversight costs outweigh the benefit of information that CMS, SNFs, and the public obtain from the measures. We must engage in various activities when administering the QRPs, such as monitoring measure results, producing provider preview reports, and ensuring the accuracy of the publicly reported data. Because these measures essentially provide the same information to SNFs as well as to consumers as the Discharge Self-Care Score and Discharge Mobility Score measures, our costs associated with measure maintenance and public display outweigh the benefit of information obtained from the measures.

Because these measures meet the criteria for measure removal factor eight, we proposed to remove the Change in Self-Care Score and Change in Mobility Score measures from the SNF QRP beginning with the FY 2025 SNF QRP. We also proposed that public reporting of the Change in Self-Care Score and the Change in Mobility Score measures would end by the October 2024 Care Compare refresh or as soon as technically feasible.

We solicited public comment on our proposal to remove the Change in Self-Care Score and the Change in Mobility Score measures from the SNF QRP beginning with the FY 2025 SNF QRP. The following is a summary of the comments we received on our proposal to remove the Change in Self-Care Score and the Change in Mobility Score measures from the SNF QRP beginning with the FY 2025 SNF QRP and our responses.

Comment: Several commenters expressed their support for the removal of the Change in Self-Care Score and the Change in Mobility Score measures, noting that these measures are duplicative of other measures and that their removal will reduce costs to SNFs and to CMS.

Response: We thank the commenters for their support on the removal of the Change in Self-Care Score and the Change in Mobility Score measures. We agree that the measures are duplicative and that their removal will reduce costs to SNFs and CMS.

Comment: Several commenters did not agree with the removal of the Change in Self-Care Score and Change in Mobility Score measures because they believe these measures provide more information than the Discharge Self-Care Score and the Discharge Mobility Score measures. Specifically, two of these commenters contended that capturing the amount of change in a resident's experience is more valuable than capturing whether residents meet or exceed an expected discharge score during their stay. One commenter advised CMS to keep the Change in Self-Care Score and Change in Mobility Score measures in the SNF QRP because the new DC Function measure lacks the positive characteristics the Change in Self-Care Score and Change in Mobility Score measures capture. Meanwhile, another commenter encouraged CMS to consider how it can incorporate the positive aspects of these measures into the new DC Function measure.

Response: We appreciate the perspective of the commenters and understand that there are advantages and disadvantages to retiring the Change in Self-Care Score and Change in Mobility Score measures rather than the Discharge Self-Care Score and Discharge Mobility Score measures. We weighed the tradeoffs of these measures in consultation with a TEP, comprised of 15 panelists with diverse perspectives and areas of expertise, including SNF representation. The majority of the TEP favored the retirement of the Change in Self-Care Score and Change in Mobility Score measures because they believed the Discharge Self-Care Score and Discharge Mobility Score measures better capture a resident's relevant functional ability. We agree that it is important for facilities to track the amount of change that occurs over the course of a stay for its residents and would like to point out that the removal of the Change in Self-Care Score and Change in Mobility Score measures does not preclude SNFs' abilities in this regard. However, we also believe that the Change in Self-Care Score and Change in Mobility Score measures are not intuitive to interpret for the primary audience of Care Compare, as the units of change and what constitutes a meaningful change are unfamiliar to the vast majority of users, particularly prospective or current residents and their caregivers. This is in contrast to the Discharge Self-Care Score and Discharge Mobility Score measures, which are presented as simple proportions. Additionally, the correlations between the Change in Self-Care Score and Discharge Self-Care Score measures and Change in Mobility Score and Discharge Mobility Score measures are very high (Spearman correlation: 0.93 and 0.95), indicating the measures capture almost identical concepts and lead to very similar rankings. As such, the testing does not support the claim that the Change in Self-Care Score and Change in Mobility Score measures provide significantly more information on which to compare facilities, as the relative rankings of facilities are very similar between the Change in Self-Care Score and Discharge Self-Care Score measures and the Change in Mobility Score and Discharge Mobility Score measures. Consequently, given the TEP's recommendation, the more intuitive interpretation, and the very high correlations, we believe there is more value in retiring the Change in Self-Care Score and Change in Mobility Score measures and retaining the Discharge Self-Care Score and Discharge Mobility Score measures.

Comment: One commenter raised concerns that the methodology used to calculate the Discharge Self-Care Score and Discharge Mobility Score measures does not account for functional abilities at admission in the way that the Change in Self-Care Score and Change in Mobility Score measures being proposed for removal do. The commenter requested that CMS clarify the extent to which the remaining Discharge Self-Care Score and Discharge Mobility Score measures would account for change in a residents' function over time, as well as resident heterogeneity. These commenters also raised concerns about unintended consequences that could be introduced through the removal of the Change in Self-Care Score and Change in Mobility Score measures, such as the cherry-picking of residents or creating limited access to services for those with lower functional status. One of these commenters urged CMS to carefully evaluate whether the removal of the Change in Self-Care Score and Change in Mobility Score measures could lead to such unintended consequences.

Response: We appreciate that measures of functional outcomes must account for resident case-mix to ensure fair and meaningful comparisons across facilities. Accordingly, the Discharge Self-Care Score and Discharge Mobility Score measures that would remain in the SNF QRP do in fact account for functional abilities at admission, as well as other relevant demographic and clinical characteristics ( see, for example, Skilled Nursing Facility Quality Reporting Program Measure Calculations and Reporting User's Manual Version 4.0. ). Specifically, the expected discharge scores, which residents must meet or exceed to meet the Discharge Self-Care Score and Discharge Mobility Score measures' numerators, are predicted using the residents' observed admission function scores plus the same clinical comorbidities and demographic characteristics as the corresponding Change in Self-Care Score and Change in Mobility Score measures. Given that the Discharge Self-Care Score and Discharge Mobility Score measures do account for functional abilities at admission, among other relevant clinical characteristics that can impact functional improvement, we do not anticipate that the removal of the Change in Self-Care Score and Change in Mobility Score measures will increase any incentive to cherry -pick residents or block access to care. We take the appropriate access to care in SNFs very seriously, and routinely monitor the performance of measures in the SNF QRP, including performance gaps across SNFs. We will continue to monitor closely whether any proposed changes to the SNF QRP have unintended consequences on access to care for high-risk residents. Should we find any unintended consequences, we will take appropriate steps to address these issues in future rulemaking.

Comment: A few commenters recommended the removal of the Discharge Self-Care Score and Discharge Mobility Score measures instead, which they believe are duplicative of the proposed DC Function Measure.

Response: We disagree that the currently adopted Discharge Self-Care Score and Discharge Mobility Score measures are duplicative of the proposed DC Function measure. As discussed in section VII.C.1.b.1.a. of the final rule, the Discharge Self-Care Score and Discharge Mobility Score measures are not cross-setting because they rely on functional status items not collected in all PAC settings and thus do not satisfy requirement of a cross-setting quality measure as set forth in sections 1888(e)(6)(B)(i)(II) and 1899B(c)(1)(A) of the Act. In contrast, the DC Function measure does include functional status items collected in each of the four PAC settings. Moreover, the DC Function measure captures information that is distinct from the Discharge Self-Care and Discharge Mobility Score measures. Specifically, the DC Function measure considers both dimensions of function within a single measure (utilizing a subset of self-care and mobility GG items in the MDS), while the Discharge Self-Care Score and Discharge Mobility score measures each consider one dimension of function (utilizing all self-care and mobility GG items, respectively).

After consideration of the public comments we received, we are finalizing our proposal to remove the Change in Self-Care Score and Change in Mobility Score measures from the SNF QRP beginning with the FY 2025 SNF QRP as proposed.

2. SNF QRP Quality Measures Beginning With the FY 2026 SNF QRP

a. CoreQ: Short Stay Discharge Measure (CBE #2614) Beginning With the FY 2026 SNF QRP

(1) Background

We define person-centered care as integrated healthcare services delivered in a setting and manner that is responsive to the individual and their goals, values and preferences, in a system that empowers residents and providers to make effective care plans together. Person-centered care is achieved when healthcare providers work collaboratively with individuals to do what is best for the health and well-being of individuals receiving healthcare services, and allows individuals to make informed decisions about their treatment that align with their preferences and values, such as including more choice in medication times, dining options, and sleeping times. Self-reported measures, including questionnaires assessing the individual's experience and satisfaction in receiving healthcare services, are widely used across various types of providers to assess the effectiveness of their person-centered care practices.

There is currently no national standardized satisfaction questionnaire that measures a resident's satisfaction with the quality of care received by SNFs. We identified resident satisfaction with the quality of care received by SNFs as a measurement gap in the SNF QRP (see section VII.D. of this final rule), as did the MAP in its report MAP 2018 Considerations for Implementing Measure in Federal Programs: Post-Acute Care and Long-Term Care. Currently the SNF QRP includes measures of processes and outcomes that illustrate whether interventions are working to improve delivery of healthcare services. However, we believe that measuring resident satisfaction would provide clinical teams compelling information to use when examining the results of their clinical care, and can help SNFs identify deficiencies that other quality metrics may struggle to identify, such as communication between a resident and the provider.

Measuring individuals' satisfaction with healthcare services using questionnaires has been shown to be a valid indicator for measuring person-centered care practices. The value of measuring consumer satisfaction is supported in the peer-reviewed literature using respondents from SNFs. One study demonstrated higher (that is, better) resident satisfaction is associated with the SNF receiving fewer deficiency citations from regulatory inspections of the SNF, and is also associated with higher perceived service quality. Other studies of the relationship between resident satisfaction and clinical outcomes suggest that higher overall satisfaction may contribute to lower 30-day readmission rates and better adherence to treatment recommendations.

We currently collect resident satisfaction data in other settings, such as home health, hospice, and hospital, using Consumer Assessment of Healthcare Providers and Systems (CAHPS®) patient experience surveys. These CAHPS® surveys ask individuals (or in some cases their families) about their experiences with, and ratings of, their healthcare providers, and then we publicly report the results of some of these resident experience surveys on Care Compare. The CAHPS® Nursing Home survey: Discharged Resident Instrument (NHCAHPS–D) was developed specifically for short-stay SNF residents by the Agency for Healthcare Research and Quality (AHRQ) and the CAHPS® consortium in collaboration with CMS. However, due to its length and the potential burden on SNFs and residents to complete it, we have not adopted it for the SNF QRP.

The CoreQ is another suite of questionnaires developed by a team of nursing home providers and researchers to assess satisfaction among residents and their families. The CoreQ suite of five measures is used to capture resident and family data for SNFs and assisted living (AL) facilities. The CoreQ was developed in 2012 by SNFs and ALs that partnered with researchers to develop a valid resident satisfaction survey for SNFs and ALs since, at the time, there was no standard questionnaire or set of identical questions that could be used to compare meaningful differences in quality between SNFs. As part of the development of the CoreQ measures, extensive psychometric testing was conducted to further refine the CoreQ measures into a parsimonious set of questions that capture the domain of resident and family satisfaction. Since 2017, the CoreQ has been used in the American Health Care Association (AHCA) professional recognition program, and several States (including New Jersey, Tennessee, and Georgia) have incorporated the CoreQ into their Medicaid quality incentive programs. In addition, 42 SNF and AL customer satisfaction vendors currently administer the CoreQ measures' surveys or have added the CoreQ questions to their questionnaires.

The CoreQ measures were designed to be different from other resident satisfaction surveys. The primary difference between the CoreQ questionnaires for residents discharged from a SNF after receiving short-stay services and the NHCAHPS–D survey is its length: the CoreQ questionnaire consists of four questions while the NHCAHPS–D has 50 questions. Another difference is that the CoreQ measures provide one score that reflects a resident's overall satisfaction, while other satisfaction surveys do not. The CoreQ questionnaires use a 5-point Likert scale, and the number of respondents with an average score greater than or equal to 3.0 across the four questions is divided by the total number of valid responses to yield the SNF's satisfaction score.

The CoreQ measures are also instruments that are familiar to the SNF community, and the CoreQ: Short Stay Discharge (CoreQ: SS DC) survey has already been voluntarily adopted by a large number of SNFs with ease. The number of SNFs voluntarily using the CoreQ: SS DC survey increased from 372 in the first quarter of 2016 to over 1,500 in the third quarter of 2019. Additionally, the measure steward, AHCA, reported that there have been no reported difficulties with the current implementation of the measure, and in fact, providers, vendors, and residents have reported they like the fact that the questionnaire is short and residents report appreciation that their satisfaction (or lack thereof) is being measured.

(a) Measure Importance

Measuring residents' satisfaction is an effective method to assess whether the goals of person-centered care are achieved. Measuring residents' satisfaction can help SNFs identify deficiencies that the other quality metrics adopted in the SNF QRP cannot identify, such as communication between a resident and the SNF's healthcare providers. We believe collecting and assessing satisfaction data from SNF residents is important for understanding residents' experiences and preferences, while the collection process ensures each resident can easily and discreetly share their information in a manner that may help other potential consumers choose a SNF. Collection of resident satisfaction data also aligns with the person-centered care domain of CMS's Meaningful Measures 2.0 Framework, and would provide SNFs with resident-reported outcome information to incorporate into their quality assessment and performance improvement (QAPI) strategies to improve their quality of care.

The CoreQ: SS DC measure is a resident-reported outcome measure using the CoreQ: SS DC measure questionnaire which calculates the percentage of residents discharged in a 6-month period from a SNF, within 100 days of admission, who are satisfied with their SNF stay. The CoreQ: SS DC measure received initial CBE endorsement in 2016 and re-endorsement in 2020, and is a widely accepted instrument for measuring resident satisfaction. The measure includes a parsimonious set of four questions, and represents an important aspect of quality improvement and person-centered care. We believe it could be used to fill the identified gap in the SNF QRP's measure set, that is, measuring residents' experience of care. Therefore, we proposed to adopt the CoreQ: SS DC measure for the SNF QRP beginning with the FY 2026 SNF QRP. More information about the CoreQ questionnaire is available at http://www.coreq.org.

(b) Measure Testing

The measure steward, AHCA, conducted extensive testing on the CoreQ: SS DC measure to assess reliability and validity prior to its initial CBE endorsement in 2016 and conducted additional analyses for the CoreQ: SS DC measure's CBE re-endorsement in 2020. These analyses found the CoreQ: SS DC measure to be highly reliable, valid, and reportable. We describe the results of these analyses in this section.

Reliability testing included administering a pilot survey to 853 residents, re-administering the survey to 100 of these residents, and then examining results at the data element level, the respondent/questionnaire level, and the measure (that is, facility) level. The data elements of the CoreQ: SS DC measure were found to be highly repeatable, with pilot and re-administered responses agreeing between 94 percent and 97 percent of the time, depending on the question. In other words, the same results were produced a high proportion of the time when assessed in the same population in the same time period. The questionnaire-level scores were also highly repeatable, with pilot and re-administered responses agreeing 98 percent of the time. Finally, reliability at the measure (that is, facility) level was also strong. Bootstrapping analyses in which repeated draws of residents were randomly selected from the measure population and scores were recalculated showed that 17.82 percent of scores were within 1 percentage point of the original score, 38.14 percent were within 3 percentage points of the original score, and 61.05 percent were within 5 percentage points of the original score. These results demonstrate that the CoreQ: SS DC measure scores from the same facility are very stable across bootstrapped samples.

The measure steward also conducted extensive validity testing of the CoreQ: SS DC measure's questionnaire, which included examination of the items in the questionnaire, the questionnaire format, and the validity of the CoreQ: SS DC measure itself.

First, the measure steward tested the items in the CoreQ: SS DC questionnaire to determine if a subset of items could reliably be used to produce an overall indicator of customer satisfaction. The measure steward started with 22 pilot questions, which assessed an individual's satisfaction with a number of concepts, such as food, environment, activities, communication, and responsiveness. Through repeated analyses, the number of questions was narrowed down to four. The four questions in the CoreQ: SS DC measure's final questionnaire were found to have a high degree of criterion validity, supporting that the instrument measures a single concept of “customer satisfaction,” rather than multiple areas of satisfaction.

Next, the validity of the four-question CoreQ: SS DC measure summary score was compared to the more expansive set of 22 pilot questions, and was found to have a correlation value of 0.94, indicating that the CoreQ: SS DC measure's questionnaire consisting of four questions adequately represents the overall satisfaction of the facility.

Finally, the measure steward found moderate levels of construct validity and convergent validity when the CoreQ: SS DC measure's relationship with Certification and Survey Provider Enhanced Reports (CASPER) Quality Indicators, Nursing Home Compare Quality Indicators, Five Star Ratings and staffing levels was examined. Therefore, the CoreQ: SS DC measure's questionnaire format has a high degree of both face validity and content validity.

Since the CoreQ: SS DC measure's original CBE endorsement in 2018, and its subsequent use by SNFs in quality improvement (see section VI.C.2.a.(1) of the proposed rule), the measure steward conducted additional testing, including examining the reportability of the measure. Testing found that when the CoreQ: SS DC measure's questionnaires were administered within one week of facility discharge, the response rate was 8 percent higher than if it was administered 2 weeks after facility discharge. The measure steward analyzed responses when it allowed up to 2 months for a resident to respond, and found the average time to respond to the CoreQ: SS DC questionnaire was 2 weeks, while the response rate dropped much lower in the second month after facility discharge. The measure steward also conducted additional analyses to determine if there was any bias introduced into the responses to the CoreQ: SS DC's questionnaires that were returned during the second month, and found that average scores for the questionnaires returned in the second month were almost identical to those returned in the first month. Finally, the measure steward examined the time period required to collect the CoreQ: SS DC measure's data, and found that a majority of SNFs (that is, 90 percent) could achieve the minimum sample size of 20 completed CoreQ: SS DC questionnaires necessary for the satisfaction score to be reported as reliable for the SNF, when given up to 6 months. Additionally, once 125 consecutive completed CoreQ: SS DC questionnaires were received for a particular SNF, the measure steward found that including additional CoreQ: SS DC questionnaires had no additional effect on the SNF's satisfaction score. As a result of these additional analyses, the recommendations to allow up to 2 months for CoreQ: SS DC questionnaire returns, a 6-month reporting period, and a ceiling of 125 completed questionnaires in a 6-month period were incorporated into the CoreQ: SS DC measure's specification.

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act be endorsed by a CBE with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

Although the CoreQ measure is CBE endorsed for SNFs, we did consider whether there were other CBE endorsed measures capturing SNF resident satisfaction after discharge from a SNF in less than 100 days. We found several CBE endorsed measures used in other programs that assess resident experiences for specific resident populations, such as residents at end of life, residents with low back pain, and residents receiving psychiatric care. However, we did not find other CBE endorsed measures that assess satisfaction of residents discharged within 100 days of their admission to the SNF.

(3) Interested Parties and Technical Expert Panel (TEP) Input

We employ a transparent process to seek input from interested parties and national experts and engage in a process that allows for pre-rulemaking input on each measure, under section 1890A of the Act. To meet this requirement, we solicited feedback from interested parties through an RFI in the FY 2022 SNF PPS proposed rule (86 FR 19998) on the importance, relevance, and applicability of patient-reported outcome (PRO) measures for SNFs. In the FY 2022 SNF PPS final rule (86 FR 42490 through 42491), we noted that several commenters supported the concept of PROs while others were uncertain what we intended with the term “patient-reported outcomes.” One commenter stressed the importance of PROs since they determine outcomes based on information obtained directly from residents, and therefore provide greater insight into residents' experience of the outcomes of care. Another commenter agreed and stated that residents and caregivers are the best sources of information reflecting the totality of the resident experience.

We solicited public comments from interested parties specifically on the inclusion of the CoreQ: SS DC measure in a future SNF QRP year through an RFI in the FY 2023 SNF PPS proposed rule (87 FR 22761 through 22762). In the FY 2023 SNF PPS final rule (87 FR 47555), we noted that support for the CoreQ: SS DC measure specifically was mixed among commenters. One commenter stated that since the CoreQ: SS DC measure has a limited number of questions, it may not fully reflect resident experience at a given facility. Another commenter would not support the CoreQ: SS DC measure since it excludes residents who leave a facility against medical advice and residents with guardians, and this commenter stated it would be important to hear from both of these resident populations. Two commenters cautioned us to consider the burden associated with contracting with third-party vendors to administer the CoreQ: SS DC measure.

(4) Measure Application Partnership (MAP) Review

The CoreQ: SS DC measure was initially endorsed by the CBE in 2016. It was originally reviewed by the CBE's Person- and Family-Centered Care (PFCC) Committee on June 6, 2016. The PFCC Committee members noted the importance of measuring residents' experiences and their preferences given health care's changing landscape. Overall, the PFCC Committee members liked that there was a conceptual framework associated with the measure submission that linked the CoreQ: SS DC measure with other improvement programs and organizational change initiatives that can help SNFs improve the quality of care they provide. Some PFCC Committee members expressed concern around the consistency of implementation across SNFs and whether scores could be compromised by a low response rate. All PFCC Committee members agreed to not risk-adjust the CoreQ: SS DC measure as it would be inappropriate to control for differences based on sociodemographic factors. We refer readers to the PFCC Final Report—Phase 3.

The following year, the CoreQ: SS DC measure was included on the publicly available “List of Measures under Consideration for December 1, 2017” for the SNF QRP Program, but the MAP did not receive any comments from interested parties. The CBE convened MAP PAC/LTC workgroup met on December 13, 2017 and provided input on the CoreQ: SS DC measure. The MAP PAC/LTC workgroup offered support of the CoreQ: SS DC measure for rulemaking, noting that it adds value by adding addressing a gap area for the SNF QRP. The MAP PAC/LTC workgroup emphasized the value of resident-reported outcomes and noted that the CoreQ: SS DC measure would reflect quality of care from the resident's perspective. However, the MAP PAC/LTC workgroup also noted the potential burden of collecting the data and cautioned that the implementation of a new data collection requirement should be done with the least possible burden to the SNF.

(5) Quality Measure Calculation

The CoreQ: SS DC measure is a resident-reported outcome measure based on the CoreQ: SS DC questionnaire that calculates the percentage of residents discharged in a 6-month period from a SNF, within 100 days of admission, who are satisfied with their SNF stay. Unless otherwise exempt from collecting and reporting on the CoreQ: SS DC measure (as discussed in section VI.F.3.b. of the FY 2024 SNF PPS proposed rule), we proposed that each SNF must contract with an independent CMS-approved CoreQ survey vendor to administer the CoreQ: SS DC measure questionnaire, and report the results to us, on behalf of the SNF (as specified in sections VI.F.3.a. and VI.F.3.c. of the FY 2024 SNF PPS proposed rule).

The CoreQ: SS DC measure questionnaire utilizes four questions (hereafter referred to as the four primary questions) and uses a 5-point Likert scale as illustrated in Table C3.

We also proposed to add two “help provided” questions to the end (as questions five and six) of the CoreQ: SS DC questionnaire to determine whether to count the CoreQ: SS DC questionnaire as a completed questionnaire for the CoreQ: SS DC measure denominator or whether the questionnaire should be excluded as described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual available on the SNF QRP Measures and Technical Information web page. These two “help provided” questions are:

5. Did someone help you [the resident] complete the survey?

6. How did that person help you [the resident]?

(a) Denominator

The denominator is the sum of all of the questionnaire-eligible residents, regardless of payer, who (1) are admitted to the SNF and discharged within 100 days, (2) receive the CoreQ: SS DC questionnaire, and (3) respond to the CoreQ: SS DC questionnaire within 2 months of discharge from the SNF. However, certain residents are excluded from the denominator and therefore are not sent a CoreQ: SS DC questionnaire by the CMS-approved CoreQ survey vendor or contacted by the CMS-approved CoreQ survey vendor for a phone interview. The residents who are not eligible to respond to the questionnaire, and therefore are excluded from the denominator for the CoreQ: SS DC measure are: (1) residents discharged to another hospital, another SNF, a psychiatric facility, an IRF, or an LTCH; (2) residents who die during their SNF stay; (3) residents with court-appointed legal guardians with authority to make decisions on behalf of the resident; (4) residents discharged to hospice; (5) residents who have dementia impairing their ability to answer the questionnaire; (6) residents who left the SNF against medical advice; and (7) residents with a foreign address. Additionally, residents are excluded from the denominator if after the CoreQ: SS DC questionnaire is returned: (1) the CMS-approved CoreQ survey vendor received the CoreQ: SS DC completed questionnaire more than 2 months after the resident was discharged from the SNF or the resident did not respond to attempts to conduct the interview by phone within 2 months of their SNF discharge date; (2) the CoreQ: SS DC questionnaire “help provided” question six indicates the questionnaire answers were answered for the resident by an individual(s) other than the resident; or (3) the received CoreQ: SS DC questionnaire is missing more than one response to the four primary questions (that is, missing two or more responses).

(b) Numerator

The numerator is the sum of the resident respondents in the denominator that submitted an average satisfaction score of greater than or equal to 3 for the four primary questions on the CoreQ: SS DC questionnaire. If a CoreQ: SS DC questionnaire is received and is missing only one response (out of the four primary questions in the questionnaire), imputation is used which represents the average value from the other three available responses. If a CoreQ: SS DC questionnaire is received and is missing more than one response to the four primary questions (that is, missing two or more responses), the CoreQ: SS DC questionnaire is excluded from the analysis (that is, no imputation will be used for these residents). The CoreQ: SS DC measure is not risk-adjusted by sociodemographic status (SDS), as the measure steward found no statistically significant differences (at the 5 percent level) in scores between the SDS categories. Additional information about how the CoreQ: SS DC measure is calculated is available in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual on the SNF QRP Measures and Technical Information web page.

We solicited public comment on our proposal to adopt the CoreQ: SS DC Measure beginning with the FY 2026 SNF QRP. The following is a summary of the comments we received and our responses.

Comment: A number of commenters supported the adoption of the CoreQ: SS DC measure in the SNF QRP as a reliable and valid tool for assessing resident satisfaction. Several commenters noted the measure is CBE endorsed and expressed appreciation to CMS for proposing a measure that was supported by the MAP PAC/LTC workgroup for rulemaking. Two commenters pointed out that the CoreQ: SS DC survey is more efficient than other tools that have over 50 questions and provides a concise satisfaction rate that is intuitive for providers to act on and for consumers to understand. Another commenter supported the adoption of the CoreQ: SS DC measure not only because they believe it is an accurate measure of resident-centered care, but also because of its long tenure, validity testing, utilization in other settings, and cooperative development with SNFs and assisted living communities. One commenter noted the importance of residents/families providing direct feedback regarding the care and services received.

Response: We thank the commenters for their support of the CoreQ: SS DC measure. We agree that this CBE endorsed measure's survey is an efficient tool for both SNFs to implement and residents to complete, which would increase the likelihood that SNFs would receive robust responses they could use to advance their person-centered care practices. We agree that capturing residents' direct feedback is valuable and the proposed measure would fill a measurement gap in the SNF QRP.

We also received several comments that did not support our proposal to adopt the CoreQ: SS DC measure. Commenters gave various reasons including: a preference for using the NHCAHPS–D survey because it includes a greater number of questions; concern about the number of residents that would be excluded from receiving a CoreQ: SS DC survey; the imputation method used to calculate a CoreQ: SS DC measure score; and the burden of submitting resident information files to the CoreQ survey vendor on a weekly basis. The following is a summary of the comments we received and our responses.

Comment: While several commenters agreed that resident satisfaction surveys would provide clinical teams information to use when examining the results of their clinical care, and help SNFs identify areas for improvement, they did question why CMS did not choose to use the standardized measures contained in the Consumer Assessment of Healthcare Providers and Systems (CAHPS) that were developed by CMS with the Agency for Healthcare Research and Quality (AHRQ), and specifically the CAHPS Nursing Home survey: Discharged Resident Instrument (NHCAHPS–D)—or a portion of this instrument. Two of these commenters cited the National Academies of Sciences, Engineering, and Medicine (NASEM) report, “The National Imperative to Improve Nursing Home Quality,” which recommended the use of the CAHPS survey, which was developed by the AHRQ, in conjunction with CMS. Another commenter suggested that the use of surveys other than CAHPS conflicts with the CMS Foundational Measurement Strategy, which aims to align all adult and pediatric person-centered care domain measures with CAHPS surveys.

A number of these commenters also questioned why CMS would use a tool that was developed by the American Health Care Association (AHCA), which is the major nursing home trade association. These commenters pointed to the NASEM report's findings that many nursing homes promote and advertise high scores from self-designed and administered surveys of their residents. One of these commenters expressed concern that CMS is proposing to adopt an instrument developed by the very industry whose members it will be used to measure.

Response: We acknowledge that the NHCAHPS–D was developed for short-stay SNF residents by the AHRQ and the CAHPS® consortium in collaboration with us. We also recognize that there are other measures of resident satisfaction that are available, but we proposed the CoreQ for two primary reasons: (1) it is the only CBE endorsed survey of SNF resident satisfaction, and (2) its extensive testing prior to initial CBE endorsement in 2016 and subsequent CBE re-endorsement in 2020 and its strong item and response reliability and validity. We also considered the length of the NHCAHPS–D tool and the potential burden on respondents to complete it.

We refer the commenters to section VII.2.a.1. of this final rule where we describe how the CoreQ was developed by a team led by researchers from the University of Pittsburgh with input from an AHCA workgroup, providers, and residents specifically for assessing satisfaction among residents and their families. Furthermore, since the measure has been endorsed by a CBE on two occasions, it means that a panel of experts and interested parties representing providers, residents, and payers support this measure for inclusion in the SNF QRP.

We also refer commenters to section VII.D. of this final rule, where we discuss the measurement gaps we identified for the SNF QRP, including the measurement concepts of resident experience and resident satisfaction. We sought feedback in the FY 2024 SNF PPS proposed rule (88 FR 21355) on the value of adding a resident experience measure, such as the NHCAHPS–D, to the SNF QRP.

Comment: Several commenters opposed the adoption of the CoreQ: SS DC measure because they believe it provides limited actionable feedback for performance improvement. One of these commenters believed that organizations tend to improve resident experiences when they have data and feedback that are actionable, which comes through measuring behaviors. They do not believe the CoreQ: SS DC measure asks about behavior and therefore fails to capture meaningful feedback. They disagree with using the CoreQ: SS DC survey because it does not ask questions about whether a specific action occurred, how often it occurred, or the quality of the action or interaction. Two commenters noted that a single score would be meaningless.

Response: We understand the commenter's concerns to be related to the fact that the CoreQ: SS DC measure represents the overall satisfaction with the nursing facility. However, we believe this to be advantageous for several reasons, including its simplicity and its utility for ranking/rating purposes.

First, the simple format may be important in helping older adults and their families choose a SNF. That is, the CoreQ: SS DC measure score is understandable. At the same time, testing demonstrated the range of CoreQ measure scores was large, indicating that the scores can be used to differentiate facilities with varying levels of customer satisfaction. Second, a single score may also be useful for facilities to easily track their performance over time and a tool they might use to gauge the effectiveness of their own quality improvement processes. It is also a score a SNF could use to compare its overall level of satisfaction with other SNFs. This is something that might be much more difficult to achieve with a resident satisfaction survey that includes multiple questions about specific actions and interactions and the quality of those actions and interactions. Moreover, other resident satisfaction surveys we found were not developed or tested to produce an overall satisfaction score.

We acknowledge that the CoreQ: SS DC measure score would not provide a detailed set of information about specific actions and interactions, but a facility could have its survey vendor add as many specific questions to the survey as it wants, so it could obtain more details about why a resident responded the way they did. For more information, we refer commenters to the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual found at https://www.cms.gov/files/document/draft-coreq-ss-dc-manual508compliant.pdf.

Comment: One commenter opposed the adoption of the CoreQ: SS DC measure because it is not currently endorsed by a CBE.

Response: We refer the commenter to section VII.C.2.a.4. of this final rule for details about the CoreQ: SS DC measure's CBE endorsement. The CoreQ: SS DC measure was initially endorsed by the CBE in 2016 and re-endorsed in 2020.

Comment: One commenter noted that in the proposed rule, CMS described comments of interested parties and the Technical Expert Panel (TEP), some of whom were critical of CoreQ and whose concerns the proposed rule did not address. This commenter acknowledged that they were a member of a TEP that reviewed the CoreQ and this commenter remains extremely critical of the tool.

Response: Contrary to the commenter's assertion, we did not describe comments from a CoreQ: SS DC measure TEP in the proposed rule. As described in section VII.C.2.a.1. of the final rule, the CoreQ: SS DC survey was developed by SNFs and ALs that partnered with researchers to develop the CoreQ: SS DC survey for SNFs and ALs. TEPs are groups of experts assembled by our contractors involved in quality activities. Since neither we nor our quality measure development contractors developed the survey tool, we cannot speak to discussions that may have occurred in a provider-assembled panel associated with the measure.

However, as discussed in section VII.C.2.a.4. of this final rule, the CoreQ: SS DC measure was reviewed by the CBE's Person- and Family-Centered Care (PFCC) Committee on June 6, 2016, and subsequently the measure appeared on the List of Measures under Consideration for December 1, 2017 for the SNF QRP Program. The CBE-convened MAP PAC/LTC workgroup met on December 13, 2017, and offered support of the CoreQ: SS DC measure for rulemaking, noting that it adds value by addressing a gap area for the SNF QRP.

Comment: One commenter acknowledged that it is vital to collect information on resident experience in SNFs but suggested the CoreQ: SS DC measure is not ready to be proposed for inclusion in the SNF QRP because the CoreQ questionnaire is a proprietary tool and thus requires administration by third-party vendors, as opposed to a CAHPS survey, which is maintained by the AHRQ.

Response: We agree with the commenter that it is vital to collect information on resident experience in SNFs. We do want to clarify, however, that the CoreQ: SS DC measure's survey is not a proprietary tool and is free to SNFs and vendors. All of the CoreQ surveys (along with instructions for use) are provided on a free publicly accessible website. The website does not ask for any fees for using the CoreQ surveys.

Comment: Several commenters stated that the CoreQ: SS DC measure has not been adequately tested for reliability, nor has it been tested to determine if it produces valid data or that the data are meaningful. One of these commenters stated that the fact that many facilities have “voluntarily adopted” CoreQ, and use it “with ease,” suggests that the tool is useful to facilities. However, the commenter asserted that facilities have historically used satisfaction surveys for marketing purposes, and the CoreQ's usability does not suggest that the tool is equally useful or meaningful to government regulators. Another one of these commenters noted that calculating measure scores by only including responses with an average score greater than or equal to 3.0 will impact the statistical reliability of the measure and expressed concern that this issue, combined with the low item count of only four questions, could potentially produce a measure with extremely low statistical reliability and compromising validity.

One commenter recommended that CMS use the CAHPS measures of resident and family experience which they noted are based on actual experiences and have been thoroughly tested for validity. This commenter went on to say that they disagree with CMS' conclusion that reproduction of CoreQ: SS DC survey results indicates the measure's reliability. Instead, they stated that the CoreQ's measure properties (that is, the limited number of questions in the measure, the vagueness of the questions, and the inherent bias in the scale, the computation process, and the selection process) increase the likelihood of repeated results.

Response: As described in section VII.C.2.a.(1)(b) of this final rule, the development of the CoreQ: SS DC measure involved multiple interested parties, involved rigorous testing and review on two separate occasions, and has been thoroughly vetted. Three steps were used in developing the CoreQ: SS DC questionnaire. The first step was the development of the general approach used in the questionnaire (that is, domains, format, and potential items). The data collection for this first step mostly involved using consumers in SNFs. The second step included validity testing to further refine items that should be included in the questionnaire. The data collection for this second step involved using residents in a national sample of nursing facilities. The third step included testing to examine the reliability of the CoreQ: SS DC measure (that is, facility and summary score validity). The data collection for this third step involved using residents from a national sample of nursing facilities. These three steps in the questionnaire development follow an approach used by the CAHPS nursing home surveys. Since this initial testing, the CoreQ: SS DC survey has been used with tens of thousands of additional residents. The response rate and score distributions have remained in-line with the initial testing.

We acknowledge the commenter's point that SNFs have historically used satisfaction surveys for marketing purposes. However, this fact does not diminish the importance of adding a resident satisfaction measure to the SNF QRP. We recognize there are other instruments to measure SNF resident satisfaction, but no one universal instrument has been adopted by SNFs. Additionally, as described in section VII.C.2.a.(2) of this final rule, we did look at and consider other measure tools to meet this gap in the SNF QRP measure set. We decided to propose the CoreQ: SS DC measure specifically because it has been exhaustively tested for validity and reliability (as described in section VII.C.2.a.(1)(b) of this final rule) and it is endorsed by a CBE.

Comment: We received a number of comments about residents who would be excluded from receiving a CoreQ: SS DC survey. Most commenters were concerned that residents who left against medical advice (AMA) were excluded from the CoreQ: SS DC measure's denominator. As a result, they fear that residents who are may have been very dissatisfied with their care will not receive a survey. One of these commenters pointed out that residents leaving AMA are at a higher risk of adverse events and readmissions, and that SNFs could use these residents' experiences and reasons for leaving in the SNF's risk management and readmission prevention strategies. This commenter also pointed out that by surveying these residents, resident feedback could highlight areas where resident-SNF communication can be improved and SNFs could identify recurring problems and implement necessary changes.

Other commenters stated that residents who transfer to another SNF, psychiatric facility, IRF, LTCH, or hospice should not be excluded either.

Two commenters also noted that residents living with Alzheimer's disease or other forms of dementia should not automatically be excluded because some residents with dementia could give meaningful opinions about their SNF stay. They maintain that CMS and the public have a significant interest in assessing the care quality provided to residents with dementia. These commenters also disagree with the exclusions for surveys completed by (i) a family member (however a resident defines “family”), (ii) a representative of a former resident with dementia or of a resident who dies during their SNF stay, and (iii) a legal guardian of a resident under any circumstance. Another commenter referenced these exclusions as “discriminatory,” and stated that they are likely to skew the results to former residents who were temporarily in the facility for rehabilitation, went home, and were satisfied.

Response: We acknowledge the commenters' concerns about the CoreQ: SS DC measure exclusions. In developing the CoreQ: SS DC measure, the measure developer convened an expert panel to advise them on which exclusions to apply to the measure. The expert panel advised the measure developer to exclude residents who died, residents who were discharged to a hospital, residents with durable power of attorney for all decisions, residents on hospice, residents with low BIMS scores, and residents who left against medical advice.

Regarding the exclusion for residents who left AMA, residents who leave AMA generally do so within the first few days of admission to the SNF. As a result, the SNF has not yet had time to develop and implement a full care plan to address the resident's needs. The measure developer was not confident they could validate their answers as accurate or unbiased.

Regarding the exclusion for residents who transfer to another SNF, IRF, LTCH, or hospice, the exclusions were applied because such residents were incapable or unlikely to complete a questionnaire.

Regarding the exclusion for residents living with Alzheimer's disease or other forms of dementia, the exclusion applied in the denominator is for residents with a BIMS score of 7 or lower. A BIMS score of 7 represents residents with severe cognitive impairment, and the measure developer determined that they were unable to validate the responses as reliable, and the response rate dropped considerably in this population.

With respect to the exclusion for surveys completed by a family member, representative, legal guardian, or other proxy, the exclusion was applied because the measure developer could not be confident the responses were accurate or unbiased. However, we are intentional in our efforts to increase the resident's voice in the assessment process and SNF QRP. All residents capable of any communication should be asked to provide information for the CoreQ: SS DC measure. Self-reporting is the single most reliable indicator of resident satisfaction. For that reason, we proposed to add two additional “help provided” questions to the original four primary questions in the CoreQ: SS DC measure. These questions would be used by the vendor to identify and code all completed surveys where a helper assisted the respondent. A decision algorithm was proposed to determine whether a CoreQ survey would be included or excluded from the CoreQ: SS DC measure numerator based on whether a helper completed the survey for the resident or whether the helper only assisted the resident due to visual, hearing, or motor coordination impairments. Residents requiring assistance only due to visual, hearing, or motor coordination impairments would be not be excluded.

Comment: Several commenters disagreed with using the CoreQ: SS DC survey because they found the number of questions to be too small, and they found the questions too vague to provide enough meaningful information for actionable improvement. One of these commenters suggested that CMS proposed a measure that is so simple that it tells consumers almost nothing about the resident's experience. This commenter, and two others, provided extensive examples of why they found each of the CoreQ: SS DC survey questions problematic. One of these commenters acknowledged that 50 questions may be very long for some residents but noted that the questions on such a survey provide much more meaningful information than the very vague four questions that constitute the CoreQ. One commenter stated the wording of the CoreQ: SS DC survey is potentially coercive in nature, implying an expected recommendation. In comparison, they noted the CAHPS Nursing Home Survey tactfully phrases similar questions to avoid such implications.

Finally, several commenters noted the CoreQ: SS DC survey does not adequately capture resident satisfaction with all types of HCP and does not represent the totality of SNF care. These commenters noted that SNF care is multifaceted, encompassing multiple disciplines and components, including activities, diet, nursing, social work, and therapies. These commenters stated that residents may have positive experiences in some aspects of their stay and negative experiences in others. One of these commenters expressed concern that the measure could potentially be gamed through a SNF's emphasis on activities that may be appealing to residents and caregivers, but do not meaningfully improve function or other outcomes. Another one of these commenters suggested that CMS should use surveyor interviews with residents, resident councils, and families to create a satisfaction score.

Response: We found the process that was used to develop the CoreQ: SS DC measure to be iterative, comprehensive, and widely published. We provide more details here and refer readers the CoreQ website at http://coreq.org/ to learn more.

The first step of the development of the CoreQ: SS DC measure was to determine the domains, format, and potential items to include in the survey. This first step involved using consumers in nursing facilities. Following prior research in this area, a literature review was conducted to examine (a) important areas of satisfaction for long-term care residents (commonly called domains), (b) response scales used, and (c) individual items used in existing surveys. The research team examined 15 commonly used satisfaction surveys and reports addressing consumer satisfaction in long-term care settings.

Next, a total of 35 domains of interest were identified. The face validity of these 35 domains was examined using nursing facility residents. That is, residents were asked to rank the importance of the domains. Residents were asked to rank only 12 of the 35 domains to help simplify the process. After analyzing the responses, there was a substantial reduction in ranking of the tenth and subsequent domains, so the nine most highly ranked domains were chosen. For the nine domains of interest, individual items (questions) were selected. That is, as many items as could be found in these domains were taken from the 15 commonly used satisfaction surveys identified previously in this section.

A list of 140 items resulted, and these were reduced in three steps. First, a team of five satisfaction survey experts, in an iterative process consisting of six rounds of consultation, identified items that most represented the domains. In each round of consultation, 100 percent agreement was used for deleting items in each domain. This process is generally known as “Member Checking.” In the second step, the survey experts were asked to isolate individual items that measured the satisfaction of each domain globally. In each round of consultation, 100 percent agreement was used for deleting items in each domain. The items thus could potentially be used to measure overall issues in this domain, rather than more focused issues in the domain. Third, the items were further reduced, again using member checking. The five satisfaction survey experts identified items they believed to be the most easily understood by potential respondents.

The resulting items were included as part of the Pilot CoreQ: Short Stay Discharge questionnaire, which consisted of 24 items. The intent of the pilot instrument was to have items that represented the most important areas of satisfaction and to be parsimonious. Additional analyses were used to eliminate items in the Pilot instrument. The Pilot CoreQ: Short Stay Discharge questionnaire items were subsequently examined to first determine the validity of the items included and second to determine if the items could be reduced with the objective of finding the lowest number of items providing the most consumer satisfaction information.

The Pilot CoreQ: Short Stay Discharge questionnaire was then sent to 865 residents who had been discharged from a SNF in less than 100 days and who met the inclusion criteria. The Pilot CoreQ: Short Stay Discharge questionnaire items were examined to determine the fewest number of items providing the most consumer satisfaction information. That is, the 24 items were examined to determine if some were globally representing the residents' overall rating of their satisfaction with the facility. Conceptually, the intent of the item reduction was to identify items (a) highly correlated with overall satisfaction, (b) having low correlations with each other, and (c) in different domains. The steps previously mentioned resulted in a short four-item instrument, the CoreQ: Short Stay Discharge questionnaire. From this instrument, a single metric was developed, the CoreQ: Short Stay Discharge measure. To determine if the 4 items in the CoreQ: Short Stay Discharge questionnaire were a reliable indicator of satisfaction, the correlation between these four items in the CoreQ: Short Stay Discharge Measure and all of the items on the Pilot CoreQ instrument was conducted. The correlation was identified as having a value of 0.94. That is, the correlation score between the final CoreQ: Short Stay Discharge Measure and all of the 22 items used in the Pilot instrument indicates that the satisfaction information is approximately the same if the survey included the four items or the 22 item Pilot instrument.

In summary, the CoreQ: SS DC measure questions were not found to be vague by the SNF residents who participated in the testing of the CoreQ survey. The CoreQ: Short Stay Discharge questionnaire was purposefully written using simple language. No a priori goal for reading level was set; however, a Flesch-Kinkaid scale score of six, or lower, is achieved for all questions. The CoreQ: SS DC survey was developed with extensive input from residents, nursing home personnel, other survey vendors, and clinical researchers. As outlined previously in this section, the CoreQ: SS DC measure represents a resident's overall satisfaction with the SNF, including all types of HCP and SNF care. Additionally, three State Medicaid programs have incorporated the CoreQ: SS DC measure into their Medicaid quality incentive programs. As we noted before, SNFs could work with their vendors to add additional questions to their survey instrument in order to ask about other aspects of their care that they believe would help them in their quality improvement efforts.

Finally, we were unable to determine what the commenter means when they suggested the wording of the CoreQ: SS DC survey is potentially coercive in nature. The language used in the CoreQ: SS DC measure is similar to language found in other survey instruments, including the NHCAHPS–D.

Comment: One commenter was concerned that if the CoreQ: SS DC measure was implemented in the SNF QRP, it would overlap considerably with a SNF's own satisfaction survey activity. This commenter also considers the CoreQ: SS DC measure to be an imperfect gauge of care quality. Specifically, they take issue with the question that asks whether a resident's discharge needs were met. They are concerned that residents may respond based on dissatisfaction with how their discharge needs were met based on limitations of their insurance network which are beyond the control of the SNF. Therefore, they recommended CMS reconsider the elements of the CoreQ questionnaire.

Response: The CoreQ: SS DC measure could be an adjunct to a SNF's own satisfaction survey activity. As described in Chapter 6 of the Draft CoreQ: SS DC Short Stay Discharge Survey Protocols and Guidelines Manual, the CoreQ: SS DC measure's set of four primary questions and two help-provided questions could be added to existing surveys used by SNFs or could be used alone to collect satisfaction information.

Regarding the comment that the CoreQ: SS DC measure is an imperfect gauge of care quality, reliability testing results at both the data element and the measure level were strong. The CoreQ: SS DC measure has a high degree of both face validity and content validity. In response to the concern that residents may respond based on dissatisfaction with how their discharge needs were met for reasons beyond the control of the SNF, we note that during the discharge planning process, it is incumbent on SNFs to make reasonable assurances that the resident's needs will be met in the next care setting.

Comment: Several commenters did not support adoption of the CoreQ: SS DC survey because they found the response scale to be skewed and lacking objectivity.

As described in section VII.C.2.a.(1) of this final rule, the CoreQ questionnaires use a 5-point Likert scale, and the number of respondents with an average score greater than or equal to 3.0 across the four questions is divided by the total number of valid responses to yield the SNF's satisfaction score. The five responses options are: Excellent (5), Very Good (4), Good (3), Average (2), and Poor (1). These commenters objected to the fact that the scale had no middle “neutral” choice and believe this grading system could create bias in the survey instrument by leading the resident to a more positive response and skews the results to the positive side. One commenter questioned what the term “average” may mean to a resident who had only experienced care in one SNF, and as a result they would not know whether the care they received was “average.” This commenter was also concerned that since the term “average” is used as a choice, then all the other terms refer to it, so that Good (3), Very Good (4), and Excellent (5) must all be better than average under this scoring system. Another commenter provided the example that because the middle score, Good (3), is a positive response, and not a neutral answer, there is only a single negative response (Poor [1]). As a result, they believe this methodology overstates positive responses. Another commenter pointed out that CAHPS surveys use a top box score methodology and other survey-based measures may use a simple mean, but the CoreQ: SS DC measure calculates a score by using an unbalanced response scale, and only includes data from residents that provide an average rating of greater than or equal to three.

Several of these commenters also quoted the NASEM report which noted that consumer advocates and survey methodologists have raised concerns that item wording and the choice of response formats may increase the tendency of respondents to provide socially appropriate response choices and thus provide only minimal variation in the scale.

Response: During the development of the CoreQ: SS DC measure, a total of 14 different scales were tested, including scales ranging from 1 to 10. Respondents were asked whether they fully understood how the response scale worked, could complete the scale, and in cognitive testing understood the scale. The scale used in the CoreQ: SS DC measure performed as well or better than the other scales tested. Based on testing conducted by the measure developer at that time, as well as since the use of the CoreQ: SS DC measure by interested parties, the distribution of CoreQ scores is large, and the measure developer has not observed a ceiling effect, which would be expected if the scale only allowed for minimal variation in responses.

In response to the comment about how item wording and choice of response formats may increase the tendency of responses to provide “socially appropriate” response choices, the NASEM report did not reference the CoreQ specifically when making this statement, and it is unclear to us how to interpret the statement in the context of our proposal.

Comment: One commenter supported the addition of two questions to the four primary questions of the CoreQ: SS DC survey that would allow CMS to determine the level of possible intermediary assistance, and therefore, exclude only surveys that met the exclusion criteria outlined in the draft CoreQ: SS Protocols and Guidelines manual. Two commenters were concerned that a significant number of eligible residents would be excluded from the measure simply because an adult child or neighbor assists with completion of the survey. These commenters pointed out that a number of residents served in a SNF face limitations and if they need assistance from a family member or trusted friend to complete the CoreQ: SS DC survey, they should not be excluded from the data files.

Response: We thank the commenter for their support of the two additional helper provided questions to determine the level of possible intermediary assistance a resident receives when completing the CoreQ: SS DC measure survey. Additionally, just because a resident is assisted by an adult child or neighbor does not mean they would automatically be excluded. As described in Chapter 8 of the Draft CoreQ: SS DC Protocols and Guidelines Manual, a decision algorithm would be used to determine whether a CoreQ survey is included or excluded from the CoreQ: SS DC measure denominator based on whether a helper completed the survey for the resident or whether the helper only assisted the resident due to visual, hearing, or motor coordination impairments. Residents would not be automatically excluded just because they required assistance with reading the survey, having the survey translated into their own primary language, or completing the mailed survey due to physical impairments.

Comment: Two commenters suggested that most SNF residents require in-person interviews for data collection because many residents have vision, hearing, and cognitive problems. They stated CMS' plan does not allow for adequate data sampling and data collection and could result in biased results.

Response: As discussed in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual, CMS-approved CoreQ survey vendors would be required to offer a toll-free assistance line and an electronic mail address which respondents could use to seek help with completing the survey. Additionally, residents could ask a family member or friend to assist them by reading the survey to them or translating the survey into their primary language. Such methods of assisted data collection have been used successfully for surveys in other PAC settings, including home health agencies.

Comment: Several commenters opposed the use of imputing a response to obtain a score when only one of the questions is missing a response. One of these commenters noted that imputation for missing data is appropriate only if it is assumed that all measures are equivalent or redundant to each other and the sum of the remaining responses can “stand in” for missing data. The commenter suggested that if individual measures are intended to address unique facets of experience, or if different populations or groups of respondents might have reason to skip particular items, imputation would be inappropriate and misleading. Another one of these commenters suggested that survey questionnaires with missing data should be discarded.

Response: We appreciate the concerns that some commenters may have with imputation of a missing score. However, the measure developer tested the imputation method as part of their overall measure development process. Two methods of imputing missing data were tested: (1) using the average value from the three available questions as the imputed value, and (2) using the lowest value from the three available questions as the imputed value. They found that imputing the average score or imputing the lowest score had no influence on the overall CoreQ measure scores for SNFs. The measure developer also correlated cases with one missing value imputed and cases with no missing values with quality indicators (that is, restraint use, pressure ulcers, catheter use, antipsychotic use, antidepressant use, antianxiety use, use of hypnotics, and deficiency citations). They found the correlation with these quality indicators unchanged and therefore bias from imputation was minimal.

Comment: While one commenter believed a short stay discharge measure is long overdue within the SNF QRP, they stated that CMS should first provide additional guidance on how it will benchmark and/or risk-adjust the measure among SNFs and over time. They stated any final methodology must factor in improvements over time, and not just the absolute score relative to all SNFs or even a smaller cohort of peers. This commenter recommended that CMS also carefully consider whether/which kinds of SNFs will perform well or poorly depending on multiple variables. They stated that facilities in underserved areas with high prevalence of social determinants of health (SDOH) and predominated by SNFs with lower star ratings will not perform well on measures of resident satisfaction, resulting in exacerbation of access in underserved communities. Another commenter is concerned that the measure is not risk-adjusted.

Response: As described in section VII.C.2.a.(5)(b) of this final rule, the CoreQ: SS DC measure is not risk-adjusted by resident level sociodemographic status (SDS) variables, as the measure steward found no statistically significant differences (at the 5 percent level) in scores between the SDS variables. We do reevaluate measures implemented in the SNF QRP on an ongoing basis to ensure they have strong scientific acceptability as well as appropriately capture the care provided by SNFs. Lastly, we take the appropriate access to care in SNFs very seriously and monitor closely to determine whether new SNF QRP measures have unintended consequences on access to care for high-risk residents.

Comment: One commenter disagreed with how the CoreQ: SS DC measure is calculated. They believe that since it only includes respondents that have an average score greater than or equal to 3.0 and then dividing that number by the total number of valid responses to the survey that SNFs will only be incentivized to drive improvement from Poor or Average to Good. They stated the methodology used to calculate a score for the CoreQ: SS DC measure is inconsistent with the calculations of other measures used by CMS and generally viewed as statistically unreliable. Another commenter was concerned that the CoreQ: SS DC survey focuses less on rating the quality of resident experience and more on summative satisfaction ratings.

Response: We do not agree with the commenter that the CoreQ: SS DC measure score will only incentivize SNFs to drive improvement from Poor or Average to Good. The CoreQ: SS DC measure is expressed as the percentage of the SNF short stay population whose average score is three or higher. Other SNF QRP measures are also expressed as the percentage of the SNF population who meet or exceed a threshold.

We believe that the CBE endorsed CoreQ: SS DC measure has been extensively tested and is highly reliable, valid, and reportable, and would fill a critical measurement gap within the SNF QRP. However, we acknowledge the concerns raised by commenters that the CoreQ: SS DC measure may not have enough questions to adequately measure residents' satisfaction with the quality of care received by SNFs. We also recognize the concerns raised by commenters that finalizing the CoreQ: SS DC measure would require SNFs to contract with a survey vendor and implement a workflow to create and send a resident information file (RIF) to the vendor on a weekly basis. Therefore, after consideration of the public comments we received on this proposal, we have decided that at this time, we will not finalize the proposal to add the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. However, we remain committed to the timely adoption of a meaningful measure that addresses resident satisfaction or resident experience for the SNF QRP. As we stated in the FY 2024 SNF PPS proposed rule (88 FR 21344), there is currently no national standardized satisfaction questionnaire that measures a resident's satisfaction with the quality of care received in SNFs. While it may require time to conduct further research to identify and/or develop a meaningful measure that meets the needs of both SNFs and consumers, we intend to propose a resident satisfaction or resident experience measure for the SNF QRP in future rulemaking.

b. COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP

(1) Background

COVID–19 has been and continues to be a major challenge for PAC facilities, including SNFs. The Secretary first declared COVID–19 a PHE on January 31, 2020. As of June 19, 2023, the U.S. has reported 103.9 million cases of COVID–19 and 1.13 million deaths due to COVID–19. Although all age groups are at risk of contracting COVID–19, older persons are at a significantly higher risk of mortality and severe disease following infection; those over age 80 dying at five times the average rate. Older adults, in general, are prone to both acute and chronic infections owing to reduced immunity, and are a high-risk population. Adults age 65 and older comprise over 75 percent of total COVID–19 deaths despite representing 13.4 percent of reported cases. COVID–19 has impacted older adults' access to care, leading to poorer clinical outcomes, as well as taking a serious toll on their mental health and well-being due to social distancing.

Since the development of the vaccines to combat COVID–19, studies have shown they continue to provide strong protection against severe disease, hospitalization, and death in adults, including during the predominance of Omicron BA.4 and BA.5 variants. Initial studies showed the efficacy of FDA-approved or authorized COVID–19 vaccines in preventing COVID–19. Prior to the emergence of the Delta variant of the virus, vaccine effectiveness against COVID–19-associated hospitalizations among adults age 65 and older was 91 percent for those who were fully vaccinated with a full mRNA vaccination (Pfizer-BioNTech or Moderna), and 84 percent for those receiving a viral vector vaccine (Janssen). Adults age 65 and older who were fully vaccinated with an mRNA COVID–19 vaccine had a 94 percent reduction in risk of COVID–19 hospitalizations, while those who were partially vaccinated had a 64 percent reduction in risk. Further, after the emergence of the Delta variant, vaccine effectiveness against COVID–19-associated hospitalizations for adults who were fully vaccinated was 76 percent among adults age 75 and older.

More recently, since the emergence of the Omicron variants and the availability of booster doses, multiple studies have shown that while vaccine effectiveness has waned, protection is higher among those receiving booster doses than among those receiving only the primary series. CDC data show that, among people age 50 and older, those who have received both a primary vaccination series and booster doses have a lower risk of hospitalization and dying from COVID–19 than their non-vaccinated counterparts. Additionally, a second vaccine booster dose has been shown to reduce risk of severe outcomes related to COVID–19, such as hospitalization or death, among nursing home residents. Nursing home residents who received their second booster dose were more likely to have additional protection against severe illness compared to those who received only one booster dose after their initial COVID–19 vaccination. Early evidence also demonstrates that the bivalent boosters, specifically aimed to provide better protection against disease caused by Omicron subvariants, have been quite effective, and underscores the role of up to date vaccination protocols in effectively countering the spread of COVID–19.

(a) Measure Importance

Despite the availability and demonstrated effectiveness of COVID–19 vaccinations, significant gaps continue to exist in vaccination rates. As of March 22, 2023, vaccination rates among people age 65 and older are generally high for the primary vaccination series (94.3 percent) but lower for the first booster (73.6 percent among those who received a primary series) and even lower for the second booster (59.9 percent among those who received a first booster). Additionally, though the uptake in boosters among people age 65 and older has been much higher than among people of other ages, booster uptake still remains relatively low compared to primary vaccination among older adults. Variations are also present when examining vaccination rates by race, gender, and geographic location. For example, 66.2 percent of the Asian, non-Hispanic population have completed the primary series and 21.2 percent have received a bivalent booster dose, whereas 44.9 percent of the Black, non-Hispanic population have completed the primary series and only 8.9 percent have received the bivalent booster dose. Among Hispanic populations, 57.1 percent of the population have completed the primary series and 8.5 percent have received the bivalent booster dose, while in White, non-Hispanic populations, 51.9 percent have completed the primary series and 16.2 percent have received a bivalent booster dose. Disparities have been found in vaccination rates between rural and urban areas, with lower vaccination rates found in rural areas. Data show that 55.2 percent of the eligible population in rural areas have completed the primary vaccination series, as compared to 66.5 percent of the eligible population in urban areas. Receipt of bivalent booster doses among those eligible has been lower: 18 percent of the urban population have received a booster dose, and 11.5 percent of the rural population have received a booster dose.

We proposed to adopt the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date (Patient/Resident COVID–19 Vaccine) measure for the SNF QRP beginning with the FY 2026 SNF QRP. The proposed measure has the potential to increase COVID–19 vaccination coverage of residents in SNFs, as well as prevent the spread of COVID–19 within the SNF resident population. This measure would also support the goal of the CMS Meaningful Measure Initiative 2.0 to “Empower consumers to make good health care choices through patient-directed quality measures and public transparency objectives.” The proposed Patient/Resident COVID–19 Vaccine measure would be reported on Care Compare and would provide residents and caregivers, including those who are at high risk for developing serious complications from COVID–19, with valuable information they can consider when choosing a SNF. The proposed Patient/Resident COVID–19 Vaccine measure would also facilitate resident care and care coordination during the hospital discharge planning process. A discharging hospital, in collaboration with the resident and family, could use this proposed measure's information on Care Compare to coordinate care and ensure resident preferences are considered in the discharge plan. Additionally, the proposed Patient/Resident COVID–19 Vaccine measure would be an indirect measure of SNF action. Since the resident's COVID–19 vaccination status would be reported at discharge from the SNF, if a resident is not up to date with their COVID–19 vaccine per applicable CDC guidance at the time they are admitted, the SNF has the opportunity to educate the resident and provide information on why they should become up to date with their COVID–19 vaccine. SNFs may also choose to administer the vaccine to the resident prior to their discharge from the SNF or coordinate a follow-up visit for the resident to obtain the vaccine at their physician's office or local pharmacy.

(b) Item Testing

Our measure development contractor conducted testing of the proposed standardized patient/resident COVID–19 vaccination coverage assessment item for the Patient/Resident COVID–19 Vaccine measure using resident scenarios, draft guidance manual coding instructions, and cognitive interviews to assess SNFs' comprehension of the item and the associated guidance. A team of clinical experts assembled by our measure development contractor developed these resident scenarios to represent the most common scenarios that SNFs would encounter. The results of the item testing demonstrated that SNFs that used the draft guidance manual coding instructions had strong agreement (that is, 84 percent) with the correct responses, supporting its reliability. The testing also provided information to improve both the item itself and the accompanying guidance.

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, each measure specified under section 1899B of the Act be endorsed by a CBE with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to the measures that have been endorsed or adopted by a CBE identified by the Secretary. The proposed Patient/Resident COVID–19 Vaccine measure is not CBE endorsed and, after review of other measures endorsed or adopted by consensus organizations, we were unable to identify any measures endorsed or adopted by consensus organizations for SNFs focused on capturing COVID–19 vaccination coverage of SNF residents. We found only one related measure addressing COVID–19 vaccination, the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) measure, adopted for the FY 2023 SNF QRP (86 FR 42480 through 42489), which captures the percentage of HCP who receive a complete COVID–19 primary vaccination series, but not booster doses.

Although SNFs' COVID–19 vaccination rates are posted on Care Compare, these data are aggregated at the facility level, and SNFs are not required to report beneficiary-level data to the CDC's NHSN. The COVID–19 vaccination rates currently posted on Care Compare are obtained from CDC's NHSN and reflect “residents who completed primary vaccination series” and “residents who are up-to-date on their vaccines” across the entire nursing home (NH) resident population. Residents receiving SNF care under the Medicare fee-for-service program differ from residents receiving long-term care in nursing homes in several ways. SNF residents typically enter the facility after an inpatient hospital stay for temporary specialized post-acute care, while NH residents typically have chronic or progressive medical conditions, requiring maintenance and supportive levels of care, and may reside in the NH for years. Additionally, the SNF QRP includes data submitted by non-CAH swing bed units whose data are only represented through the SNF QRP and are not included in the COVID–19 vaccination data reported to the NHSN by nursing homes. The proposed Patient/Resident COVID–19 Vaccine measure would be calculated using data collected on the MDS (as described in section VI.F.4. of the FY 2024 SNF proposed rule) at the beneficiary level, which would enhance SNFs' ability to monitor their own infection prevention efforts with information on which they can act.

Additionally, the COVID–19 reporting requirements set forth in 42 CFR 483.80(g), finalized in the interim final rule with comment period (IFC) published on May 13, 2021 entitled “Medicare and Medicaid Programs; COVID–19 Vaccine Requirements for Long-Term Care (LTC) Facilities and Intermediate Care Facilities for Individuals with Intellectual Disabilities (ICFs-IID) Residents, Clients, and Staff” (86 FR 26315 through 26316) (hereafter referred to as the May 2021 IFC) are directed at the LTC facilities' requirements and are separate from the SNF QRP. The purpose of the May 2021 IFC was to collect information which would allow the CDC to identify and alert us to facilities that may need additional support in regard to vaccine administration and education. While the COVID–19 staff vaccination requirements are being withdrawn from the Conditions of Participation, SNFs must continue to educate and offer the COVID–19 vaccine to their residents, clients, and staff, as well as perform the appropriate documentation for these activities.

The purpose of the proposed Patient/Resident COVID–19 Vaccine measure is to allow for the collection of resident vaccination data under the SNF QRP and subsequent public reporting of SNFs' facility-level resident vaccination rates on Care Compare so that Medicare beneficiaries who require short stays can make side-by-side SNF comparisons. Adoption of the proposed measure would also promote measure harmonization across quality reporting programs and provide Medicare beneficiaries the information to make side-by-side comparisons across other facility types to facilitate informed decision making in an accessible and user-friendly manner. Finally, the proposed Patient/Resident COVID–19 Vaccine measure would generate actionable data on vaccination rates that can be used to target quality improvement among SNFs.

Therefore, after consideration of other available measures that assess COVID–19 vaccination rates among SNF residents, we believe the exception under section 1899B(e)(2)(B) of the Act applies. We intend to submit the proposed measure to the CBE for consideration of endorsement when feasible.

(3) Interested Parties and Technical Expert Panel (TEP) Input

First, the measure development contractor convened a focus group of patient and family/caregiver advocates (PFAs) to solicit input. The PFAs believed a measure capturing raw vaccination rate, irrespective of SNF action, would be most helpful in resident and caregiver decision-making. Next, TEP meetings were held on November 19, 2021, and December 15, 2021 to solicit feedback on the development of patient/resident COVID–19 vaccination measures and assessment items for the PAC settings. The TEP panelists voiced their support for PAC patient/resident COVID–19 vaccination measures and agreed that developing a measure to report the rate of vaccination in a SNF/NH setting without denominator exclusions was an important goal. We considered the TEP's recommendations, and we applied the recommendations, where technically feasible and appropriate. A summary of the TEP proceedings titled Technical Expert Panel (TEP) for the Development of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) COVID–19 Vaccination-Related Items and Measures Summary Report is available on the CMS MMS Hub.

To seek input on the importance, relevance, and applicability of a patient/resident COVID–19 vaccination coverage measure, we solicited public comments in an RFI for publication in the FY 2023 SNF PPS proposed rule (87 FR 42424). Commenters were mixed on whether they supported the concept of a measure addressing COVID–19 vaccination coverage among SNF residents. Two commenters noted the measure should account for other variables, such as whether the vaccine was offered, as well as excluding residents with medical contraindications to the vaccine (87 FR 47553).

(4) Measure Applications Partnership (MAP) Review

In accordance with section 1890A of the Act, the pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the Measures Under Consideration (MUC) List, that the Secretary is considering adopting for use in Medicare programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the list. The Patient/Resident COVID–19 Vaccine measure was included on the publicly available 2022 MUC List for the SNF QRP.

After the MUC List was published, MAP received seven comments by interested parties during the measure's MAP pre-rulemaking process. Commenters were mostly supportive of the measure and recognized the importance of resident COVID–19 vaccination, and that measurement and reporting is one important method to help healthcare organizations assess their performance in achieving high rates of up to date vaccination. One commenter also noted that resident engagement is critical at this stage of the pandemic because best available information indicates COVID–19 variants will continue to require additional boosters to avert case surges. Another commenter noted the benefit of less-specific criteria for inclusion in the numerator and denominator of the proposed Patient/Resident COVID–19 Vaccine measure, which would provide flexibility for the measure to remain relevant to current circumstances. Several commenters noted their conditional support, however, and raised several issues about the measure. Specifically, one questioned whether our intent was to replace the required NHSN reporting if this measure were finalized and noted it did not collect data on Medicare Advantage residents. Another commenter suggested that nursing homes might refuse to admit unvaccinated residents, and was concerned about the costs SNFs would incur purchasing the vaccines. Another commenter raised concerns about the measure since it did not directly measure provider actions to increase vaccine uptake in the numerator and that it would only collect vaccination information on Medicare fee-for-service residents, rather than all residents, regardless of payer. Finally, one commenter was concerned because there were no exclusions for residents who refused to become up to date with their COVID–19 vaccination.

Subsequently, several MAP workgroups met to provide input on the measure. First, the MAP Health Equity Advisory Group convened on December 6, 2022. One MAP Health Equity Advisory Group member noted that the percentage of true contraindications for the COVID–19 vaccine is low, and the lack of exclusions on the measure is reasonable in order to minimize variation in what constitutes a contraindication. The MAP Rural Health Advisory Group met on December 8, 2022, and requested clarification of the term “up to date” and noted concerns with the perceived level of burden for collection of data.

Next, the MAP PAC/LTC workgroup met on December 12, 2022. The voting workgroup members noted the importance of reporting residents' vaccination status, but discussed their concerns about: (1) the duplication of data collection with the NHSN if an assessment-based measure were adopted into the SNF QRP; (2) how publicly reported rates would differ from the rates reported by the NHSN; (3) that the Patient/Resident COVID–19 Vaccine measure does not account for resident refusals or those who are unable to respond; and (4) the difficulty of implementing the definition of “up to date.” We clarified during the PAC/LTC workgroup meeting that this measure was intended to only include Medicare Part A-covered SNF stays. We further noted that the proposed Patient/Resident COVID–19 Vaccine measure does not have exclusions for resident refusals because the proposed measure was intended to report raw rates of vaccination. We explained that raw rates of vaccination collected by the proposed Patient/Resident COVID–19 Vaccine measure are important for consumer choice and PAC providers, including SNFs, are in a unique position to leverage their care processes to increase vaccination coverage in their settings to protect residents and prevent negative outcomes. We also clarified that the measure defines “up to date” in a manner that provides flexibility to reflect future changes in the CDC's guidance with respect to COVID–19 vaccination. Finally, we clarified that, like the existing HCP COVID–19 Vaccine measure, this measure would continue to be reported quarterly because the CDC has not yet determined whether COVID–19 is seasonal. Ultimately, the PAC/LTC workgroup did not achieve a 60 percent consensus vote to accept the CBE's preliminary analysis assessment of conditional support for the Patient/Resident COVID–19 Vaccine measure for SNF QRP rulemaking pending testing demonstrating the measure is reliable and valid, and CBE endorsement. Since the PAC/LTC workgroup did not reach consensus to accept, or subsequently to overturn the CBE staff's preliminary analysis assessment, the preliminary analysis assessment became the final recommendation of the PAC/LTC workgroup.

The CBE received 10 comments by interested parties in response to the PAC/LTC workgroup recommendations. Interested parties generally understood the importance of COVID–19 vaccinations' role in preventing the spread of COVID–19 infections, although a majority of commenters did not recommend the inclusion of the proposed Patient/Resident COVID–19 Vaccine measure in the SNF QRP and raised several concerns. Specifically, several commenters were concerned about vaccine hesitancy, SNFs' inability to influence measure results based on factors outside of their control, duplication with NHSN reporting requirements, data lag in public reporting of QRP data relative to NHSN's current reporting of the measure, and that the proposed Patient/Resident COVID–19 Vaccine measure is not representative of the full SNF population, noting that the proposed Patient/Resident COVID–19 Vaccine measure has not been fully tested, and encouraged us to monitor the measure for unintended consequences and ensure that the measure has meaningful results. One commenter was in support of the proposed Patient/Resident COVID–19 Vaccine measure and provided recommendations for us to consider, including an exclusion for medical contraindications and submitting the measure for CBE endorsement. Another commenter questioned why the PAC/LTC workgroup recommendation for SNF was not consistent with their recommendation for the proposed Patient/Resident COVID–19 Vaccine measure in other PAC QRPs.

Finally, the MAP Coordinating Committee convened on January 24, 2023, and noted concerns which were previously discussed in the PAC/LTC workgroup, such as the duplication of NHSN reporting requirements and potential for selection bias based on the resident's vaccination status. We were able to clarify that this measure was intended to include only Medicare Part A-covered SNF stays for facilities required to report to the SNF QRP, since the Medicare Advantage resident population is not part of the SNF QRP reporting requirements. We also noted that this measure does not have exclusions for resident refusals since this is a process measure intended to report raw rates of vaccination and is not intended to be a measure of SNFs' actions. We acknowledged that a measure accounting for variables, such as SNFs' actions to vaccinate residents, could be important, but noted that we are focused on a measure which would provide and publicly report vaccination rates for consumers given the importance of this information to residents and their caregivers.

The MAP Coordinating Committee recommended three mitigation strategies for the Patient/Resident COVID–19 Vaccine measure: (i) reconsider exclusions for medical contraindications, (ii) complete reliability and validity measure testing, and (iii) seek CBE endorsement. The Coordinating Committee ultimately reached 90 percent consensus on its recommendation of “Do not Support with potential for mitigation.” Despite the MAP Coordinating Committee's vote, we believe it is still important to propose the Patient/Resident COVID–19 Vaccine measure for the SNF QRP. As we stated in section VI.C.2.b.(3) of the FY 2024 SNF PPS proposed rule, we did not include exclusions for medical contraindications because the PFAs we met with told us that a measure capturing raw vaccination rate, irrespective of any medical contraindications, would be most helpful in resident and family/caregiver decision-making. We do plan to conduct reliability and validity measure testing once we have collected enough data, and we intend to submit the proposed measure to the CBE for consideration of endorsement when feasible. We refer readers to the final MAP recommendations, titled 2022–2023 MAP Final Recommendations.

(5) Quality Measure Calculation

The proposed Patient/Resident COVID–19 Vaccine measure is a process measure that reports the percent of stays in which residents in a SNF are up to date on their COVID–19 vaccinations per the CDC's latest guidance. This measure has no exclusions, and is not risk adjusted.

The numerator for this measure would be the total number of Medicare Part A-covered SNF stays in which residents are up to date with their COVID–19 vaccine per CDC's latest guidance during the reporting year. The denominator for this measure would be the total number of Medicare Part A-covered SNF stays discharged during the reporting period. For the SNF QRP, this would apply to all freestanding SNFs, SNFs affiliated with acute care facilities, and all non-CAH swing-bed rural hospitals.

The data source for the proposed Patient/Resident COVID–19 Vaccine measure is the MDS assessment instrument for SNF residents. For more information about the proposed data submission requirements for this measure, we refer readers to section VII.F.4. of this final rule. For additional technical information about this proposed measure, we refer readers to the draft measure specifications document titled Patient-Resident-COVID-Vaccine-Draft-Specs.pdf available on the SNF QRP Measures and Technical Information web page.

We solicited public comments on our proposal to adopt the Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 SNF QRP. The following is a summary of the comments we received on our proposal to adopt the Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 SNF QRP and our responses.

Comment: A number of commenters supported the adoption of this measure into the SNF QRP because of the importance to the safety of residents. Commenters agreed that this measure would provide another source of valuable information to current and prospective SNF residents and their family/caregivers in their decision-making process. One commenter suggested that rather than remaining specific to COVID–19, the measure could be revised to include all CDC-recommended vaccines. Two commenters also appreciated that collection of this data would only require minimal burden since it consists of only one MDS item on the discharge assessment and the item is similar to the existing resident influenza vaccination item.

Response: We thank the commenters for their support and agree that the Patient/Resident COVID–19 Vaccine measure would provide residents and caregivers, including those who are at high risk for developing serious complications from COVID–19, with valuable information they can consider when choosing a SNF. We also agree with the commenter that the measure would not add significant burden since the data item would consist of a single MDS item and SNFs would be able to use multiple sources of information available to obtain the vaccination data, such as resident interviews, medical records, proxy response, and vaccination cards provided by the resident or their caregivers. We would also publish coding guidance for the new item and SNFs will also have access to guidance from the CDC to further aid their collection of these data. Finally, we appreciate the commenter's suggestion that the measure could be revised to include all CDC-recommended vaccines and will use this input to inform our future measure development efforts.

Comment: Several commenters stated that the proposed measure was not a measure of quality of care because it did not reflect provider action. They noted that there may be medical, religious, and/or cultural reasons for a resident's decision not to receive a vaccine that are out of a SNF's control. One commenter noted that it is possible for a SNF to have a robust effort to encourage vaccination among its patients/residents, but still have a relatively low rate of vaccination. Another commenter noted that resident vaccination may also be influenced by political beliefs and the political environment in a resident's region. One commenter noted that continuing disparities in vaccine uptake do not reflect the local SNFs' efforts to bring their residents up to date, but often reflect differences deeply rooted in culture, religion, ethnicity, socioeconomic status, and more. Some commenters pointed out that residents have the right to refuse vaccination, in the same way they have the right to refuse other medical and nursing interventions.

Response: While we agree with the commenters that residents have the right to refuse vaccination, we disagree with the commenters who suggested the proposed Patient/Resident COVID–19 Vaccine measure is an invalid measure of quality of care. On the contrary, we believe it would be a beneficial addition to the other vaccination measures in the SNF QRP. We believe it is an indirect measure of provider action since SNFs have the opportunity to encourage, as well as coordinate, vaccinations among residents. This is particularly important for residents at SNFs, who tend to be older and thus more vulnerable to serious complications from COVID–19. CDC data show that, among people age 50 and older, those who have received both a primary vaccination series and booster doses have a lower risk of hospitalization and dying from COVID–19 than their non-vaccinated counterparts. Additionally, a second vaccine booster dose has been shown to reduce risk of severe outcomes related to COVID–19, such as hospitalization or death, among nursing home residents. Nursing home residents who received their second booster dose were more likely to have additional protection against severe illness compared to those who received only one booster dose after their initial COVID–19 vaccination.

We acknowledge that individual residents have a choice regarding whether to receive a COVID–19 vaccine or booster dose(s), but residents and their caregivers also have choices about selecting PAC providers, and it is our role to empower them with the information they need to make an informed decision by publicly reporting the data we receive from SNFs on this measure. We understand that despite a SNF's best efforts, there may be instances where a resident may choose not to receive a booster dose of the COVID–19 vaccine. However, we want to remind SNFs that this measure does not mandate residents be up to date with their COVID–19 vaccine. The number of residents who have been vaccinated in a SNF does not impact a SNF's ability to successfully report the measure to comply with the requirements of the SNF QRP. Finally, we do appreciate SNFs' commitment and efforts at ensuring residents are educated and encouraged to become and remain up to date with their COVID–19 vaccinations.

Comment: One commenter noted that, while some SNFs have been extremely successful, especially with their long-stay residents, in having a high degree of acceptance of the COVID–19 vaccines throughout the last 3 years, this success is not a proxy for providing the actual care and services a resident has come to the SNF to receive. Another commenter noted that CMS's statement “SNFs could choose to administer the vaccine to the resident prior to discharge” seemed to indicate that vaccination is a SNF's choice, and not a resident's choice.

Response: The primary intent of the Patient/Resident COVID–19 Vaccine measure is to promote transparency of raw data regarding COVID–19 vaccination rates for residents and their caregivers to make informed decisions for selecting facilities. This measure will provide potential residents and their caregivers with an important piece of information regarding vaccination rates as part of their process of identifying SNFs they would want to seek care from, alongside other measures available on Care Compare, to make an informed, comprehensive decision. In response to the comment about our statement in the proposed rule that seemed to indicate vaccination is a SNF's choice, and not a resident's choice, we appreciate the opportunity to clarify the statement. We acknowledge and support a resident's choice about whether to receive an up to date vaccine. Our statement was meant to convey that the SNF could work with the resident to determine the most appropriate approach for them.

Comment: One commenter noted that sometimes patients/residents may not have the opportunity to “shop” for a facility outside of their region simply based on the COVID–19 vaccinations rates. They noted that insurance and proximity to loved ones are often the drivers for selecting a post-acute care facility.

Response: We acknowledge that sometimes residents may not have access to as many SNF choices as others. However, we believe that the information provided by this measure will still be valuable to potential SNF residents/caregivers who may have geographic limitations.

Comment: One commenter noted that vaccination administration rates can ebb and flow significantly based on factors outside the control of SNFs, including holidays, weather, vaccine/pharmaceutical supply chain management, staff availability and more.

Response: We are unaware of any access issues to COVID–19 vaccines or vaccine production delays. While we believe SNFs will be able to administer the COVID–19 vaccine if a resident consents, this measure does not require SNFs to administer the vaccine themselves. They could arrange for the resident to obtain the vaccine outside of their facility, or work with community pharmacies to obtain vaccines.

Comment: One commenter agreed with CMS's proposed justification that the measure has the potential to drive COVID–19 vaccination uptake among SNF residents and prevent the spread of COVID–19 in the SNF population and agreed that the measure could help empower consumers in making decisions about their care. Despite this, they still urged CMS to ensure that measures are appropriately specified and adequately tested and validated prior to implementation. This commenter also noted that unlike the proposed HCP COVID–19 Vaccine measure, the specifications for this Patient/Resident COVID–19 Vaccine measure solely reference the definition of up to date as described on CDC's “Stay Up to Date” website. Even though this definition more accurately reflects the most current Advisory Committee on Immunization Practices (ACIP) recommendation, the commenter urged CMS to ensure that this approach to specifying measures is valid and will not serve to cause confusion or reporting challenges in the future.

However, several commenters did not support the proposal due to the measure not being fully tested for reliability and validity, and one commenter raised concerns about the feasibility to report this measure as well as the measure's ability to produce statistically meaningful information.

Response: We are pleased that the commenter agrees with our proposed rationale that the measure has the potential to drive COVID–19 vaccination uptake among SNF residents, prevent the spread of COVID–19 in the SNF population, and empower consumers in making decisions about their care.

While we acknowledge that we have not yet tested the measure for reliability and validity, we have tested the item proposed for the MDS to capture data for this measure and its feasibility and appropriateness. Since a COVID–19 vaccination item does not yet exist within the MDS, we developed clinical vignettes to test item-level reliability of a draft Patient/Resident COVID–19 Vaccine measure. The clinical vignettes were a proxy for resident records with the most common and challenging cases SNFs would encounter, similar to the approach that we use to train SNFs on all new assessment items, and the results demonstrated strong agreement (that is, 84 percent).

Validity testing has not yet been completed, since the COVID–19 vaccination item does not yet exist on the MDS. However, the Patient/Resident COVID–19 Vaccine measure was constructed based on prior use of similar items, such as the Percent of Residents or Patients Who Were Assessed and Appropriately Given the Seasonal Influenza Vaccine (Short Stay) for the IRF and LTCH QRPs. Four Nursing Home Quality Initiative (NHQI) pneumococcal vaccination measures also use similar item construction. We have used these types of patient/resident vaccination assessment items in the calculation of vaccination quality measures in our PAC QRPs and intend to conduct reliability and validity testing for this specific Patient/Resident COVID–19 Vaccine measure once the COVID–19 vaccination item has been added to the MDS and we have collected sufficient data. Additionally, we solicited feedback from our Technical Expert Panel (TEP) on the proposed assessment item and its feasibility. No concerns were raised by the TEP regarding obtaining the information that would be required to complete the new COVID–19 vaccination item.

Comment: Several commenters did not support the measure and pointed to the fact that the MAP Coordinating Committee reached 90 percent consensus on its recommendation of “do not support with potential for mitigation” when evaluating this proposed measure. Two of these commenters also urged CMS to delay adoption of the measure until concerns raised by the MAP Coordinating Committee have been addressed. Specifically, they encouraged CMS to address the MAP's recommendations for adding exclusions to the measure, conducting measure testing, and submitting the measure for CBE endorsement. One commenter noted they were deeply concerned about the proposal to adopt the Patient/Resident COVID–19 Vaccine measure because it appeared as though CMS disregarded the recommendations of the MAP.

Response: As part of the pre-rulemaking process, HHS takes into consideration the recommendations of the MAP in selecting candidate quality and efficiency measures. HHS selects candidate measures and publishes proposed rules in the Federal Register , which allows for public comment and further consideration before a final rule is issued. If the CBE has not endorsed a candidate measure, then HHS must publish a rationale for the use of the measure described in section 1890(b)(7)(B) of the Act in the notice. The MAP Coordinating Committee recommended three mitigation strategies for the Patient/Resident COVID–19 Vaccine measure: (i) reconsider exclusions for medical contraindications, (ii) complete reliability and validity measure testing, and (iii) seek CBE endorsement. We would like to reiterate that this measure is intended to promote transparency of raw data regarding COVID–19 vaccination rates for residents/caregivers to make informed decisions for selecting facilities, providing potential residents with an important piece of information regarding vaccination rates as part of their process of identifying SNFs they would want to seek care from. As we stated in section VI.C.2.a.(3) of the FY 2024 SNF PPS proposed rule, we did not include exclusions for medical contraindications because the PFAs we met with told us that a measure capturing raw vaccination rate, irrespective of any medical contraindications, would be most helpful in resident and family/caregiver decision-making. We intend to conduct measure testing once sufficient data on the COVID–19 vaccination item are collected through the MDS and plan to submit the measure for CBE endorsement when it is technically feasible to do so.

Comment: Several commenters were concerned about the burden this measure places on SNFs as a result of having a new assessment item in the MDS, especially in light of changing guidelines around vaccine requirements, and workforce shortages. One commenter noted that the proposed changes to the measure will require SNFs to track CDC guidance on a quarterly basis and will also require SNFs to change their processes to track whether residents have received multiple doses. Two commenters noted that if CDC were to update its guidance and require booster doses, SNFs would then need to validate and track whether all residents met the new requirements, creating an added burden for SNFs to adapt to the new recommendations that will take both time and staff resources.

Response: To ensure appropriate coding of the assessment item, SNFs would be able to use multiple sources of information to obtain a resident's vaccination status, such as resident interviews, medical records, proxy response, and vaccination cards provided by the resident or their caregivers. As with any assessment item in the MDS, we will also publish coding guidance and instructions to further aid SNFs in collection of these data. Additionally, we believe SNFs should be assessing whether residents are up to date with COVID–19 vaccination as a part of their routine care and infection control processes, and during our item testing, we heard from SNFs that they are routinely inquiring about COVID–19 vaccination status when admitting residents already.

Comment: One commenter was concerned that the proposed Patient/Resident COVID–19 Vaccine measure could have unintended consequences if adopted. Another commenter stated the adoption of the measure would create a difficult dynamic for SNFs. They suggested SNFs would have two choices when making a decision whether to admit a resident who is not up to date with their COVID–19 vaccine: (1) not offer admission to residents who are not up to date with CDC recommendations, because they stated it would result in the SNF receiving a low-quality score on this measure, or (2) admit the resident, administer a COVID–19 vaccination to bring them in line with CDC recommendations even though the vaccine may increase the resident's risk of adverse health outcomes. One commenter pointed to the concerns raised by MAP and other interested parties and states CMS should consider the potential impacts of its approach on vaccination efforts. They caution that as SNFs are endeavoring to follow the vaccine guidelines and gain resident trust, this measure—as constructed—has the potential to adversely impact resident-provider relationships, trust, and provider performance.

Response: We do not anticipate issues with resident access to SNF care if this measure is adopted. Use or adoption of other vaccination measures in PAC settings have not previously impacted access to care. Additionally, SNFs have been required to “educate and offer” COVID–19 vaccine to residents, clients, and staff, and report COVID–19 vaccination status to the CDC's NHSN, on a weekly basis, since May 13, 2021. More recently, we finalized certain infection control requirements at § 483.80(d) that SNFs and LTC facilities must meet to participate in the Medicare and Medicaid programs. As finalized in the “Medicare and Medicaid Programs; Policy and Regulatory Changes to the Omnibus COVID–19 Health Care Staff Vaccination Requirements; Additional Policy and Regulatory Changes to the Requirements for Long-Term Care (LTC) Facilities and Intermediate Care Facilities for Individuals with Intellectual Disabilities (ICFs-IID) to Provide COVID–19 Vaccine Education and Offer Vaccinations to Residents, Clients, and Staff; Policy and Regulatory Changes to the Long Term Care Facility COVID–19 Testing Requirements” (88 FR 36491 to 36492), SNFs must continue to educate residents, resident representatives, and staff about COVID–19 vaccines and offer a COVID–19 vaccine to residents, resident representatives, and staff, as well as complete the appropriate documentation for these activities. Since the information captured by the Patient/Resident COVID–19 Vaccine measure is consistent with these activities a SNF is already required to perform to meet 42 CFR 483.80(d)(3)(iii) through (vi), we believe SNFs are having those discussions with their residents every day, and the adoption of this measure should not have adverse impacts on resident-provider relationships.

We believe SNFs consider resident care of paramount importance and will not refuse care to residents based on their vaccination status. We also believe SNFs should use clinical judgement to determine if a resident is eligible to receive the vaccination. Lastly, we take the appropriate access to care in SNFs very seriously, and routinely monitor the performance of measures in the SNF QRP, including performance gaps across SNFs. We intend to monitor closely whether any proposed change to the SNF QRP has unintended consequences on access to care. Should we find any unintended consequences, we will take appropriate steps to address these issues in future rulemaking.

Comment: Several commenters were concerned regarding the lack of a well-defined definition of up to date, and the burden it poses on SNFs to collect these data from residents due to the constantly changing guidelines. One commenter characterized it as a “moving-target” definition, and another commenter noted that the CDC maintains different definitions of “up to date” and “fully vaccinated.” This commenter states that the public has a limited appreciation for the differences in these definitions and could easily misreport their vaccination status to facility staff when asked, giving the public a misleading picture of the vaccination levels of a SNF's resident population. Another commenter noted that it was unclear whether most residents would have an understanding of the CDC's specific definition of “up to date” when answering a yes/no question for the resident assessment, leading to potentially inaccurate data.

Response: The concept of up to date is not new and is currently in use by SNFs for the short stay and long stay Percent of Residents Assessed and Appropriately Given the Pneumococcal Vaccine and Percent of Residents Who Received the Pneumococcal Vaccine measures. Beyond the historical use of this concept, ensuring that standards of care are up to date according to the relevant authorities remains a widespread goal for all SNFs. We believe that SNFs should be staying current on the latest care guidelines of COVID–19 vaccination as part of best practice. Additionally, SNFs would be able to use multiple sources of information available to obtain the vaccination data, such as resident interviews, medical records, proxy response, and vaccination cards provided by the resident or their caregivers. Gathering this information gives the SNF the opportunity to educate residents about what it means to be up to date per CDC guidelines, so that the item can be completed accurately. Further, the MDS Resident Assessment Instrument (RAI) Guidance Manual will indicate how to code the item and SNFs could access the CDC website at any time to find the definition of up to date. The CDC has published FAQs that clearly state the difference in the terms “fully vaccinated” and “up to date.” Finally, as described in section VII.C.2.b.(1)(b) of this final rule, our item testing demonstrated strong agreement with the correct responses when facilities used the available guidance, and rates increased when facilities accessed the CDC website.

Comment: One commenter noted that given the various lengths of stay for residents, residents may be up to date one month and then with additional boosters and evidence on the horizon, they would move to being not up to date.

Response: Given this assessment item is completed at discharge, SNFs would only code the item using guidance in place at the time of resident discharge.

Comment: One commenter raised concerns about the evolving recommendation landscape from FDA and CDC as well as lack of full authorization from FDA for bivalent vaccines. They stated expert advisory groups will meet in June 2023 to provide additional recommendations to the agencies and to the public and encouraged CMS to delay measure amendment or adoption until future years when greater clarity from experts and other agencies is available. Another commenter was concerned about the uncertainty about the seasonality of COVID–19, future vaccination schedules, and how often new versions of a COVID–19 vaccine will be available.

Response: We disagree with the commenter and do not believe the evolving landscape and recommendations will affect this measure negatively. We recognize that the up to date COVID–19 vaccination definition may evolve due to the changing nature of the virus. As the COVID–19 virus mutates, this vaccination measure takes a forward-thinking approach to ensure that SNF residents are protected in the event of COVID–19 infection. Given that CDC guidelines may change over time in response to the virus, we believe the use of “up to date” will actually be simpler for facilities since it ensures that the measure specifications, item responses, and accompanying item guidance would not have to continually change. The public health response to COVID–19 has necessarily adapted to respond to the changing nature of the virus's transmission and community spread. Just as we stated when we finalized the adoption of the HCP COVID–19 Vaccine measure in the FY 2022 SNF PPS final rule (86 FR 42481), we intend to continue to work with partners including FDA and CDC to consider any updates to the Patient/Resident COVID–19 Vaccine measure in future rulemaking as appropriate. We believe that the proposed measure aligns with our responsive approach to COVID–19 and will continue to support vaccination as the most effective means to prevent the worst consequences of COVID–19, including severe illness, hospitalization, and death. Additionally, FDA recently authorized the bivalent vaccine to be used for all doses administered to individuals 6 months of age and older, including for an additional dose or doses for certain populations. Lastly, we regularly review our measures as part of the measure maintenance process and welcome feedback and expert input on our measures, and will re-specify the measure in the future, if needed, based on any changes to guidelines.

Comment: Several commenters did not support the measure due to the lack of exclusions in the measure for reasons such as medical contraindications, religious beliefs, cultural norms, and resident refusals. Some commenters encouraged CMS to consider the MAP's recommendations to add exclusions to the measure calculation. One commenter suggested CMS include a follow-up question to learn why the vaccine is not up to date, like MDS item O0300B for the pneumococcal vaccine, with three response options: “Not eligible—medical contraindication,” “Offered and declined,” and “Not offered.”

Response: We thank the commenters for their recommendations about adding exclusions to the measure. Our measure development contractor convened a focus group of PFAs as well as a TEP that included interested parties from every PAC setting, to solicit input on patient/resident COVID–19 vaccination measures and assessment items. The PFAs told us that a measure capturing raw vaccination rates would be most helpful in resident and family/caregiver decision-making. Our TEP agreed that developing a measure to report the rate of vaccination without denominator exclusions was an important goal. ²¹⁸ Based on this feedback, we believe excluding patients/residents with contraindications from the measure would distort the intent of the measure of providing raw COVID–19 resident vaccination rates, while making the information more difficult for residents/caregivers to interpret, and hence did not include any exclusions.

Comment: Some commenters did not support adoption of this measure in light of the Administration's announcement of the end of the COVID–19 PHE on May 11, 2023. One of these commenters noted that it will be even more challenging for residents to stay informed on the most recent guidance from the CDC. Another one of these commenters noted that with the end of the PHE and the end of the Federal vaccination mandates, CMS should eliminate any tracking of vaccines. Finally, one of these commenters commended CMS for recognizing the burden of such a requirement included in the SNF Conditions of Participation and working to remove it, but now questions the “juxtaposition” of proposing a vaccine uptake measure as a metric for quality of care.

Response: Despite the announcement of the end of the COVID–19 PHE, many people continue to be affected by COVID–19, particularly seniors, people who are immunocompromised, and people with disabilities. As mentioned in the End of COVID–9 Public Health Emergency Fact Sheet, our response to the spread of SARS–CoV–2, the virus that causes COVID–19, remains a public health priority. Even beyond the end of the COVID–19 PHE, we will continue to work to protect Americans from the virus and its worst impacts by supporting access to COVID–19 vaccines, treatments, and tests, including for people without health insurance. Given the continued impacts of COVID–19, we believe it is important to promote resident vaccination and education, which this measure aims to achieve. Accordingly, we are aligning our approach with those for other infectious diseases, such as influenza by encouraging ongoing COVID–19 vaccination. Further, published coding guidance will indicate how to code the item taking into account CDC guidelines, and SNFs could access the CDC website at any time to find the definition of up to date. Lastly, this measure as proposed for the SNF QRP is not associated with the PHE declaration, or the Conditions of Participation. This measure is being proposed to address our priority to empower consumers to make informed health care choices through resident-directed quality measures and public transparency, as with previous vaccination measures.

Comment: One commenter did not support the measure for the SNF QRP because residents entering a Medicare Part A SNF stay have had an acute care stay and they believe the hospital has already determined the person's interest in receiving the COVID–19 vaccine.

Response: We believe that COVID–19 vaccination for high-risk populations, such as those in SNF settings, is of paramount importance. This is particularly important for residents at SNFs, who tend to be older and thus more vulnerable to serious complications from COVID–19. Therefore, if a resident is not vaccinated at the time they are admitted, the SNF has the opportunity to continue to educate the resident and provide information on why they should receive the vaccine, irrespective of whether the resident has received prior education.

Comment: Some commenters provided alternate recommendations for a measure of a SNF's action, such as a count of the number of documented encounters facility staff had with a resident and/or their family concerning the COVID–19 vaccine, or a process measure that collects data on vaccines that are offered to residents in SNFs that are eligible for boosters. One commenter recommended a “balancing measure” which would track whether a SNF recommended the resident become up to date with their COVID–19 vaccine as opposed to tracking whether the resident accepted and received a COVID–19 vaccine.

Response: We appreciate the input from the commenters. We did not propose a measure of SNF action related to the measure but will use this input to inform our future measure development efforts.

After consideration of the public comments we received, we are finalizing our proposal to adopt the Patient/Resident COVID–19 Vaccine measure as an assessment-based measure beginning with the FY 2026 SNF QRP as proposed.

D. Principles for Selecting and Prioritizing SNF QRP Quality Measures and Concepts Under Consideration for Future Years—Request for Information (RFI)

1. Solicitation of Comments

We solicited general comments on the principles for identifying SNF QRP measures, as well as additional thoughts about measurement gaps, and suitable measures for filling these gaps. Specifically, we solicited comment on the following questions:

• Principles for Selecting and Prioritizing QRP Measures

++ To what extent do you agree with the principles for selecting and prioritizing measures?

++ Are there principles that you believe CMS should eliminate from the measure selection criteria?

++ Are there principles that you believe CMS should add to the measure selection criteria?

• SNF QRP Measurement Gaps

++ We requested input on the identified measurement gaps, including in the areas of cognitive function, behavioral and mental health, resident experience and resident satisfaction, chronic conditions and pain management.

++ Are there gaps in the SNF QRP measures that have not been identified in this RFI?

• Measures and Measure Concepts Recommended for Use in the SNF QRP.

++ Are there measures that you believe are either currently available for use, or that could be adapted or developed for use in the SNF QRP program to assess performance in the areas of (1) cognitive functioning, (2) behavioral and mental health, (3) resident experience and resident satisfaction, (4) chronic conditions, (5) pain management, or (6) other areas not mentioned in this RFI?

We also sought input on data available to develop measures, approaches for data collection, perceived challenges or barriers, and approaches for addressing challenges. We received several comments in response to this RFI, which are summarized below.

Comments on Principles for Selecting and Prioritizing QRP Measures: Many commenters expressed support for the measure selection and prioritization criteria identified by CMS in the FY 2024 SNF PPS proposed rule (88 FR 21353), as well as those espoused through the National Quality Strategy and the “Universal Foundation” of quality measures. In addition to support for these principles, commenters emphasized the importance of prioritizing measures that are meaningful to residents and their caregivers; support shared decision-making; promote continuity or consistency across a range of accountability programs; are constructed from data that are clearly defined, validated, and standardized; for which the SNF is able to influence outcomes; and are consensus-based.

A couple of commenters expressed appreciation for CMS' interest in adopting quality measures that do not impose undue administrative or financial burden on SNFs. These commenters urged that, when considering whether to adopt a measure, CMS assess SNF (including rural SNF) costs in terms of time, money, and staff resources.

Many commenters suggested principles that relate to the types of data that are used in measure construction. For instance, one commenter recommended that measures that are incorporated into the SNF QRP emphasize resident-reported outcomes. Other commenters recommended that measures not be based on facility self-reported data, such as the MDS, due to concerns about data accuracy and completeness. Some commenters recommended that CMS focus on data sources considered to be more objective, such as claims-based measures, the Payroll Based Journal (PBJ), and State surveys. One commenter emphasized the importance of ensuring that regardless of the assessment tool used, requirements for staff training, certification, and interim certification are met.

Comments on Principles for Selecting and Prioritizing QRP Measures and Measures and Measure Concepts Recommended for Use in the SNF QRP: Several commenters agreed with CMS that SNF QRP measurement gaps exist in domains that include cognitive function, behavioral and mental health, resident experiences of care and satisfaction, and chronic condition and pain management.

Cognitive Function

Although several commenters noted the importance of developing quality measures that focus on cognitive function, one commenter suggested caution in selecting measures of cognitive functioning. According to this commenter, SNFs have limited ability to meaningfully influence cognitive functioning during a typical SNF stay.

One commenter indicated that despite the usefulness of a cognitive function measure, the MDS is one of the only available data sources to develop this measure which, according to the commenter, is neither reliable nor accurate.

A few commenters voiced concerns about the use of the BIMS and CAM^© in measure development. Some commenters indicated that the BIMS, for example, was designed to screen for the presence of cognitive impairment and determine residents' need for further cognitive assessment. Commenters noted that the BIMS was not intended to diagnose or track changes in cognition; and it only effectively assesses basic elements of cognition (for example, attention, short-term memory), rather than executive functioning, judgment, and other higher-level cognitive functions. One commenter also stated that the constructs that are measured by the BIMS are not those that are the typical focus of therapy.

Other concerns about the BIMS or CAM^© for use in development of measures of cognitive functioning included the lack of physician buy-in, variation in the reliability of scoring, and limited utility of the BIMS for measuring and risk adjusting resident cognition and communication.

A commenter indicated that instruments identified in the FY 2024 SNF PPS proposed rule (88 FR 21353 to 21354) RFI (for example, PROMIS Cognitive Function Short Form) are not utilized by many SNFs. Because therapy practitioners are more familiar with the BIMS and CAM^© than with other cognitive function instruments mentioned in the RFI—the PROMIS short forms and the PROMIS Neuro-QoL—the commenter thought that use of PROMIS measures would present a greater burden to SNFs. This commenter further indicated that the PROMIS tools were developed for use in broad populations or to measure specific cognitive functions and, as such, would not readily translate to a SNF QRP measure. The commenter recommended that CMS perform feasibility, reliability, and validity testing to ensure that QRP measures could be effectively developed from these instruments.

Commenters encouraged CMS to collaborate with SNFs and experts in cognition to assess and consider other measures that not only offer information on a broad set of elements related to cognitive function but could also be used to assess change in cognitive abilities throughout the course of the SNF episode. One commenter indicated that the proprietary nature of many instruments that assess cognitive functioning could be a challenge for measure development.

Behavioral and Mental Health

A few commenters agreed with CMS that measurement gaps exist in the areas of behavioral and mental health. One commenter indicated that although a measure of behavioral and mental health would be useful, the MDS is one of the only available data sources that could be used to develop this measure. The commenter questioned the accuracy and reliability of the MDS.

One commenter noted that because occupational therapists have a key role in addressing residents' behavioral and mental health needs, that they need to be included in quality measures in this area. Another commenter suggested caution in selecting measures of behavioral and mental health functioning, indicating that SNFs are not specialized in treating behavioral and mental health issues.

Resident Experience and Resident Satisfaction

One commenter expressed support for the use of the CAHPS measure to measure resident experience and satisfaction but cautioned that an independent contractor should be used to identify the resident sample—rather than having SNFs identify this sample—and CMS should ensure that the survey sample mirrors the SNF population using a random sample process.

Chronic Condition and Pain Management

One commenter acknowledged the importance of measures of chronic condition and pain management. However, they did not support development of measures in this area as they believed the MDS to be inaccurate and subject to gaming by nursing facilities.

Other Measurement Gaps

Some commenters believed measurement gaps do exist in domains not identified in the RFI. Noting the importance of good nutrition in reducing readmissions and increasing SNF resident quality of life, two commenters recommended the inclusion of a malnutrition screening and intervention measures in the SNF QRP to promote both quality and health equity. These commenters suggested that malnutrition-related quality measures that CMS has adopted in other quality programs be considered as the foundation for a SNF QRP malnutrition measure. These include the Global Composite Malnutrition Score which will be used in the Hospital Inpatient Quality Reporting program beginning in 2024, and the Food Insecurity/Nutrition Risk Identification and Treatment Improvement Activity that is part of the Merit-based Incentive Payment System.

Another commenter recommended the adoption of structural measures that indicate hours of service provided by physicians, social workers, and therapists to ensure that residents receive needed services. The commenter supported the use of data from the CMS PBJ to develop these measures.

Commenters expressed support for the development of measures focused on degenerative cognitive conditions, for which maintenance of function is the primary focus. One commenter suggested consideration of a measure related to residents' ability to safely and effectively return to the community.

Other measures and measurement concepts identified by commenters include health equity, psychosocial issues, caregiver status (for example, availability of caregiver), receipt of or referral for smoking cessation counseling among residents with COPD, referrals to pulmonary rehabilitation for residents with COPD, and resident vaccination status, including adult Td/Tdap (tetanus, diphtheria, and pertussis) and herpes zoster (shingles) vaccinations.

Response: We appreciate the input provided by commenters. While we will not be responding to specific comments submitted in response to this RFI in this final rule, we intend to use this input to inform our future measure development efforts.

E. Health Equity Update

1. Background

In the FY 2023 SNF PPS proposed rule (87 FR 22754 through 22760), we included an RFI entitled “Overarching Principles for Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs.” We define health equity as “the attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes.” We are working to advance health equity by designing, implementing, and operationalizing policies and programs that support health for all the people served by our programs and models, eliminating avoidable differences in health outcomes experienced by people who are disadvantaged or underserved, and providing the care and support that our beneficiaries need to thrive. Our goals outlined in the CMS Framework for Health Equity 2022–2023 are in line with Executive Order 13985, “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government.” The goals included in the CMS Framework for Health Equity serve to further advance health equity, expand coverage, and improve health outcomes for the more than 170 million individuals supported by our programs, and set a foundation and priorities for our work, including: strengthening our infrastructure for assessment; creating synergies across the healthcare system to drive structural change; and identifying and working to eliminate barriers to CMS-supported benefits, services, and coverage. The CMS Framework for Health Equity outlines the approach CMS will use to promote health equity for enrollees, mitigate health disparities, and prioritize CMS's commitment to expanding the collection, reporting, and analysis of standardized data.

In addition to the CMS Framework for Health Equity, we seek to advance health equity and whole-person care as one of eight goals comprising the CMS National Quality Strategy (NQS). The NQS identifies a wide range of potential quality levers that can support our advancement of equity, including: (1) establishing a standardized approach for resident-reported data and stratification; (2) employing quality and value-based programs to address closing equity gaps; and (3) developing equity-focused data collections, analysis, regulations, oversight strategies, and quality improvement initiatives.

A goal of the NQS is to address persistent disparities that underlie our healthcare system. Racial disparities in health, in particular, are estimated to cost the U.S. $93 billion in excess medical costs and $42 billion in lost productivity per year, in addition to economic losses due to premature deaths. At the same time, racial and ethnic diversity has increased in recent years with an increase in the percentage of people who identify as two or more races accounting for most of the change, rising from 2.9 percent to 10.2 percent between 2010 and 2020. Therefore, we need to consider ways to reduce disparities, achieve equity, and support our diverse beneficiary population through the way we measure quality and display the data.

We solicited public comments via the aforementioned RFI on changes that we should consider in order to advance health equity. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47553 through 47555) for a summary of the public comments and suggestions we received in response to the health equity RFI. In the proposed rule, we stated that we would take these comments into account as we continue to work to develop policies, quality measures, and measurement strategies on this important topic.

2. Anticipated Future State

We are committed to developing approaches to meaningfully incorporate the advancement of health equity into the SNF QRP. One option we are considering is including social determinants of health (SDOH) as part of new quality measures.

Social determinants of health are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks. They may have a stronger influence on the population's health and well-being than services delivered by practitioners and healthcare delivery organizations. Measure stratification by CMS is important for better understanding differences in health outcomes from across different patient population groups according to specific demographic and SDOH variables. For example, when “pediatric measures over the past two decades are stratified by race, ethnicity, and income, they show that outcomes for children in the lowest income households and for Black and Hispanic children have improved faster than outcomes for children in the highest income households or for White children, thus narrowing an important health disparity.” This analysis and comparison of the SDOH items in the assessment instruments support our desire to understand the benefits of measure stratification. Hospital providers receive such information in their confidential feedback reports, and we believe this learning opportunity would benefit PAC providers. The goal of the confidential feedback reports is to provide SNFs with their results so they can compare certain quality measures stratified by dual eligible status and race and ethnicity. The process is meant to increase provider's awareness of their data. We will solicit feedback from SNFs for future enhancements to the confidential feedback reports.

In the proposed rule, we stated that we are considering whether health equity measures we have adopted for other settings, such as hospitals, could be adopted in PAC settings. We stated that we are exploring ways to incorporate SDOH elements into the measure specifications. For example, we could consider a future health equity measure like screening for social needs and interventions using our current SDOH Data items of preferred language, interpreter services, health literacy, transportation, and social isolation. With 30 percent to 55 percent of health outcomes attributed to SDOH, a measure capturing and addressing SDOH could encourage SNFs to identify residents' specific needs and connect them with the community resources necessary to overcome social barriers to their wellness. We could specify a health equity measure using the same SDOH data items that we currently collect as standardized patient assessment data elements under the SNF. These SDOH data items assess health literacy, social isolation, transportation problems, and preferred language (including need or want of an interpreter). We also see value in aligning SDOH data items according to existing health IT vocabulary and codes sets where applicable and appropriate such as those included in the Office of the National Coordinator for Health Information (ONC) United States Core Data for Interoperability (USCDI) across all care settings as we develop future health equity quality measures under our SNF QRP statutory authority. This would further the goals of the NQS to align quality measures across our programs as part of the Universal Foundation.

Although we did not directly solicit feedback to our update, we did receive some public comments, which we summarize later in this section.

Comment: Commenters were generally supportive of CMS' efforts to develop ways to measure and mitigate health inequities. Four commenters applauded CMS' continuing efforts to advance health equity and encouraged CMS to continue to develop and adopt measures of SDOH into the SNF QRP. One of these commenters referenced their belief that collection of SDOH will enhance holistic care, call attention to impairments that might be mitigated or resolved, and facilitate clear communication between residents and SNFs. Another commenter shared strategies they are using with their member organizations to assess organizational leadership's commitment to identify and address health equity, as well as evaluating the impact of health equity on care delivery.

We also received comments supporting measure stratification and adoption of screening measures in the SNF QRP. One commenter noted the importance of stratification to understanding the differences in outcomes across different groups. Some commenters suggested CMS incorporate screening measures similar to those adopted in the FY 2023 Inpatient Prospective Payment System (IPPS) final rule for the Hospital Inpatient Quality Reporting Program.

We also received feedback on other ways to incorporate health equity into the SNF QRP. One commenter recommended CMS incorporate workforce equity measures into the SNF QRP, suggesting that workforce factors are related to a worker's ability to provide quality care. We received some comments on other data points that may be useful in identifying and addressing health disparities. One commenter noted that while it is important to still try to understand differences by race and ethnicity to identify and address disparities that might root from racism and social/economic inequities, they recommended against making generalizations about differences in health and health care simply based on race and ethnicity and to instead conduct more in-depth evaluations of underlying social and economic drivers of health. This commenter suggested CMS incentivize the collection and analysis of data on factors such as, but not limited to, disability status, veteran status, primary or preferred language, health literacy, food security, transportation access, housing stability, social support after discharge from a SNF, and a person's access to care. This same commenter, however, pointed out that any program must account for the fact that there are many contributors to health inequities, including personal factors, many of which are outside the control of SNFs. They encouraged CMS to have ongoing engagement from interested parties to best understand structural and socioeconomic barriers to health and to monitor for any unintended consequences. Finally, this commenter urged CMS to focus on improving care coordination as residents move between settings.

One commenter recommended CMS consider including SDOH in new quality measures and in SNF payment and suggested it could be accomplished through the use of ICD–10 Z-codes as indicators of the additional resources required to care for residents. There were also several commenters who urged CMS to balance any reporting requirements so as not to create an undue administrative burden on clinicians. One of these commenters noted that quantifying health care disparities and barriers faced by residents is extremely nuanced due to the sensitive nature of this issue, and an overly burdensome reporting approach may impact the critical relationship between the SNF and resident.

One commenter was critical of our efforts to meaningfully incorporate the advancement of health equity into the SNF QRP, noting that it disregards a person's behavior and accountability for their own health. This commenter raised a concern that these efforts presuppose systemic bias on the part of the healthcare system or bigotry on the part of medical providers, or that medical providers' bias is responsible for differences in the health outcomes among demographic minority groups. This commenter also cautioned CMS against expecting providers to view treatments through the lens of race, as it could result in allocating resources to one group at the expense of another.

Finally, one commenter suggested that the abbreviated term for “social determinants of health” was incorrect, believing it should be SDoH.

Response: We thank all the commenters for responding to our update on this important CMS priority. When abbreviating “social determinants of health,” we consistently use SDOH across our agencies and programs. We also want to be transparent about our efforts to provide SNFs with information that they find beneficial as they seek to improve clinical outcomes for all SNF residents and are not intended to be critical of any health system or provider. As we stated in the FY 2024 SNF PPS proposed rule (88 FR 21355–21356), our goals outlined in the CMS Framework for Health Equity 2022–2023 are in line with Executive Order 13985, “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government.” We will continue to prioritize our efforts to advance health equity by designing, implementing, and operationalizing policies and programs that support health for all people served by our program. As we move this important work forward, we will take these comments into account as we work to develop policies, quality measures, and measurement strategies.

F. Form, Manner, and Timing of Data Submission Under the SNF QRP

1. Background

We refer readers to the current regulatory text at § 413.360(b) for information regarding the policies for reporting SNF QRP data.

2. Reporting Schedule for the Minimum Data Set (MDS) Assessment Data for the Discharge Function Score Measure Beginning With the FY 2025 SNF QRP

As discussed in section VI.C.1.b. of the FY 2024 SNF PPS proposed rule, we proposed to adopt the DC Function measure beginning with the FY 2025 SNF QRP. We proposed that SNFs would be required to report these MDS assessment data beginning with residents admitted and discharged on October 1, 2023 for purposes of the FY 2025 SNF QRP. Starting in CY 2024, SNFs would be required to submit data for the entire calendar year beginning with the FY 2026 SNF QRP. Because the DC Function measure is calculated based on data that are currently submitted to the Medicare program, there would be no new burden associated with data collection for this measure.

We solicited public comment on this proposal. We did not receive public comments on this proposed schedule for data submission of the DC Function measure beginning with the FY 2025 SNF QRP, and therefore, we are finalizing as proposed.

3. Method of Data Submission and Reporting Schedule for the CoreQ: Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP

a. Method of Data Submission To Meet SNF QRP Requirements Beginning With the FY 2026 Program Year

As discussed in section VII.C.2.a. of this final rule, we proposed to adopt the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. In the FY 2024 SNF PPS proposed rule (88 FR 21357), we proposed that Medicare-certified SNFs and all non-CAH swing bed rural hospitals would be required to contract with a third-party vendor that is CMS-trained and approved to administer the CoreQ: SS DC survey on their behalf (referred to as a “CMS-approved CoreQ survey vendor”). Under this proposal, SNFs would have been required to contract with a CMS-approved CoreQ survey vendor to ensure that the data are collected by an independent organization that is trained to collect this type of data and given the independence of the CMS-approved CoreQ survey vendor from the SNF, ensure that the data collected are unbiased. The CMS-approved CoreQ survey vendor would have been the business associate of the SNF and required to follow the minimum business requirements described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. This method of data collection has been used successfully in other settings, including for Medicare-certified home health agencies and hospices.

As described in the FY 2024 SNF PPS proposed rule (88 FR 21357), it was proposed that CMS-approved CoreQ survey vendors administering the CoreQ: SS DC survey would be required to offer a toll-free assistance line and an electronic mail address which respondents could use to seek help.

We also proposed in the FY 2024 SNF PPS proposed rule (88 FR 21357) to require SNFs to use the protocols and guidelines for the proposed CoreQ: SS DC measure as defined by the Draft CoreQ: SS Survey Protocols and Guidelines Manual in effect at the time the questionnaires are sent to eligible residents. The Draft CoreQ: SS DC Survey Protocols and Guidelines Manual is available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information. We also proposed that CMS-approved CoreQ survey vendors and SNFs be required to participate in CoreQ: SS DC measure oversight activities to ensure compliance with the protocols, guidelines, and questionnaire requirements. Additionally, we proposed that all CMS-approved CoreQ survey vendors develop a Quality Assurance Plan (QAP) for CoreQ: SS DC survey administration in accordance with the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.

At § 413.360, we also proposed redesignating paragraph (b)(2) as paragraph (b)(3) and add new paragraph (b)(2) for the CoreQ: SS DC measure's data submission requirements. Finally, we proposed to codify the requirements for being a CMS-approved CoreQ: SS DC survey vendor at paragraphs (b)(2)(ii) through (b)(2)(iii) in regulation. The proposed revisions are outlined in the FY 2024 SNF PPS proposed rule (88 FR 21422).

In the FY 2024 SNF PPS proposed rule (88 FR 21358), we proposed that SNFs would send a resident information file (RIF) to the CMS-approved CoreQ survey vendor on a weekly basis so the vendor can start administering the CoreQ: SS DC questionnaire within seven days after the reporting week closes. However, we received a significant number of comments expressing concern about the burden associated with weekly data submission.

We solicited public comment on this proposal to require Medicare-certified SNFs to contract with a third-party vendor to administer the CoreQ: SS DC measure questionnaire on their behalf beginning with the FY 2026 SNF QRP. We received comments that supported and opposed our proposal to require Medicare-certified SNFs to contract with a third-party vendor to administer the CoreQ: SS DC measure questionnaire on their behalf, but we will not be responding to these. As described in section VII.C.2.a.5.b of this final rule, we have decided that, at this time, we will not finalize the proposal to add the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. Therefore, we are not finalizing our proposal to require Medicare-certified SNFs to contract with a third-party vendor to administer the CoreQ: SS DC measure questionnaire on their behalf beginning with the FY 2026 SNF QRP.

b. Exemptions for the CoreQ: SS DC Measure Reporting Requirements Beginning With the FY 2026 Program Year

(1) Low Volume Exemptions

We are aware that there is a wide variation in the size of Medicare-certified SNFs. Therefore, we proposed that SNFs with less than 60 residents, regardless of payer, discharged within 100 days of SNF admission in the prior calendar year would be exempt from the CoreQ: SS DC measure data collection and reporting requirements. A SNF's total number of short-stay discharged residents for the period of January 1 through December 31 for a given year would have been used to determine if the SNF would have to participate in the CoreQ: SS DC measure in the next calendar year. To qualify for the exemptions, SNFs would have been required to submit their request using the Participation Exemption Request form no later than December 31 of the CY prior to the reporting CY.

(2) New Provider Exemptions

We also proposed in the FY 2024 SNF PPS proposed rule (88 FR 21357 through 21358), that newly Medicare-certified SNFs (that is, those certified on or after January 1, 2024) be excluded from the CoreQ: SS DC measure reporting requirement for CY 2024, because there would be no information from the previous CY to determine whether the SNF would be required to report or exempt from reporting the CoreQ: SS DC measure.

In future years, we proposed requiring that SNFs certified for Medicare participation on or after January 1 of the reporting year would be excluded from reporting on the CoreQ: SS DC measure for the applicable SNF QRP program year.

We solicited public comment on this proposal to exempt SNFs with less than 60 residents, regardless of payer, discharged within 100 days of SNF admission in the prior calendar year, and to exempt newly Medicare-certified SNFs in their first-year of certification, from the CoreQ: SS DC measure reporting requirements for the applicable SNF QRP program year.

We received comments that supported and opposed our proposal to exempt SNFs with less than 60 residents, regardless of payer, discharged within 100 days of SNF admission in the prior calendar year, and to exempt newly Medicare-certified SNFs in their first year of certification from the CoreQ: SS DC measure reporting requirements for the applicable SNF QRP program year, but we will not be responding to these. As described in section VII.C.2.a.5.b of this final rule, we have decided that, at this time, we will not finalize the proposal to add the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. Therefore, we are not finalizing our proposal to exempt SNFs with less than 60 residents, regardless of payer, discharged within 100 days of SNF admission in the prior calendar year, and to exempt newly Medicare-certified SNFs in their first year of certification from the CoreQ: SS DC measure reporting requirements for the applicable SNF QRP program year.

c. Reporting Schedule for the Data Submission of the CoreQ: Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP

In the FY 2024 SNF PPS proposed rule (88 FR 21358 through 21360), we proposed that the CoreQ: SS DC measure questionnaire be a component of the SNF QRP for the FY 2026 SNF QRP and subsequent years. To comply with the SNF QRP reporting requirements for the FY 2026 SNF QRP, we proposed that SNFs would be required to collect data for the CoreQ: SS DC measure by utilizing CMS-approved CoreQ survey vendors in compliance with the proposed revisions outlined at § 413.360(b)(2)(i) through (b)(2)(iii) in the regulation text of the FY 2024 SNF PPS proposed rule.

For the CoreQ: SS DC measure, we proposed that SNFs would send a resident information file to the CMS-approved CoreQ survey vendor on a weekly basis so the CMS-approved CoreQ survey vendor could start administering the CoreQ: SS DC questionnaire within 7 days after the reporting week closes. The resident information file, whose data is listed in Table 14, represented the minimum required information the CMS-approved CoreQ survey vendor would need to determine the residents' eligibility for the CoreQ: SS DC measure's questionnaire to administer the survey to eligible residents.

For the CoreQ: SS DC measure, we proposed that SNFs would be required to meet or exceed two separate data completeness thresholds: (1) one threshold, set at 75 percent, for submission of weekly resident information files to the CMS-approved CoreQ survey vendor for the full reporting year; and (2) a second threshold, set at 90 percent, for completeness of the resident information files. In other words, as proposed, SNFs would have submitted resident information files on a weekly basis that included at least 90 percent of the required data fields to their CMS-approved CoreQ survey vendors for at least 75 percent of the weeks in a reporting year. SNFs could have chosen to submit resident information files more frequently but would have been required meet the minimum threshold to avoid receiving a 2-percentage-point reduction to their Annual Payment Update (APU). We also proposed to codify this data completeness threshold requirement at our regulation at § 413.360(f)(1)(iv) as described in the regulation text of the FY 2024 SNF PPS proposed rule.

We also proposed an initial data submission period from January 1, 2024, through June 30, 2024. As described in Table 15 in the FY 2024 SNF PPS proposed rule (88 FR 21359), we proposed that to meet the pay-for-reporting requirement of the SNF QRP for the first half of the FY 2026 program year, SNFs would only be required to contract with a CMS-approved CoreQ survey vendor and submit one resident information file to their CMS-approved CoreQ survey vendor for at least 1 week during January 1, 2024 through June 30, 2024. During this period, the CMS-approved CoreQ survey vendor would follow the procedures as described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. Beginning July 1, 2024, SNFs would have been required to submit weekly resident information files for at least 75 percent of the weeks remaining in CY 2024.

Starting in CY 2025, SNFs would be required to submit resident information files no less than weekly for the entire calendar year beginning with the FY 2027 SNF QRP, as described in Table 16 in the FY 2024 SNF PPS proposed rule (88 FR 21359).

We proposed that the CMS-approved CoreQ survey vendor administer the CoreQ: SS DC measure's questionnaire to discharged residents within 2 weeks of their discharge date through the U.S. Postal Service or by telephone. If administered by mail, the questionnaires must be returned to the CMS-approved CoreQ survey vendor within 2 months of the resident's discharge date from the SNF.

Although the CMS-approved CoreQ survey vendor would administer the CoreQ: SS DC measure's survey on a SNF's behalf, each SNF would have been responsible for ensuring required data are collected and submitted to CMS in accordance with the SNF QRP's requirements. We also recommended that SNFs submitting CoreQ: SS DC resident information files to their CMS-approved CoreQ survey vendor promptly review the Data Submission Summary Reports that are described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.

We solicited public comment on the proposed schedule for data submission and the participation requirements for the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. We received several comments on our proposed schedule for data submission and the participation requirements for the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP, but we will not be responding to these. As described in section VII.C.2.a.5.b of this final rule, we have decided that, at this time, we will not finalize the proposal to add the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. Therefore, we are not finalizing our proposed schedule for data submission and the participation requirements for the CoreQ: SS DC Measure beginning with the FY 2026 SNF QRP.

4. Reporting Schedule for the Data Submission of Minimum Data Set (MDS) Assessment Data for the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP

As discussed in section VI.C.2.b. of the FY 2024 SNF PPS proposed rule, we proposed to adopt the Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 SNF QRP. We proposed that SNFs would be required to report this new MDS assessment data item beginning with Medicare Part A residents discharged on October 1, 2024, for purposes of the FY 2026 SNF QRP. Starting in CY 2025, SNFs would be required to submit data for the entire calendar year beginning with the FY 2027 SNF QRP.

We also proposed to add a new item to the MDS for SNFs to report the proposed Patient/Resident COVID–19 Vaccine measure. Specifically, a new item would be added to the MDS discharge item sets to collect information on whether a resident is up to date with their COVID–19 vaccine at the time of discharge from the SNF. A draft of the new item is available in the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Draft Measure Specifications.

We solicited public comment on this proposal. The following is a summary of the comments we received on our proposal to require SNFs to report a new MDS assessment data item for the Patient/Resident COVID–19 Vaccine measure on Medicare Part A residents beginning with residents discharged on October 1, 2024 and our responses.

Comment: Several commenters raised concerns about the data collected using the assessment item on the MDS being duplicative of what is currently being reported to NHSN. They noted that this reporting adds additional burden on SNFs and could confuse residents looking for information. One commenter recommended that in order to remove burdensome duplication of reporting for the same process, CMS should issue a regulatory revision to the requirements promulgated through a prior COVID–19 IFC to end reporting of resident COVID–19 vaccination up to date status requirements through the NHSN no later than September 30, 2024.

Response: We acknowledge the commenters' concerns and thank them for their recommendations regarding the duplication of reporting resident COVID–19 vaccination status on the MDS and to NHSN. We will take the recommendations into consideration.

Comment: Some commenters noted their preference for the NHSN reported data, since it includes the entire nursing home population regardless of payer source and provides more valuable information, as opposed to this proposed SNF QRP measure which only reflects short-stay residents.

Response: While the data that SNFs report to the NHSN are aggregated resident vaccination data, SNF's are not required to report beneficiary-level data to the CDC's NHSN. However, since the proposed Patient/Resident COVID–19 Vaccine measure would be collected using an MDS assessment item at the resident-level, the data submitted would be included in the SNF's Review and Correct reports as well as the Quality Measure (QM) resident- and facility-level confidential feedback reports and would allow SNFs to track resident-level information for quality improvement purposes. These data would also allow for granular analyses of vaccinations, including identification of potential disparities within the SNF QRP.

Comment: A few commenters raised concerns about this measure being based on facility self-reported MDS data and its reliability. Commenters urged CMS to consider alternative data sources or implement auditing and penalty systems for inaccurate or falsified data, if an MDS assessment item was finalized as the source to collect this information. One commenter suggested that having a single yes or no item on the MDS without any requirements for documentation or validation of vaccination status would amount to a mere checkmark in a box with no evidence that it leads to improved quality of care.

Response: We acknowledge the commenters' concerns regarding the MDS data. However we note that the RAI process has multiple regulatory requirements. Our regulations at §§ 483.20(b)(1)(xviii), (g), and (h) require that (1) the assessment must be a comprehensive, accurate assessment of the resident's status, (2) the assessment must accurately reflect the resident's status, (3) a registered nurse and each individual who completes a portion of the assessment must sign and certify the assessment is completed, and (4) the assessment process includes direct observation, as well as communication with the resident.

We intend to monitor this measure closely to identify any concerning trends, and we will continue to do so as part of our routine monitoring activities to regularly assess measure performance, reliability, and reportability for all data submitted for the SNF QRP.

After consideration of the public comments we received, we are finalizing our proposal to require SNFs to report the new MDS assessment data item for the Patient/Resident COVID–19 Vaccine measure on Medicare Part A residents beginning with residents discharged on October 1, 2024 for the FY 2026 SNF QRP.

5. SNF QRP Data Completion Thresholds for MDS Data Items Beginning With the FY 2026 SNF QRP

In the FY 2016 SNF PPS final rule (80 FR 46458), we finalized that SNFs would need to complete 100 percent of the data on 80 percent of MDSs submitted in order to be in compliance with the SNF QRP reporting requirements for the applicable program year, as codified in regulation at § 413.360(f). We established this data completion threshold because SNFs were accustomed to submitting MDS assessments for other purposes and they should easily be able to meet this requirement for the SNF QRP. We also noted at that time our intent to raise the proposed 80 percent threshold in subsequent program years.

We proposed that, beginning with the FY 2026 SNF QRP, SNFs would be required to report 100 percent of the required quality measure data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments they submit through the CMS-designated submission system.

Complete data are needed to help ensure the validity and reliability of SNF QRP data items, including risk-adjustment models. The proposed threshold of 90 percent is based on the need for substantially complete records, which allows appropriate analysis of SNF QRP measure data for the purposes of updating quality measure specifications as they undergo yearly and triennial measure maintenance reviews with the CBE. Additionally, we want to ensure complete SNF QRP measure data from SNFs, which will ultimately be reported to the public, allowing our beneficiaries to gain a more complete understanding of SNF performance related to these metrics, helping them to make informed healthcare choices. Finally, the proposal would contribute to further alignment of data completion thresholds across the PAC settings.

We believe SNFs should be able to meet the proposed requirement for the SNF QRP. Our data suggest that the majority of SNFs are already in compliance with, or exceeding, the proposed threshold. The complete list of items required under the SNF QRP is updated annually and posted on the SNF QRP Measures and Technical Information page.

We proposed that SNFs would be required to comply with the proposed new data completion threshold beginning with the FY 2026 SNF QRP. Starting in CY 2024, SNFs would be required to report 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of all assessments submitted January 1 through December 31 for that calendar year's payment determination. Any SNF that does not meet the proposed requirement will be subject to a reduction of 2 percentage points to the applicable FY APU beginning with the FY 2026 SNF QRP. We proposed to update § 413.360(f) of our regulations to reflect this new policy, as well as to clarify and make non-substantive edits to improve clarity of the regulation.

We solicited public comment on the proposed schedule for the increase of SNF QRP data completion thresholds for the MDS data items beginning with the FY 2026 program year. The following is a summary of the comments we received and our responses.

Comment: A number of commenters opposed our proposal to increase the SNF QRP data completion thresholds for MDS data items beginning with the FY 2026 SNF QRP because they believe SNFs need more time to adjust to the collection of the new standardized patient assessment data elements that begins October 1, 2023. These commenters do not believe that 3 months is adequate time for SNFs to adjust to the new data elements. One of these commenters noted that the proposed increase in the data completion threshold comes at a time when CMS is significantly expanding the MDS 3.0, and there is additional health IT programming that will need to be done to accommodate these data as well. One of these commenters suggested that CMS apply the higher 90 percent threshold only to the current required data elements and implement a 75 percent threshold for the new standardized patient assessment data element.

Response: We acknowledge the commenters' concerns, but as we stated in the SNF PPS proposed rule, our data suggest that the majority of SNFs are already in compliance with, or exceeding, this proposed threshold. As the commenters noted, SNFs will begin collecting new standardized patient assessment data elements beginning October 1, 2023. However, many of these items are not “new” to SNFs. SNFs have been collecting the Brief Interview for Mental Status (BIMS), Confusion Assessment Method (CAM©), the Patient Health Questionnaire (PHQ), some of the Nutritional Approaches, and even some of the Special Treatments, Procedures, and Programs for several years, but they have not counted toward the SNF's data completion threshold for the SNF QRP. We also want to note that three of the new items have a response option (“None of the above”) that SNFs can select for residents who are not receiving special nutritional approaches, high-risk drug classes, and special treatments, procedures, and programs. When “None of the above” is selected, 46 of the items are eliminated and SNFs do not have to complete them. To support SNFs, we have already begun to provide extensive education and training opportunities on the standardized patient assessment data elements for SNFs, and will continue to do so, in addition to answering all questions through our SNF QRP Helpdesk.

We also do not believe it would be appropriate to implement a lower threshold for the new standardized patient assessment data elements. As noted earlier, many of these items are not “new” to SNFs, even though they did not count towards the SNF's data completion threshold for the SNF QRP. We must maintain our commitment to the quality of care for all residents, and we continue to believe that the collection of the standardized patient assessment data elements and TOH Information measures will contribute to this effort. We note that in response to the “Request for Information to Close the Health Equity Gap” in the FY 2022 SNF PPS proposed rule (86 FR 20000), we heard from interested parties that it is important to gather additional information about race, ethnicity, gender, language, and other SDOH, and some SNFs noted they had already begun to collect some of this information for use in their operations. We believe capturing complete information on these new items is equally important and therefore do not plan to implement a lower threshold for these items.

Comment: One commenter noted it would place additional burden on the important role of the Nurse Assessment Coordinators at a time when they are already in short supply. Another suggested that because SNF residents are often extremely sick, there are often situations outside of the facility's control that may prevent them from being able to complete an MDS in its entirety. Another commenter echoed that point and added that for facilities that serve larger proportions of complex and/or acutely ill residents, these cases are more frequent, and that 20 percent buffer is necessary. This commenter also added that CMS rationale for increasing the data completion threshold—that is, that the majority of SNFs already meet or exceed the 90 percent threshold—is moot since these SNFs clearly do not need the motivation of a higher threshold to report a larger proportion of complete assessments.

Response: While we acknowledge the impacts of the COVID–19 PHE on the healthcare system, including staffing shortages, it also makes it especially important now to monitor quality of care. Still, we are mindful of burden that may occur from the collection and reporting of our measures. We emphasize, however, that several of the standardized patient assessment data elements reflect activities that align with the existing Requirements of Participation for SNFs. As a result, the information gathered will reflect a process that SNFs should already be conducting and will demonstrate the quality of care provided by SNFs. Additionally, for each of the items, the MDS RAI manual provides instructions for how to code the items if the item does not apply to the resident or the resident is unable to respond. Selecting these responses when applicable counts toward the data completion threshold. Additionally, the assessments of the special services, treatments, and interventions with multiple responses are formatted as a “check all that apply” format. Therefore, when treatments do not apply, the assessor need only check one row for “None of the Above,” and the data completion requirement is met, and when a resident has to leave emergently, the resident interview questions are not required.

Finally, we do not believe that shortages in staffing will affect implementation of the new MDS because many of the data elements adopted as standardized patient assessment data elements in the FY 2020 SNF PPS final rule are already collected on the MDS 1.17.2 using current SNF staffing levels. Therefore, MDS 1.18.11 results in fewer “new” standardized patient assessment data elements for SNFs, as compared to other PAC settings.

Comment: One commenter noted that starting with FY 2026, if finalized, SNFs will have additional reporting requirements for weekly submissions to the approved vendor for the CoreQ: SS Discharge measure. This commenter suggested that delaying the threshold increase would allow time to analyze whether the increase in data elements significantly impacts the SNF's ability to maintain compliance with the QRP requirements.

Response: As described in section VII.C.2.a.(5)(b) of this final rule, we have decided at this time, not to finalize the proposal to add the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP.

After consideration of the public comments we received, we are finalizing our proposal to require SNFs to report 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of all assessments submitted beginning with the FY 2026 SNF QRP as proposed.

G. Policies Regarding Public Display of Measure Data for the SNF QRP

1. Background

Section 1899B(g) of the Act requires the Secretary to establish procedures for making the SNF QRP data available to the public, including the performance of individual SNFs, after ensuring that SNFs have the opportunity to review their data prior to public display. For a more detailed discussion about our policies regarding public display of SNF QRP measure data and procedures for the SNF's opportunity to review and correct data and information, we refer readers to the FY 2017 SNF PPS final rule (81 FR 52045 through 52048).

2. Public Reporting of the Transfer of Health Information to the Provider—Post-Acute Care Measure and Transfer of Health Information to the Patient—Post-Acute Care Measure Beginning With the FY 2025 SNF QRP

We proposed to begin publicly displaying data for the measures: (1) Transfer of Health (TOH) Information to the Provider—Post-Acute Care (PAC) Measure (TOH-Provider); and (2) TOH Information to the Patient—PAC Measure (TOH-Patient) beginning with the October 2025 Care Compare refresh or as soon as technically feasible.

We adopted these measures in the FY 2020 SNF PPS final rule (84 FR 38761 through 38764). In response to the COVID–19 PHE, we released an Interim Final Rule (85 FR 27595 through 27597) which delayed the compliance date for collection and reporting of the TOH-Provider and TOH-Patient measures to October 1 of the year that is at least 2 full fiscal years after the end of the COVID–19 PHE. Subsequently, in the FY 2023 SNF PPS final rule (87 FR 47502), the compliance date for the collection and reporting of the TOH-Provider and TOH-Patient measures was revised to October 1, 2023. Data collection for these two assessment-based measures will begin with residents discharged on or after October 1, 2023.

We proposed to publicly display data for these two assessment-based measures based on four rolling quarters of data, initially using discharges from January 1, 2024, through December 31, 2024 (Quarter 1 2024 through Quarter 4 2024), and to begin publicly reporting these measures with the October 2025 refresh of Care Compare, or as soon as technically feasible. To ensure the statistical reliability of the data, we proposed that we would not publicly report a SNF's performance on a measure if the SNF had fewer than 20 eligible cases in any four consecutive rolling quarters for that measure. SNFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/resident stays is too small to report.”

We solicited public comment on our proposal for the public display of the (1) Transfer of Health (TOH) Information to the Provider—Post-Acute Care (PAC) Measure (TOH-Provider), and (2) Transfer of Health (TOH) Information to the Patient—Post-Acute Care (PAC) Measure (TOH-Patient) assessment-based measures. The following is a summary of the comments we received and our responses.

Comment: Several commenters supported the proposal to publicly report the Transfer of Health Information to the Provider-PAC Measure and the Transfer of Health Information to the Patient-PAC Measure beginning with the October 2024 Care Compare refresh or as soon as possible. One commenter expressed their appreciation at CMS' decision to delay the implementation of these process measures during the COVID–19 PHE and stated their members are in a better position to be successful with these measures with the timelines presented in the proposed rule.

Another commenter supported these two measures as a starting point to reflect that health information is shared with the next applicable setting as well as the resident.

Response: We appreciate these commenters' support for the proposed public reporting of these measures.

Comment: Two commenters were not supportive of the proposal. One of these commenters believed the publication of the information will be confusing for consumers and burdensome to SNFs.

Response: We want to clarify that the proposal would add no additional reporting requirements to the SNF QRP. Additionally, we believe that publicly reporting these measures will provide consumers with meaningful information about a SNF's communication of health information, which is critical to ensuring safe and effective transitions from one healthcare setting to another. We work closely with our Office of Communications and consumer groups when onboarding new measures to the Care Compare websites, and we will do the same with the TOH-Patient and TOH-Provider measures.

Comment: Another commenter stated CMS should reconsider publicly reporting the information, and requested CMS delay public display until 2025, using information based on discharges beginning January 1, 2024. They stated the calculation of the measure is confusing, and instructions provided by CMS and its contractors were not made clear until very recently.

Response: SNFs will begin collecting the TOH Information data elements for all residents discharged beginning October 1, 2023. Consistent with the implementation of these measures in other PAC settings, we began providing provider education earlier this year. Additionally, our helpdesks have been responding to provider questions about these measures since the compliance date for the collection of the TOH Information data elements was finalized in the FY 2023 SNF PPS final rule (87 FR 47544 through 47551). We proposed using data collected from January 1, 2024 through December 31, 2024, and believe this will provide SNFs ample time to adjust to their collection. This schedule is consistent with the inaugural display of other new SNF QRP measures.

Comment: We received several additional comments that were outside the scope of our proposal for public reporting of these measures. One commenter urged CMS to expand the measure to include additional information at the time of transfer to facilitate appropriate infection prevention and control, such as other transmission-based precautions a resident may have, presence of indwelling catheters and a resident's vaccination status. One commenter suggested that CMS should consider that sharing the medication list with the resident may not be enough if the resident is unable to understand or follow that list and that it might be more appropriate to assess whether, in those instances, the list was provided to the resident and the family or caregiver. One commenter noted that providing an electronic list to the next provider can be problematic when the PAC provider and the resident's primary care practitioner utilize different Electronic Medical Record (EMR) systems.

Response: We thank the commenters for bringing these issues to our attention and will take these comments into consideration for potential policy refinements.

After consideration of the public comments we received, we are finalizing our proposal to begin publicly displaying data for the measures: (1) Transfer of Health (TOH) Information to the Provider—Post-Acute Care (PAC) Measure (TOH-Provider); and (2) TOH Information to the Patient—PAC Measure (TOH-Patient) beginning with the October 2025 Care Compare refresh or as soon as technically feasible.

3. Public Reporting of the Discharge Function Score Measure Beginning With the FY 2025 SNF QRP

We proposed to begin publicly displaying data for the DC Function measure beginning with the October 2024 refresh of Care Compare, or as soon as technically feasible, using data collected from January 1, 2023 through December 31, 2023 (Quarter 1 2023 through Quarter 4 2023). We proposed, that a SNF's DC Function score would be displayed based on four quarters of data. Provider preview reports would be distributed in July 2024, or as soon as technically feasible. Thereafter, a SNF's DC Function score would be publicly displayed based on four quarters of data and updated quarterly. To ensure the statistical reliability of the data, we proposed that we would not publicly report a SNF's performance on the measure if the SNF had fewer than 20 eligible cases in any quarter. SNFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/resident stays is too small to report.”

We solicited public comment on the proposal for the public display of the Discharge Function Score assessment-based measure beginning with the October 2024 refresh of Care Compare, or as soon as technically feasible. The following is a summary of the comments we received and our responses.

Comment: Two commenters provided support to publicly report the DC Function measure.

Response: We thank the commenters for their support to publicly report the proposed measure.

Comment: One commenter opposed public reporting for this measure as it may inappropriately skew the decision-making process when residents and facilities are reviewing SNF performance prior to admission to a SNF. Although the commenter does not explicitly state the rationale for how this measure would skew decision-making processes, they urge CMS to wait to adopt this measure until it has undergone CBE endorsement.

Response: We do not believe the publication of this measure inappropriately skews residents' decision-making process, and on the contrary will allow Care Compare users to base healthcare decisions on a measure that, as testing demonstrated, more accurately measures functional ability. We direct readers to section VII.C.1.b.1.b. of this final rule, and the technical report for detailed measures testing results demonstrating that the measure provides meaningful information which can be used to improve quality of care, and to the TEP report summaries which detail TEP support for the proposed measure concept. We also acknowledge the importance of the CBE endorsement process and plan to submit the proposed measure for CBE endorsement in the future.

Comment: One commenter expressed concern about consumer confusion with the public reporting of multiple SNF functional outcome measures, as the DC Function measure correlates highly with the Discharge Self-Care Score and Discharge Mobility Score measures. This commenter asks CMS to consider whether reporting only the DC Function measure is sufficient to help the public make informed care decisions.

Response: We work closely with our Office of Communications and consumer groups when onboarding new measures to the Care Compare websites, and we will do the same with the DC Function measure. We will also provide additional training and outreach materials for SNFs before the measure is publicly reported.

After consideration of the public comments we received, we are finalizing our proposal to begin publicly displaying data for the DC Function measure beginning with the October 2024 Care Compare refresh or as soon as technically feasible.

4. Public Reporting of the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP

We proposed to begin publicly displaying data for the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure beginning with the October 2025 refresh of Care Compare or as soon as technically feasible using data collected for Q4 2024 (October 1, 2024 through December 31, 2024). We proposed that a SNF's Patient/Resident COVID–19 Vaccine percent of residents who are up to date would be displayed based on one quarter of data. Provider preview reports would be distributed in July 2025 for data collected in Quarter 4 of CY 2024, or as soon as technically feasible. Thereafter, the percent of SNF residents who are up to date with their COVID–19 vaccinations would be publicly displayed based on 1 quarter of data updated quarterly. To ensure the statistical reliability of the data, we proposed that we would not publicly report a SNF's performance on the measure if the SNF had fewer than 20 eligible cases in any quarter. SNFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/resident stays is too small to report.”

We solicited public comment on the proposal for the public display of the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure beginning with the October 2025 refresh of Care Compare, or as soon as technically feasible. The following is a summary of the comments we received and our responses.

Comment: A few commenters supported public reporting of this measure on Care Compare, to aid beneficiaries and families in selecting a facility, while protecting resident privacy. One commenter suggested that CMS provide contextual guidance that the vaccine is not mandatory and that community vaccine hesitancy factors may influence the vaccination rate in any particular SNF. One commenter suggested that CMS should explicitly detail alongside any public reporting the scoring methodology and exclusions for the measure. Another commenter noted that these data on Care Compare should be coordinated with existing measures of staff and resident COVID–19 vaccination rates to avoid confusion and duplication. They also suggested that reported data on Care Compare include demographic information and be stratified by race, ethnicity and other social risk factors to highlight potential disparities and help address health equity gaps. One commenter noted that if adopted this measure should not be reported through the NHSN.

Response: We thank the commenter for their support and appreciate the additional suggestions provide by other commenters. We work closely with our Office of Communications and consumer groups when onboarding new measures to the Care Compare websites, and we will do the same with the Patient/Resident COVID–19 Vaccine measure. We will also provide additional training and outreach materials for SNFs before the measure is publicly reported. Additionally, we set public reporting thresholds for each measure to ensure we are protecting resident privacy. We also did not propose stratified reporting of these data for this measure; however, we continue to take all concerns, comments, and suggestions into account for future development and expansion of policies to advance health equity across the SNF QRP, including by supporting SNFs in their efforts to ensure equity for all of their residents, and to identify opportunities for improvements in health outcomes. Any updates to specific program requirements related to quality measurement and reporting provisions would be addressed through separate and future notice-and-comment rulemaking, as necessary. Lastly, this SNF QRP measure will be reported on Care Compare using data collected through an assessment item on the MDS. This measure was not proposed to be reported through the NHSN.

Comment: One commenter disagrees with CMS's statement that public reporting of the resident/patients who are up to date measure “would provide residents and caregivers, including those who are at high risk for developing serious complications from COVID–19, with valuable information they can consider when choosing a SNF.” They believe the measure reflects only short-stay residents who are a small portion of the total resident population that is generally not segregated from the broader population, and no longer resides in the nursing home. They noted that the measure tells nothing about risks to potential residents due to the vaccination status of the individuals with whom they will be living and interacting, and that this information is not beneficial to individuals considering SNF care. Another commenter was concerned that scores from both sets of data would be publicly reported and could lead to confusion when a SNF's scores appearing on Care Compare would display two different data sets for the same measure.

Response: We acknowledge that the proposed measure captures only short-stay residents. As mentioned in section VII.C.2.b.2. of this final rule, residents receiving SNF care under the Medicare fee-for-service program may differ from residents receiving long-term care in nursing homes. We also note that SNFs are not required to report beneficiary-level data to the CDC's NHSN, and data from non-CAH swing bed units are not included in the COVID–19 vaccination data reported to the NHSN by nursing homes. Therefore, reporting of this data through the MDS would capture additional resident characteristics and resident populations that may not be covered under the NHSN reporting. Additionally, we believe that adding this measure to the SNF QRP as an assessment-based measure will give SNFs more visibility into their patient-level vaccination rates in order to identify opportunities to improve COVID–19 vaccination rates.

We also acknowledge the commenter's concern regarding the public display of resident vaccination rates using NHSN and MDS data. We work closely with the Office of Communications and consumer groups when onboarding new measures to the Care Compare websites and will take this concern under consideration.

Comment: One commenter raised concerns regarding the reliability of this data collected due to a moving-target definition in addition to there being a lag time from when the vaccine is administered, the data gathered and submitted, and its eventual display online.

Response: We intend to publicly report one quarter of data, so that each Care Compare refresh would include the most up to date information available. We believe this mitigates concerns that the data would not reflect “recent” information to consumers.

After consideration of the public comments we received, we are finalizing our proposal to begin publicly displaying data for the Patient/Resident COVID–19 Vaccine measure beginning with the October 2025 Care Compare refresh or as soon as technically feasible.

VIII. Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program

A. Statutory Background

Through the Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program, we award incentive payments to SNFs to encourage improvements in the quality of care provided to Medicare beneficiaries. The SNF VBP Program is authorized by section 1888(h) to the Act, and it applies to freestanding SNFs, SNFs affiliated with acute care facilities, and all non-CAH swing bed rural hospitals. We believe the SNF VBP Program has helped to transform how Medicare payment is made for SNF care, moving increasingly towards rewarding better value and outcomes instead of merely rewarding volume. Our codified policies for the SNF VBP Program can be found in our regulations at 42 CFR 413.337(f) and 413.338.

B. SNF VBP Program Measures

1. Background

For background on the measures we have adopted for the SNF VBP Program, we refer readers to the following prior final rules:

• In the FY 2016 SNF PPS final rule (80 FR 46411 through 46419), we finalized the Skilled Nursing Facility 30 Day All-Cause Readmission Measure (SNFRM) as required under section 1888(g)(1) of the Act.
• In the FY 2017 SNF PPS final rule (81 FR 51987 through 51995), we finalized the Skilled Nursing Facility 30-Day Potentially Preventable Readmission (SNFPPR) Measure as required under section 1888(g)(2) of the Act.
• In the FY 2020 SNF PPS final rule (84 FR 38821 through 38822), we updated the name of the SNFPPR measure to the “Skilled Nursing Facility Potentially Preventable Readmissions after Hospital Discharge measure” (§ 413.338(a)(14)).
• In the FY 2021 SNF PPS final rule (85 FR 47624), we amended the definition of “SNF Readmission Measure” in our regulations to reflect the updated name for the SNFPPR measure.
• In the FY 2022 SNF PPS final rule (86 FR 42503 through 42507), we finalized a measure suppression policy for the duration of the PHE for COVID–19, and finalized suppression of the SNFRM for scoring and payment purposes for the FY 2022 SNF VBP Program. We also updated the lookback period for risk-adjustment in the FY 2023 performance period (FY 2021).
• In the FY 2023 SNF PPS final rule (87 FR 47559 through 47580), we finalized suppression of the SNFRM for scoring and payment purposes for the FY 2023 SNF VBP Program. We also modified the SNFRM beginning with the FY 2023 program year by adding a risk-adjustment variable for both patients with COVID–19 during the prior proximal hospitalization (PPH) and patients with a history of COVID–19. We also finalized three new quality measures for the SNF VBP Program as permitted under section 1888(h)(2)(A)(ii) of the Act. We finalized two new measures beginning with the FY 2026 program year: (1) Skilled Nursing Facility Healthcare Associated Infections Requiring Hospitalization (SNF HAI) measure; and (2) Total Nursing Hours per Resident Day Staffing (Total Nurse Staffing) measure. We finalized an additional measure beginning with the FY 2027 program year: Discharge to Community—Post-Acute Care Measure for Skilled Nursing Facilities (DTC PAC SNF) measure.

2. Refinements to the SNFPPR Measure Specifications and Updates to the Measure Name

a. Background

Section 1888(g)(2) of the Act requires the Secretary to specify a resource use measure that reflects an all-condition, risk-adjusted potentially preventable hospital readmission rate for skilled nursing facilities. To meet this statutory requirement, we finalized the Skilled Nursing Facility Potentially Preventable Readmission (SNFPPR) measure in the FY 2017 SNF PPS final rule (81 FR 51987 through 51995). In the FY 2020 SNF PPS final rule (84 FR 38821 through 38822), we updated the SNFPPR measure name to the Skilled Nursing Facility Potentially Preventable Readmissions after Hospital Discharge measure, while maintaining SNFPPR as the measure short name.

Although our testing results indicated that the SNFPPR measure was sufficiently developed, valid, and reliable for use in the SNF VBP Program at the time we adopted it, we have since engaged in additional measure development work to further align the measure's specifications with the specifications of other potentially preventable readmission (PPR) measures, including the SNF PPR post-discharge (PD) measure specified for the SNF QRP, and the within-stay PPR measure used in the IRF QRP. Based on those efforts, we proposed to refine the SNFPPR measure specifications as follows: (1) changing the outcome observation window from a fixed 30-day window following acute care hospital discharge to within the SNF stay; and (2) changing the length of time allowed between a qualifying prior proximal inpatient discharge (that is, the inpatient discharge that occurs prior to admission to the index SNF stay) and SNF admission from one day to 30 days. To align with those measure refinements, we also proposed to update the measure name to the “Skilled Nursing Facility Within-Stay Potentially Preventable Readmission (SNF WS PPR) Measure.”

b. Overview of the Updated Measure

The SNF WS PPR measure estimates the risk-standardized rate of unplanned, potentially preventable readmissions (PPR) that occur during SNF stays among Medicare fee-for-service (FFS) beneficiaries. Specifically, this outcome measure reflects readmission rates for SNF residents who are readmitted to a short-stay acute-care hospital or long-term care hospital (LTCH) with a principal diagnosis considered to be unplanned and potentially preventable while within SNF care. The measure is risk-adjusted and calculated using 2 consecutive years of Medicare FFS claims data.

We have tested the updated SNF WS PPR measure for reliability and validity. The random split-half correlation tests indicated good reliability with the intraclass correlation coefficient being notably better than that of the SNFRM. In addition, we tested the validity of the SNF WS PPR measure by comparing SNF WS PPR measure scores with those of nine other measures. The testing results indicated that the SNF WS PPR measure is not duplicative of those nine measures and provides unique information about quality of care not captured by the other nine measures. Validity tests also showed that the measure can accurately predict PPRs while controlling for differences in resident case-mix. We refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf.

(1) Measure Applications Partnership (MAP) Review

We included the SNF WS PPR measure as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List.” The MAP offered conditional support of the SNF WS PPR measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure would add value to the Program because PPRs are disruptive and burdensome to patients. We refer readers to the final 2022–2023 MAP recommendations for further details available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.

c. Data Sources

The SNF WS PPR measure is calculated using 2 consecutive years of Medicare FFS claims data to estimate the risk-standardized rate of unplanned PPRs that occur during SNF stays. Specifically, the stay construction, exclusions, and risk-adjustment model utilize data from the Medicare eligibility files and inpatient hospital claims. Calculating the SNF WS PPR measure using 2 years of data improved the measure's statistical reliability relative to 1 year of data, which is used in the current version of the SNFPPR measure. Because the SNF WS PPR measure is calculated entirely using administrative data, we stated that our proposed adoption of the measure would not impose any additional data collection or submission burden for SNFs.

d. Measure Specifications

(1) Denominator

The population included in the measure denominator is Medicare FFS beneficiaries who are admitted to a SNF during a 2-year measurement period who are not then excluded based on the measure exclusion criteria, which we describe in the next section. For SNF residents with multiple SNF stays during the 2-year readmission window, each of those SNF stays is eligible for inclusion in the measure. In addition, the index SNF admission must have occurred within 30 days of discharge from a prior proximal hospital (PPH) stay, which is defined in the measure specifications as an inpatient stay in an IPPS hospital, a CAH, or an inpatient psychiatric facility. Residents who expire during the readmission window are included in the measure.

The measure denominator is the risk-adjusted “expected” number of residents with a PPR that occurred during the SNF stay. This estimate includes risk adjustment for certain resident characteristics without the facility effect, which we further discuss in section VIII.B.2.e. of this final rule. The “expected” number of residents with a PPR is derived from the predicted number of residents with a PPR if the same residents were treated at the average SNF, which is defined for purposes of this measure as a SNF whose facility effect is zero.

(2) Denominator Exclusions

A SNF stay is excluded from the measure denominator if it meets at least one of the following conditions:

• The SNF resident is less than 18 years old.
• The SNF resident did not have at least 12 months of continuous FFS Medicare enrollment prior to SNF admission, which is defined as the month of SNF admission and the 11 months prior to that admission.
• The SNF resident did not have continuous FFS Medicare enrollment for the entire risk period (defined as enrollment during the month of SNF admission through the month of SNF discharge).
• SNF stays where there was a gap of greater than 30 days between discharge from the PPH and the SNF admission.
• The SNF resident was discharged from the SNF against medical advice.
• SNF stays in which the principal diagnosis for the PPH was for the medical treatment of cancer. Residents with cancer whose principal diagnosis from the PPH was for other medical diagnoses or for surgical treatment of their cancer remain included in the measure.
• SNF stays in which the principle diagnosis for the PPH was for pregnancy (this is an atypical reason for resident to be admitted to SNFs).
• The SNF resident who the SNF subsequently transfers to a Federal hospital. A transfer to a Federal hospital is identified when discharge code 43 is entered for the patient discharge status field on the Medicare claim.
• The SNF resident received care from a provider outside of the United States, Puerto Rico, or a U.S. territory, as identified by the provider's CCN on the Medicare claim.

• SNF stays with data that are problematic (for example, anomalous records for hospital stays that overlap wholly or in part or are otherwise erroneous or contradictory).

• SNF stays that occurred in a CAH swing bed.

For additional details on the denominator exclusions, we refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf.

(3) Numerator

The numerator is defined as the number of SNF residents included in the measure denominator who also have an unplanned PPR during an index SNF stay. For the purposes of this measure, an unplanned PPR is defined as a readmission from a SNF to an acute care hospital or a long-term care hospital, with a diagnosis considered to be unplanned and potentially preventable. The numerator only includes unplanned PPRs that occur during the within-SNF stay period (that is, from the date of the SNF admission through and including the date of discharge), which can be a hospital readmission that occurs within the SNF stay or a direct transfer to a hospital on the date of the SNF discharge. Because this measure focuses on potentially preventable and unplanned readmissions, we do not count planned readmissions in the numerator. Further, because we consider readmissions to inpatient psychiatric facilities to be planned, they are also not counted in the numerator.

The measure numerator is the risk-adjusted “predicted” estimate of the number of residents with an unplanned PPR that occurred during a SNF stay. This estimate starts with the unadjusted, observed count of the measure outcome (the number of residents with an unplanned PPR during a SNF stay), which is then risk-adjusted for resident characteristics and a statistical estimate of the SNF's facility effect, to become the risk-adjusted numerator.

e. Risk Adjustment

The SNF WS PPR measure is risk-adjusted to control for risk factor differences across SNF residents and SNF facilities. Specifically, the statistical model utilizes a hierarchical logistic regression to estimate the effect of resident characteristics on the probability of readmission across all SNFs and the effect of each SNF on readmissions that differs from that of the average SNF (“facility effect”). The denominator is risk-adjusted for resident characteristics only, while the numerator is risk-adjusted for both resident characteristics and the facility effect. The specific risk adjustment variables included in the statistical model for this measure are the following:

• Age and sex category.
• Original reason for Medicare entitlement (disability or other).
• Indicator of End-Stage Renal Disease (ESRD).
• Surgery category if present (for example, cardiothoracic, orthopedic), as defined in the Hospital Wide Readmission (HWR) measure model software. The surgical procedures are grouped using the Clinical Classification Software (CCS) classes for ICD–10 procedures developed by the Agency for Healthcare Research and Quality (AHRQ).
• Principal diagnosis on PPH inpatient claim. The ICD–10 codes are grouped clinically using the CCS mappings developed by AHRQ.
• Comorbidities from secondary diagnoses on the PPH inpatient claim and diagnoses from earlier hospital inpatient claims up to 1 year before the date of the index SNF admission (these are clustered using the Hierarchical Condition Categories (HCC) groups used by CMS).
• Length of stay in the PPH (categorical to account for nonlinearity).
• Prior acute intensive care unit (ICU) or critical care unit (CCU) utilization.
• Number of prior acute care hospital discharges in the prior year.

For additional details on the risk adjustment model, we refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf.

f. Measure Calculation

The SNF WS PPR measure estimates the risk-standardized rate of unplanned PPRs that occur during SNF stays among Medicare FFS beneficiaries. A lower score on this measure indicates better performance. The provider-level risk-standardized readmission rate (RSRR) of unplanned PPRs is calculated by multiplying the standardized risk ratio (SRR) by the mean readmission rate in the population (that is, all Medicare FFS residents included in the measure). The SRR is calculated as the predicted number of readmissions at the SNF divided by the expected number of readmissions for the same residents if treated at the average SNF. For additional details on the calculation method, we refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf.

g. Scoring of SNF Performance on the SNF WS PPR Measure

(1) Background

In the FY 2017 SNF PPS final rule (81 FR 52000 through 52001), we finalized a policy to invert SNFRM measure rates such that a higher measure rate reflects better performance on the SNFRM. In that final rule, we also stated our belief that this inversion is important for incentivizing improvement in a clear and understandable manner, and because a “lower is better” rate could cause confusion among SNFs and the public. In the FY 2023 SNF PPS final rule (87 FR 47568), we applied this policy to the SNF HAI measure such that a higher measure rate reflects better performance on the SNF HAI measure. We also stated our intent to apply this inversion scoring policy to all measures in the Program for which the calculation produces a “lower is better” measure rate. We continue to believe that inverting measure rates such that a higher measure rate reflects better performance on a measure is important for incentivizing improvement in a clear and understandable manner.

The measure rate inversion scoring policy does not change the measure specifications or the calculation method. We use this measure rate inversion only as part of the scoring methodology under the SNF VBP Program. The measure rate inversion is part of the methodology we use to generate measure scores, and resulting SNF Performance Scores, that are clear and understandable for SNFs and the public.

(2) Inversion of the SNF WS PPR Measure Rate for SNF VBP Scoring Purposes

In the previous section, we stated that a lower risk-standardized rate for the SNF WS PPR measure indicates better performance. Therefore, we proposed to apply our measure rate inversion scoring policy to the SNF WS PPR measure because a “lower is better” rate could cause confusion among SNFs and the public. Specifically, we proposed to calculate the scores for this measure for the SNF VBP Program by inverting the SNF WS PPR measure rates using the following calculation:

SNF WS PPR Inverted Rate = 1–Facility's SNF WS PPR Risk Standardized Rate

This calculation will invert SNF WS PPR measure rates such that a higher measure rate would reflect better performance.

h. Confidential Feedback Reports and Public Reporting for the SNF WS PPR Measure

Our confidential feedback reports and public reporting policies are codified at § 413.338(f) of our regulations. In the FY 2023 SNF PPS final rule (87 FR 47591 through 47592), we revised our regulations such that the confidential feedback reports and public reporting policies apply to each measure specified for a fiscal year, which includes the SNF WS PPR measure beginning with the FY 2028 program year.

We solicited public comment on our proposal to refine the measure specifications for the SNFPPR measure, and our proposal to update the measure's name to the “Skilled Nursing Facility Within-Stay Potentially Preventable Readmissions (SNF WS PPR) measure.” We also solicited public comment on our proposal to invert the SNF WS PPR measure rate for SNF VBP Program scoring purposes.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: Several commenters supported the proposal to refine the SNFPPR measure specifications and update the measure name to the SNF WS PPR measure because those proposals more appropriately align the measure with changes and improvements within the SNF's control. Specifically, commenters supported the change to a within-SNF stay readmission specification because it allows for a fairer comparison of SNF performance given the socioeconomic and other community factors outside a SNF's control that may impact hospital readmissions during the periods before SNF admission and after SNF discharge.

Response: We thank the commenters for their support. We agree that this measure refinement allows us to accurately measure the rates of PPRs across SNFs and to assess performance based on factors within a SNF's control.

Comment: One commenter, while supporting the proposal to refine the SNFPPR measure specifications and update the measure name generally, recommended that CMS delay adoption of the SNF WS PPR measures until it has been endorsed by the consensus-based entity (CBE).

Response: SNF VBP measures are not required to be endorsed by the CBE to be included in the Program. We will consider submitting this measure for endorsement by the CBE in the future.

Comment: One commenter expressed concern about the proposal to implement the SNF WS PPR measure because we would score it using predicted and expected outcomes for residents, which may not be accurate.

Response: We do not agree with commenter's concern regarding the accuracy and use of predicted and expected outcomes for residents as part of the calculation for the SNF WS PPR measure. The “expected” and “predicted” values are estimates of the measure outcome (denominator and numerator, respectively) and are calculated by risk adjusting the data obtained from the Medicare FFS claims. As we discuss in section VIII.G. of this final rule, claims data are validated for accuracy by Medicare Administrative Contractors (MACs) and therefore, we believe these data are sufficiently validated and accurate for use in calculating SNF VBP claims-based measures. Further, the risk adjustment model helps ensure we are assessing SNF performance based on the quality of care delivered by SNFs. We also note that the current measure (SNFRM) is calculated in a similar manner.

Comment: A few commenters expressed concern about the proposal to implement the SNF WS PPR measure, due to the potential to attribute preventable hospital readmissions to the SNF when the hospital readmission is due to other factors, such as being prematurely discharged from a hospital or if a patient's condition worsened before admission to a SNF. Specifically, one commenter expressed concern that refining the SNFPPR measure specifications to increase the number of days between the hospital inpatient discharge and SNF admission could increase the potential for factors outside the hospital or SNF's control to influence a resident's condition prior to the SNF admission. A few commenters recommended that CMS consider expanding the exclusion criteria to exclude residents with more complex care and applying appropriate risk adjustment. One commenter expressed concern that the SNF WS PPR measure could produce counterproductive SNF behavior, such as incentivizing SNFs to not admit patients discharged from the hospital who have multiple co-morbidities and are at higher risk of being readmitted to the hospital, and to only admit those perceived to have a lower risk of hospital readmission. One commenter recommended that CMS continue to measure how transitioning to the SNF WS PPR measure impacts the conditions residents present with at admission.

Response: We recognize that the measure cannot completely eliminate the potential risk of attributing a PPR to a SNF when that readmission occurred due to factors outside the SNFs control. However, we believe that the SNF WS PPR measure specifications minimize that risk to the extent feasible. For example, the SNF WS PPR measure has a robust risk-adjustment model that controls for numerous variables including comorbidities, principal diagnoses for the prior proximal hospital inpatient claim, and measures of prior acute care utilization. We also note that the WS PPR definition was developed based on findings from an environmental scan, empirical analyses, and clinical team evaluations to ensure that hospital readmissions included in this measure are potentially preventable and unplanned, and that readmissions include only PPR conditions associated with post-acute care. For additional details on the PPR definition used for the measure, we refer commenters to the SNF WS PPR measure technical specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf. In addition, we note that section 1888(g)(2) of the Act requires that the SNF WS PPR measure be “all-condition,” which we believe necessitates attributing readmissions to SNFs even in the cases the commenter specified.

The original SNFPPR measure excluded SNF stays with a gap of greater than one day between discharge from the prior proximal hospitalization and SNF admission in order to harmonize with the SNFRM measure specifications. We received public comments and feedback from a Technical Expert Panel (TEP) expressing concern with the 1-day prior proximal hospitalization lookback window noting that this 1-day lookback window does not consider medically complex patients and that this criterion did not align with the measure specifications for other PPR measures. In response to that feedback, we refined the SNF WS PPR measure specifications such that the SNF admission must occur within 30 days of discharge from the prior proximal hospitalization. This refinement aligns the SNF WS PPR measure specifications with those of PPR measures used in other CMS Programs, including the SNF PPR post-discharge measure specified for the SNF QRP. We note that the SNF WS PPR measure refinements are associated with improved measure reliability and validity. We intend to monitor performance on this measure as part of ongoing evaluation efforts.

We believe the exclusion criteria for the SNF WS PPR measure, as detailed in section VIII.B.2.d.(2) of this final rule, in addition to the variables included in the risk-adjustment model, are sufficient for controlling for medically complex residents. For example, the risk-adjustment model includes variables relating to comorbidities, principal diagnoses for the prior proximal hospital inpatient claim, and measures of prior acute care utilization. Therefore, we do not believe it is necessary to expand the exclusion criteria to include medically complex residents at this time. However, we will take this into consideration as we monitor performance on this measure.

After consideration of public comments, we are finalizing the updates to the SNFPPR measure specifications and finalizing our proposal to update the measure's name to the “Skilled Nursing Facility Within-Stay Potentially Preventable Readmissions (SNF WS PPR) measure.”

3. Replacement of the SNFRM With the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

Section 1888(h)(2)(B) of the Act requires the Secretary to apply the measure specified under section 1888(g)(2) of the Act, instead of the measure specified under section 1888(g)(1) of the Act as soon as practicable. To meet that statutory requirement, we proposed to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year. This is the first program year that we can feasibly implement the SNF WS PPR measure after taking into consideration its proposed performance period and a number of other statutory requirements.

We proposed a 2-year performance period for the proposed SNF WS PPR measure, and we believe the earliest the first performance period can occur is FY 2025 and FY 2026 (October 1, 2024 through September 30, 2026). This will provide us with sufficient time to calculate and announce the performance standards for the SNF WS PPR measure at least 60 days before the beginning of that performance period, as required under section 1888(h)(3)(C) of the Act. Additionally, we are required under section 1888(h)(7) of the Act to announce the net payment adjustments for SNFs no later than 60 days prior to the start of the applicable fiscal year. We calculate these payment adjustments using performance period data. To provide us with sufficient time to calculate and announce the net payment adjustments after the end of the performance period (FY 2025 and FY 2026), we believe the earliest program year in which we can feasibly adopt the proposed SNF WS PPR measure is FY 2028.

We solicited public comment on our proposal to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: Several commenters supported the proposal to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year because they agreed that this is the earliest CMS can implement this change and that the SNF WS PPR measure is more reflective of actions SNF's can take to reduce hospital readmissions.

Response: We thank the commenters for their support. We agree that replacing the SNFRM with the SNF WS PPR measure more appropriately assesses the quality of care within the SNF's control.

Comment: One commenter opposed the proposal to replace the SNFRM with the SNF WS PPR measure because the SNFRM is already publicly reported and available to consumers.

Response: The commenter is correct in that we do publicly report information on the performance of SNFs with respect to the SNFRM. However, we are required at section 1888(h)(2)(B) of the Act to replace the measure specified under section 1888(g)(1) of the Act, currently the SNFRM, with the measure specified under section 1888(g)(2) of the Act, which we proposed as the SNF WS PPR measure. We will also begin publicly reporting information on the performance of SNFs with respect to the SNF WS PPR measure when the measure is implemented beginning with the FY 2028 SNF VBP program year.

After consideration of public comments, we are finalizing our proposal to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP program year.

4. Adoption of Quality Measures for the SNF VBP Expansion Beginning With the FY 2026 Program Year

a. Background

Section 1888(h)(2)(A)(ii) of the Act (as amended by section 111(a)(2)(C) of the CAA 2021) allows the Secretary to expand the SNF VBP Program to include up to 10 quality measures with respect to payments for services furnished on or after October 1, 2023. These measures may include measures of functional status, patient safety, care coordination, or patient experience. Section 1888(h)(2)(A)(ii) of the Act also requires that the Secretary consider and apply, as appropriate, quality measures specified under section 1899B(c)(1) of the Act.

In the FY 2023 SNF PPS final rule (87 FR 47564 through 47580), we adopted the first three measures for the Program expansion: (1) SNF HAI measure; (2) Total Nurse Staffing measure; and (3) DTC PAC SNF measure. We adopted the SNF HAI and Total Nurse Staffing measures beginning with the FY 2026 program year (FY 2024 is the first performance period). We also adopted the DTC PAC SNF measure beginning with the FY 2027 program year (FY 2024 and FY 2025 is the first performance period).

In the proposed rule, we proposed to adopt four additional measures for the Program. We proposed one new measure beginning with the FY 2026 program year (FY 2024 would be the first performance period): Total Nursing Staff Turnover (“Nursing Staff Turnover”) measure. We also proposed to adopt three new measures beginning with the FY 2027 program year (FY 2025 would be the first performance period): (1) Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) (“Falls with Major Injury (Long-Stay)”) measure; (2) Discharge Function Score for SNFs (“DC Function measure”); and (3) Number of Hospitalizations per 1,000 Long Stay Resident Days (“Long Stay Hospitalization”) measure.

Therefore, for the FY 2024 performance period, we proposed that SNF data would be collected for five measures: SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, and DTC PAC SNF measures. Performance on the first four measures would affect SNF payment in the FY 2026 program year. Since the DTC PAC SNF measure is a 2-year measure, performance on that measure would affect SNF payment in the FY 2027 program year.

Beginning with the FY 2025 performance period, SNF data would be collected for nine measures: SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, DC Function, Falls with Major Injury (Long-Stay), Long Stay Hospitalization, DTC PAC SNF, and SNF WS PPR measures. Performance on the first eight measures will affect SNF payment in the FY 2027 program year. Since the SNF WS PPR measure is a 2-year measure, performance on this measure will affect SNF payment in the FY 2028 program year. Further, we refer readers to section VIII.B.3. of this final rule for additional details on our replacement of the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year, which will mean that the FY 2027 and FY 2028 program years will each only have eight measures that affect SNF payment for those program years. Finally, there is no additional burden on SNFs to submit data on these previously adopted and proposed measures for the SNF VBP Program.

Table 15 provides the list of the currently adopted measures and proposed measures for the SNF VBP Program.

b. Adoption of the Total Nursing Staff Turnover Measure Beginning With the FY 2026 SNF VBP Program Year

(1) Background

Nursing home staffing, including nursing staff turnover, has long been considered an important indicator of nursing home quality. Longer-tenured nursing staff are more familiar with the residents and are better able to detect changes in a resident's condition. They are also more acclimated to their facility's procedures and thus, operate more efficiently. In contrast, higher nursing staff turnover can mean that nursing staff are less familiar with resident needs and facility procedures, which can contribute to lower quality of care.

There is considerable evidence demonstrating the impact of nursing staff turnover on resident outcomes, with higher turnover associated with poorer quality of care. A recent 2019 study comparing nursing home's annualized turnover rates with the overall five-star ratings for the facilities found that the average total nursing staff annual turnover rates were 53.4 percent among one-star nursing homes and 40.7 percent for five-star facilities. The same study found a statistically significant relationship between higher turnover rates and lower performance on clinical quality measures, including hospitalization rates, readmission rates, and emergency department visits. Studies have also shown that nursing staff turnover is a meaningful factor in nursing home quality of care and that staff turnover influences quality outcomes. For example, higher staff turnover is associated with an increased likelihood of receiving an infection control citation.

Recently, the National Academies of Sciences, Engineering, and Medicine formed the Committee on the Quality of Care in Nursing Homes to examine the delivery of care and the complex array of factors that influence the quality of care in nursing homes. The committee published a report in 2022 titled “The National Imperative to Improve Nursing Home Quality.” The report details the complex array of factors that influence care quality in nursing homes, including staffing variables such as staffing levels and turnover, and identifies several broad goals and recommendations to improve the quality of care in nursing homes. In the 2022 report, the National Academies of Sciences, Engineering, and Medicine highlighted the association between the high turnover of many nursing home staff, including RNs, and lower quality of care delivery in nursing homes. The report also recognized the need for quality measures that report on turnover rates, citing that increased transparency will improve patient care. Because of its central role in the quality of care for Medicare beneficiaries, HHS and the Biden-Harris Administration are also committed to improving the quality of care in nursing homes with respect to staffing, as stated in the fact sheets entitled “Protecting Seniors by Improving Safety and Quality of Care in the Nation's Nursing Homes” and “Biden-Harris Administration Announces New Steps to Improve Quality of Nursing Homes.” While much of this research has been conducted in long-term care facilities or nursing homes, we believe this research is relevant to the SNF setting, because approximately 94 percent of long-term care facilities are dually certified as both SNFs and nursing facilities (86 FR 42508).

In light of the strong association between high nursing staff turnover rates and negative resident outcomes, including the nursing staff turnover measure in the SNF VBP Program will provide a comprehensive assessment of the quality of care provided to residents. This measure may also drive improvements in nursing staff turnover that are likely to translate into positive resident outcomes.

Although the Nursing Staff Turnover measure is not specified under section 1899B(c)(1) of the Act, we believe this measure supports the Program's goals to improve the quality of care provided to Medicare beneficiaries throughout their entire SNF stay. We have long identified staffing as one of the vital components of a SNF's ability to provide quality care and use staffing data to gauge a facility's impact on quality of care in SNFs with more accuracy and efficacy. The proposed measure aligns with the topics listed under section 1888(h)(2)(A)(ii) of the Act and with HHS and Biden-Harris Administration priorities. We also believe that the Nursing Staff Turnover measure would complement the Total Nursing Hours per Resident Day (Total Nurse Staffing) measure, adopted in the FY 2023 SNF PPS final rule (87 FR 47570 through 47576). Together, these measures emphasize and align with our current priorities and focus areas for the Program.

(2) Overview of Measure

The Nursing Staff Turnover measure is a structural measure that uses auditable electronic data reported to CMS' Payroll-Based Journal (PBJ) system to calculate annual turnover rates for nursing staff, including registered nurses (RNs), licensed practical nurses (LPNs), and nurse aides. Given the well-documented impact of nurse staffing on resident outcomes and quality of care, this measure will align the Program with the Care Coordination domain of CMS' Meaningful Measures 2.0 Framework. The Nursing Staff Turnover measure is currently being measured and publicly reported for nursing facilities on the Care Compare website https://www.medicare.gov/care-compare/ and is used in the Five-Star Quality Rating System. For more information on measure specifications and how this measure is used in the Five-Star Quality Rating System, we referred readers to the January 2023 Technical Users' Guide available at https://www.cms.gov/medicare/provider-enrollment-and-certification/certificationandcomplianc/downloads/usersguide.pdf.

This measure is constructed using daily staffing information submitted through the PBJ system by nursing facilities. Specifically, turnover is identified based on gaps in days worked, which helps ensure that Nursing Staff Turnover is defined the same way across all nursing facilities with SNF beds and that it does not depend on termination dates that may be reported inconsistently by these facilities. Individuals are identified based on the employee system ID and SNF identifiers in the PBJ data. We refer readers to the Nursing Staff Turnover measure specifications available at https://www.cms.gov/medicare/provider-enrollment-and-certification/certificationandcomplianc/downloads/usersguide.pdf.

Payroll data are considered the gold standard for nurse staffing measures and are a significant improvement over the manual data previously used, wherein staffing information was calculated based on a form (CMS–671) filled out manually by the facility. The PBJ staffing data are electronically submitted and auditable back to payroll and other verifiable sources. Analyses of PBJ-based staffing measures show a relationship between higher nurse staffing levels and higher ratings for other dimensions of quality such as health inspection survey results and quality measures.

(a) Interested Parties and TEP Input

In 2019 through 2022, CMS tested this measure based on input from the CMS Five-Star Quality Rating Systems' TEP, as well as input from interested parties. We began publicly reporting this measure on the Care Compare website via the Nursing Home Five-Star Rating System in January 2022.

We solicited public feedback on this measure in a “Request for Comment on Additional SNF VBP Program Measure Considerations for Future Years” in the FY 2023 SNF PPS proposed rule (87 FR 22786 through 22787). We considered the input we received as we developed our proposal for this measure. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47592 through 475963) for a detailed summary of the feedback we received on this measure.

(b) Measure Applications Partnership (MAP) Review

We included the Nursing Staff Turnover measure as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List.” The MAP offered conditional support of the Nursing Staff Turnover measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure would add value to the Program because staffing turnover is a longstanding indicator of nursing home quality, and it addresses the Care Coordination domain of the Meaningful Measures 2.0 Framework. We refer readers to the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.

(3) Data Sources

The Nursing Staff Turnover measure is calculated using auditable, electronic staffing data submitted by each SNF for each quarter through the PBJ system. Specifically, this measure utilizes five data elements from the PBJ data, including employee ID, facility ID, hours worked, work date, and job title code.

(4) Inclusion and Exclusion Criteria

We proposed that SNFs will be excluded from the measure under the following conditions:

• Any SNF with 100 percent total nursing staff turnover for any day in the six-quarter period during which there were at least five eligible nurse staff. A 100 percent daily turnover is typically the result of changes in the employee IDs used by SNFs and does not reflect actual staff turnover.
• SNFs that do not submit staffing data or submit data that are considered invalid (using the current exclusion rules for the staffing domain) for one or more of the quarters used to calculate the Nursing Staff turnover measure.
• SNFs that do not have resident census information (derived from MDS assessments).
• SNFs with fewer than five eligible nurses (RNs, LPNs and nurse aides) in the denominator.

(a) Denominator

The denominator for the Nursing Staff Turnover measure includes all eligible employees, defined as RNs, LPNs, and nurse aides, who are regular employees and agency staff who work at a Medicare certified SNF and use the same job category codes as other nurse staffing measures that are reported on the Care Compare website. For the purposes of this measure, the RN category is defined as RNs (job code 7), RN director of nursing (job code 5), and RNs with administrative duties (job code 6). The LPN category is defined as LPNs (job code 9) and LPNs with administrative duties (job code 8). The nurse aide category is defined as certified nurse aides (job code 10), aides in training (job code 11), and medication aides/technicians (job code 12). This measure only includes eligible employees who work at least 120 hours in a 90-day period. The timeframe for the 90-day period begins on the first workday observed during the quarter prior to the start of the performance period (termed the baseline quarter) and ends on the last workday, of the last month, of the second quarter of the performance period. Eligible employees who work infrequently (that is, those who work fewer than 120 hours during a 90-day period, including those who only occasionally cover shifts at a nursing home) would be excluded from the denominator calculation.

(b) Numerator

The numerator includes eligible employees who were included in the denominator and who are not identified in the PBJ data as having worked at the SNF for at least 60 consecutive days during the performance period. The 60-day gap must start during the period covered by the turnover measure. The turnover date is defined as the last workday prior to the start of the 60-day gap.

(5) Measure Calculation

The Nursing Staff Turnover measure is calculated using six consecutive quarters of PBJ data. Data from a baseline quarter, Q0, along with the first two quarters of the performance period, are used for identifying employees who are eligible to be included in the measure (denominator). The four quarters of data (Q1 through Q4) of the performance period are used for identifying the number of employment spells, defined as a continuous period of work, that ended in turnover (numerator). Data from the sixth quarter (Q5), which occurs after the four-quarter numerator (performance) period, are used to identify gaps in days worked that started in the last 60 days of the fifth quarter (Q4) used for the measure. To calculate the measure score, we first determine the measure denominator by identifying the total number of employment spells, defined as a continuous period of work. For example, for the FY 2026 program year, the denominator will be calculated as the number of eligible employees who worked 120 or more hours in a 90-day period with the first workday of the 90-day period occurring in FY 2023 Q4, the quarter prior to the start of the performance period (Q0), through FY 2024 Q2, the first 2 quarters of the performance period (July 1, 2023 through March 31, 2024). The numerator is calculated as the total number of eligible employees who had a 60-day gap from October 1, 2023 through September 30, 2024 during which they did not work. Data from FY 2025 Q1, defined as Q5 above, is also used to identify gaps that start within 60 days of the end of the performance period (August 2, 2024 through September 30, 2024).

We proposed to calculate the Nursing Staff Turnover measure rate for the SNF VBP Program using the following formula:

We also note that based on analysis and previous research on turnover measures, and a review by a technical expert panel, the Nursing Staff Turnover measure is not risk-adjusted.

We solicited public comment on our proposal to adopt the Total Nursing Staff Turnover measure beginning with the FY 2026 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: Many commenters supported CMS's proposal to adopt the Total Nursing Staff Turnover Measure because it provides a meaningful assessment of the quality of care provided to SNF residents.

Response: We thank the commenters for their support. We agree that this measure will provide valuable insight into the quality of care that SNF residents are receiving.

Comment: A few commenters that supported the proposed measure also recommended that a retention measure either be added or used in place of the turnover measure to help incentivize positive behavior by SNFs. One commenter recommended that CMS develop a resident “dumping” measure as a metric to reduce facility-initiated transfers and discharges which negatively impact residents and their quality of care.

Response: We thank the commenters for their recommendations and will take this feedback into consideration as we develop additional measures for future rulemaking.

Comment: A few commenters supported the measure generally but recommended that CMS consider a number of factors with respect to both the proposed measure and potential future measures. One commenter suggested that CMS revise the proposed measure to exclude team members that move, or float, within a health system. A few commenters recommended that CMS consider the impact of staffing changes when employees do not work for a period of time that exceeds 60 days (for example, because of family or medical leave) but indicate their intention to return. Several commenters did not support the proposed measure because it does not exclude staff that have taken parental leave or are students or seasonal workers. A few commenters recommended expanding the length of the gap beyond 60 days or providing an adjustment for workers returning from an approved leave. One commenter stated that the proposed measure should take into consideration a differential impact of staff turnover on residents depending on the role of the exiting nursing staff member within the SNF. One commenter suggested that the measure be revised to include all direct care workers and rehabilitation professionals in SNFs because they all impact performance and quality of care. One commenter recommended that CMS monitor the impact of the measure by assessing the relationship between resident outcomes and staff turnover to see if SNFs change their behavior in ways that may lower quality of care.

Response: We carefully considered different turnover specifications, including the 60-day gap threshold for turnover, the inclusion of agency and other types of nursing staff, and the minimum number of hours required to be included in the measure. The final measure specifications were developed based on extensive data analyses, as well as recommendations to us from the project's Technical Expert Panel (TEP) convened by a CMS contractor. We believe this measure, as proposed, is both a reliable and valid measure of nursing staff turnover. We tested the validity of the measure by examining the association between the Nursing Staff Turnover measure and a comprehensive set of measures that capture nursing home quality, including nursing home ratings from Care Compare's Five-Star Quality Rating System and claims-based measures of hospitalizations and outpatient Emergency Department visits for both short- and long-stay residents. We found a consistent and statistically significant relationship between the Nursing Staff Turnover measure and this comprehensive set of measures that capture nursing home quality. For reliability testing, we used split-sample reliability testing. We calculated the Shrout-Fleiss intraclass correlation coefficient (ICC) between the split-half scores to measure reliability. The split-sample ICC was 0.834. The results of this extensive testing indicate the strong relationship between nursing staff turnover, as proposed, and quality of care. It shows that the quality of care is impacted when a caregiver does not report any hours worked for 60 days or more whether they are still officially employed by the SNF or not. Additionally, we conducted analyses that showed a very high correlation in nursing home turnover rates for a measure based on different gaps in days worked (for example, 30, 60, 90 days) suggesting extending the number of days in the gap would have little impact on the measure rate. Lastly, the PBJ data that we use to calculate the turnover measures do not allow us to identify individuals who have taken a period of leave but intend to return to work.

Although we recognize that all staff may have an impact on resident quality, there is substantial literature documenting the relationship between nursing staff turnover and quality. Additional research supports that all nursing staff, including certified nursing assistants and LPNs, play a critical role in providing care to Medicare beneficiaries in SNFs. Because of this extensive evidence, we chose to focus on nursing staff turnover at this time.

Comment: A few commenters supported the proposed measure in concept but expressed concern that the measure may not accurately reflect true nursing staff turnover. A few commenters stated that the measure should distinguish between voluntary and involuntary turnover because they believe SNFs should not be negatively impacted by the latter. A few commenters stated that the inclusion of contracted nursing staff would lead to inaccurate nursing staff turnover counts. One commenter stated that the inclusion of nursing staff who work solely in an administrative capacity and do not perform direct resident care would lead to inaccurate nursing staff turnover counts. One commenter suggested that CMS delay the implementation of this measure to develop a way to index SNFs to a regional nursing staff turnover measure that would better reflect local labor market variance and factors within a SNF's control.

Response: There is significant research connecting nursing staff turnover with resident outcomes (88 FR 21366). The TEP convened by our contractor concluded that continuity of care is impacted when a caregiver does not work for 60 or more days, regardless of whether they are still employed by the facility or the reason they are no longer employed (on a voluntary or involuntary basis). This was further supported by the analysis we conducted that showed a strong relationship between the Nursing Staff Turnover measure, as proposed, and quality of care. In addition to evidence linking nursing staff turnover to quality, there is also evidence of a significant relationship between directors of nursing and nursing administrator turnover and resident quality of care. Specifically, retention of directors of nursing and nursing administrators is associated with better resident outcomes and fewer facility health and safety deficiencies. Thus, we believe it is appropriate to include nurses with administrative responsibilities in this measure. We also note that we do not believe delaying this measure to incorporate regional differences is necessary or appropriate at this time. As described previously in this section, this measure went through extensive reliability and validity testing and thus we are confident that this measure, as proposed, is reliable, valid, and an excellent indicator of quality. However, we will continue to assess the measure and if needed, propose measure updates in future rulemaking.

Comment: Many commenters did not support the proposed Nursing Staff Turnover measure because they believe it is unrelated to the intent of the program and reflects circumstances outside of SNFs' control such as market conditions. One commenter stated that the proposed measure is not a good indicator of high-quality care because of current healthcare workforce challenges that are outside the control of SNFs. One commenter believed this measure is solving a problem that does not exist and that current staffing standards are adequate to ensure patient safety. One commenter requested that CMS delay implementing the proposed measure until the nurse staffing minimum standards that the agency is developing are finalized and implemented in long-term care facilities. One commenter noted that the proposed measure will not be risk-adjusted and urged CMS to consider adding risk adjustment to the measure.

Response: We recognize the relationship between nursing staff turnover and quality of care is multi-faceted, but we disagree that this measure is unrelated to the intent of the Program to reward SNFs that provide high quality care. We refer commenters to the proposed rule (88 FR 21366 through 21367) where we discussed several studies that emphasize the evidence of a relationship between nursing staff turnover, quality of care, and patient outcomes. We have selected this measure as a complement to the Total Nursing Staffing measure we finalized in the FY 2023 SNF PPS final rule (87 FR 47576) and as an additional step towards addressing this complex relationship between nurse staffing and quality of care. There are ongoing efforts at CMS to address staffing, including discussions around nurse staffing minimum standards. However, nursing staff minimums and turnover are distinct, and we do not believe those efforts need to be in place prior to finalizing this Nursing Staff Turnover measure for the SNF VBP Program. We reiterate that the proposed Nursing Staff Turnover measure is reliable and valid, and we do not anticipate staffing minimums having significant impact on this proposed measure. Regarding risk-adjustment, as we stated in the proposed rule (88 FR 21368), based on analysis and previous research on turnover measures, and a review by a TEP convened by our contractor, we do not believe the Nursing Staff Turnover measure needs to be risk-adjusted at this time. We do not believe that differences in nursing home turnover rates are related to nursing home acuity. Rather, we believe that turnover is related to management practices such as high-quality leadership, valuing and respecting nursing staff, positive human resource practices, work organization and care practices that help to retain staff and build relationships, and compensation and benefits, among others. It would not be appropriate to have any type of adjustment for these factors; however, we will continue to monitor the data and adjust as needed in future rulemaking.

Comment: Several commenters did not support the proposed measure because SNFs are being impacted by widespread healthcare personnel shortages for which they believe SNFs should not be penalized. A few commenters expressed concern that SNFs do not have the financial support for retention and recruitment and that finalizing this measure could make turnover worse as facilities will be penalized and will then have less money to hire and train additional staff. One commenter suggested CMS instead focus on limiting the number of staffing agencies that are contributing to the staffing crisis. One commenter was concerned that SNFs will have to choose between having enough staff and accepting agency staff at the cost of poor performance on the measure.

Response: We recognize that the past few years, which included the COVID–19 PHE, have significantly affected SNF operations and staffing. We also remain committed to the importance of value-based care and incentivizing quality care tied to payment. SNF staffing, including turnover, is a high priority for us because of its central role in the quality of care for SNF residents. As described previously in this section, the measure specifications were developed based on extensive data analyses, as well as recommendations to us from the project's TEP convened by a CMS contractor. This measure is both a reliable and valid measure of nursing staff turnover as proposed, and therefore, we continue to believe that this measure will provide a more comprehensive assessment of, and accountability for, the quality of care provided to residents despite staffing challenges. Further, this measure, which includes agency staff, has been shown to have a strong relationship with quality of care, and thus we do not believe it is appropriate to revise the measure. We will continue to evaluate the impact on SNFs' behaviors, staffing levels, and quality outcomes as the measure is implemented in the Program.

Comment: One commenter did not support the measure without endorsement by the CBE.

Response: We note the SNF VBP Program is not required to seek endorsement by the CBE to include measures in the Program. We will consider submitting this measure for endorsement by the CBE in the future.

Comment: A few commenters believed the measure is overly complicated. One commenter expressed that the measure will only add to the reporting burden for SNFs.

Response: The Nursing Staff Turnover measure should already be familiar to SNFs that are dually certified as nursing facilities (NFs) because nursing facilities are currently required to report to us the data needed to calculate the measure. We publicly report data on the measure on the Care Compare website (https://www.medicare.gov/care-compare/) for the Five-Star Quality Rating System. We chose to align the specifications for the proposed measure with the specifications for the turnover measure being reported by NFs to reduce the reporting burden for SNFs under the SNF VBP.

Comment: One commenter suggested that CMS should collaborate with congressional leaders to provide additional funding to both State and Federal VBP programs instead of offering quality measures that are poorly conceived, like the Nursing Staff Turnover measure.

Response: As noted previously, we believe the Nursing Staff Turnover measure has strong reliability and validity, and the measure was strongly supported in recommendations made by the TEP convened by CMS contractors. For the SNF VBP Program, the Medicare Payment Advisory Commission (MedPAC) found, according to the 2023 Report to Congress on Medicare Payment Policy, that Medicare payments for SNFs were adequate in the latest year of available data. Additionally, this same report found that a combination of federal policies and the implementation of the new case-mix system resulted in improved financial performance for SNFs, indicating providing additional funding for SNFs unrelated to quality is not appropriate at this time. The goal of this Program is to incentivize high quality care. We believe the addition of the Nursing Staff Turnover measure helps us meet this goal because the measure displays a strong relationship to quality.

Comment: One commenter requested CMS amend the PBJ data submission policies to allow facilities to submit payroll data used to calculate the Nursing Staff Turnover measure after the submission deadline to allow SNFs to provide the most complete and accurate staffing data for consumers.

Response: We thank the commenter for their suggestion. This request would be a considerable update to our current policies around data submission that impacts programs beyond the SNF VBP Program. However, we will take it into consideration for future rulemaking.

After consideration of public comments, we are finalizing adoption of the Total Nursing Staff Turnover measure beginning with the FY 2026 SNF VBP program year.

c. Adoption of the Percent of Residents Experiencing One or More Falls With Major Injury (Long-Stay) Measure Beginning With the FY 2027 SNF VBP Program Year

We proposed to adopt the Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) Measure (“Falls with Major Injury (Long-Stay) measure”) beginning with the FY 2027 SNF VBP program year. The Falls with Major Injury (Long-Stay) measure is an outcome measure that estimates the percentage of long-stay residents who have experienced one or more falls with major injury. We refer readers to the specifications for this measure, which are located in the Minimum Data Set (MDS) 3.0 Quality Measures User's Manual Version 15 available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures. The Falls with Major Injury (Long-Stay) measure was endorsed by the consensus-based entity (CBE) in 2011. The measure is currently reported by nursing facilities under the CMS Nursing Home Quality Initiative (NHQI) and the Five-Star Quality Rating System and those results are publicly reported on the Care Compare website, available at https://www.medicare.gov/care-compare/.

(1) Background

Falls are the leading cause of injury-related death among persons aged 65 years and older. According to the Centers for Disease Control and Prevention (CDC), approximately one in four adults aged 65 years and older fall each year, and fall-related emergency department visits are estimated at approximately 3 million per year. In 2016, nearly 30,000 U.S. residents aged 65 years and older died as the result of a fall, resulting in an age-adjusted mortality rate of 61.6 deaths per 100,000 people. This represents a greater than 30 percent increase in fall-related deaths from 2007, where the age-adjusted mortality rate was 47.0 deaths per 100,000 people. Additionally, the death rate from falls was higher among adults aged 85 years and older as indicated by a mortality rate of 257.9 deaths per 100,000 people.

Of the 1.6 million residents in U.S. nursing facilities, approximately half fall annually, with one in three having two or more falls in a year. One in every ten residents who falls has a serious related injury, and about 65,000 residents suffer a hip fracture each year. An analysis of MDS data from FY 2019 Q2 found that, among the 14,586 nursing facilities included in the sample, the percent of long-stay residents who experienced one or more falls with major injury ranged from zero percent to nearly 21 percent. This wide variation in facility-level fall rates indicates a performance gap and suggests that there are opportunities to improve performance on this measure.

It is important to monitor injurious falls among the long-stay population because of the potentially negative impacts on resident health outcomes and quality of life. Research has found that injurious falls are one of the leading causes of disability and death for all nursing home residents. Specifically, falls have serious health consequences, such as reduced quality of life, decreased functional abilities, anxiety and depression, serious injuries, and increased risk of morbidity and mortality.

Injurious falls are also a significant cost burden to the entire healthcare system. The U.S. spends approximately $50 billion on medical costs related to non-fatal fall-related injuries and $754 million on medical costs related to fatal falls annually. Of the amount paid on non-fatal fall injuries, Medicare pays approximately $29 billion, while private or out-of-pocket payers pay $12 billion. Research suggests that acute care costs incurred for falls among nursing home residents range from $979 for a typical case with a simple fracture to $14,716 for a typical case with multiple injuries. Other research examining hospitalizations of nursing home residents with serious fall-related injuries (intracranial bleed, hip fracture, or other fracture) found an average cost of $23,723.

Research has found that 78 percent of falls are anticipated physiologic falls, which are defined as falls among individuals who scored high on a risk assessment scale, meaning their risk could have been identified in advance of the fall. To date, studies have identified a number of risk factors for falls within the long-stay population, including impaired cognitive function, history of falls, difficulties with walking and balancing, vitamin D deficiency, and use of psychotropic medications. In addition, residents who experience dementia or depression, are underweight, or are over the age of 85 are at a higher risk of falling. While much of this research has been conducted in long-term care facilities or nursing homes, we believe this research is relevant to the SNF setting, because approximately 94 percent of long-term care facilities are dually certified as both SNFs and nursing facilities (86 FR 42508). Therefore, these risk factors described above suggest that SNFs may be able to identify, reduce, and prevent the incidence of falls among their residents.

Given the effects of falls with major injury, preventing and reducing their occurrence in SNFs is critical to delivering safe and high-quality care. We believe the Falls with Major Injury (Long-Stay) measure aligns with this goal by monitoring the occurrence of falls with major injury and assessing SNFs on their performance on fall prevention efforts. In doing so, we believe this measure will promote patient safety and increase the transparency of care quality in the SNF setting, and it will align the Program with the Patient Safety domain of CMS' Meaningful Measures 2.0 Framework.

We believe there are effective interventions that SNFs can implement to reduce and prevent falls, including those that cause major injury. Specifically, several studies observed that multifactorial interventions such as exercise, medication review, risk assessment, vision assessment, and environmental assessment significantly reduce fall rates. Another study found that a single intervention of exercise reduced the number of resident falls in the nursing home setting by 36 percent and the number of recurrent fallers by 41 percent. Additionally, various systematic reviews link facility structural characteristics to falls with major injury. For example, the incorporation of adequate equipment throughout the facility, such as hip protectors or equipment used for staff education tasks, may reduce fall rates or fall-related injuries. In addition, poor communication between staff, inadequate staffing levels, and limited facility equipment have been identified as barriers to implementing fall prevention programs in facilities. Other studies have shown that proper staff education can significantly reduce fall rates. The effectiveness of these interventions suggest improvement of fall rates among SNF residents is possible through modification of provider-led processes and interventions, which supports the overall goal of the SNF VBP Program.

(2) Overview of Measure

The Falls with Major Injury (Long-Stay) measure is an outcome measure that reports the percentage of long-stay residents in a nursing home who have experienced one or more falls with major injury using 1 year of data from the Minimum Data Set (MDS) 3.0. This measure defines major injuries as bone fractures, joint dislocations, closed head injuries with altered consciousness, or subdural hematomas. Long-stay residents are defined as residents who have received 101 or more cumulative days of nursing home care by the end of the measure reporting period (performance period). This measure is a patient safety measure reported at the facility-level.

Although the Falls with Major Injury (Long-Stay) measure is a long-stay measure, we believe that including a long-stay measure in the SNF VBP Program is appropriate because it will better capture the quality of care provided to the entirety of the population that resides in facilities that are dually certified as SNFs and nursing facilities, including long-stay residents who continue to receive Medicare coverage for certain services provided by nursing facilities. We discussed the potential to include long -stay measures in the SNF VBP Program in the FY 2022 SNF PPS final rule Summary of Comments Received on Potential Future Measures for the SNF VBP Program (86 FR 42507 through 42510). Specifically, we stated that the majority of long-stay residents are Medicare beneficiaries, regardless of whether they are in a Medicare Part A SNF stay, because they are enrolled in Medicare Part B and receive Medicare coverage of certain services provided by long-term care facilities even if they are a long-stay resident. We did not receive any negative comments on inclusion of this specific Falls with Major Injury (Long-Stay) measure or long-stay measures generally in the Program in response to this request for comment.

We have adopted a similar measure in the SNF QRP, the Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long Stay) (80 FR 46440 through 46444), but that measure excludes long-stay residents. We believe it is important to hold SNFs accountable for the quality of care provided to long-stay residents given that the majority of long-term care facilities are dually certified as SNFs and nursing facilities. Additionally, we believe the Falls with Major Injury (Long-Stay) measure satisfies the requirement to consider and apply, as appropriate, quality measures specified under section 1899B(c)(1) of the Act, in which this measure aligns with the domain, incidence of major falls, described at section 1899B(c)(1)(D) of the Act. Therefore, we believe it is appropriate for the SNF VBP program to include a falls with major injury for long-stay resident measure.

Testing for this measure has demonstrated that the Falls with Major Injury (Long-Stay) measure has sufficient reliability and validity. For example, signal-to-noise and split-half reliability analyses found that the measure exhibited moderate reliability. Validity testing showed that there are meaningful differences in nursing facility-level scores for this measure, indicating good validity. For additional details on measure testing, we refer readers to the MAP PAC/LTC: 2022–2023 MUC Cycle Measure Specifications Manual available at https://mmshub.cms.gov/sites/default/files/map-pac-muc-measure-specifications-2022-2023.pdf.

(a) Interested Parties and TEP Input

In considering the selection of this measure for the SNF VBP Program, CMS convened a TEP in March 2022 which focused on the identification of measurement gaps and measure development priorities for the Program. Panelists were largely supportive of including a falls with major injury measure compared to a general falls measure or a falls with injury measure for several reasons including: (1) the broad definition of falls; and (2) the consensus-based entity endorsement of the Falls with Major Injury (Long-Stay) measure in the Nursing Home Quality Initiative Program. A summary of the TEP meeting is available at https://mmshub.cms.gov/sites/default/files/SNF-VBP-TEP-Summary-Report-Mar2022.pdf.

(b) Measure Applications Partnership (MAP) Review

We included the Falls with Major Injury (Long-Stay) measure as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List”. The MAP supported the Falls with Major Injury (Long-Stay) measure for rulemaking, noting that the measure would add value to the Program because of the lack of an existing falls measure and that it would help improve patient safety. We refer readers to the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.

(3) Data Sources

The Falls with Major Injury (Long-Stay) measure is calculated using 1 year of resident data collected through the MDS. The collection instrument is the Resident Assessment Instrument (RAI), which contains the MDS 3.0. The RAI is a tool used by nursing home staff to collect information on residents' strengths and needs. We describe the measure specifications in more detail below and also refer readers to the MDS 3.0 Quality Measures User's Manual Version 15.0 for further details on how these data components are utilized in calculating the Falls with Major Injury (Long-Stay) measure available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures. Technical information for the MDS 3.0 is also available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/NHQIMDS30TechnicalInformation. The Falls with Major Injury (Long-Stay) measure is calculated using data from the MDS, which all Medicare-certified SNFs and Medicaid-certified nursing facilities are currently required to report. Therefore, this measure will not impose any additional data collection or submission burden for SNFs.

(4) Measure Specifications

(a) Denominator

All long-stay residents with one or more look-back scan assessments no more than 275 days prior to the target assessment, except those that meet the exclusion criteria, are included in the measure denominator. Long-stay residents are defined as those who have 101 or more cumulative days of nursing home care by the end of the measure reporting period (performance period). Residents who return to the nursing home following a hospital discharge would not have their cumulative days in the facility reset to zero, meaning that days of care from a previous admission will be added to any subsequent admissions.

The MDS includes a series of assessments and tracking documents, such as Omnibus Budget Reconciliation Act (OBRA) Comprehensive Assessments, OBRA Quarterly Assessments, OBRA Discharge Assessments or PPS assessments. For the purposes of this measure, a target assessment, which presents the resident's status at the end of the episode of care or their latest status if their episode of care is ongoing, is selected for each long-stay resident. Target assessments may be an Omnibus Budget Reconciliation Act (OBRA) admission, quarterly, annual, or significant change/correction assessment; or PPS 5-day assessments; or discharge assessment with or without anticipated return. For more information on how we define target assessments, we refer readers to the MDS 3.0 Quality Measures User's Manual Version 15.0 available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures.

(b) Denominator Exclusions

Residents are excluded from the denominator if the number of falls with major injury was not coded for all of the look-back scan assessments. A SNF will not be scored on this measure if it does not have long-stay residents, or residents with 101 or more cumulative days of care. The measure also excludes all SNF swing beds because they do not provide care to long-stay residents.

(c) Numerator

The measure numerator includes long-stay residents with one or more look-back scan assessments that indicate one or more falls that resulted in major injury. Major injuries include bone fractures, joint dislocations, closed-head injuries with altered consciousness, or subdural hematomas. The selection period for the look-back scan consists of the target assessment and all qualifying earlier assessments in the scan.

An assessment should be included in the scan if it meets all of the following conditions: (1) it is contained within the resident's episode, (2) it has a qualifying Reason for Assessment (RFA), (3) its target date is on or before the target date for the target assessment, and (4) its target date is no more than 275 days prior to the target date of the target assessment. For the purposes of this measure, we defined the target date as the event date of an MDS record (that is, entry date for an entry record or discharge date for a discharge record or death-in-facility record) or the assessment reference date (for all records that are not entry, discharge, or death-in-facility). For additional target date details, we refer readers to Chapter 1 of the MDS 3.0 Quality Measures User's Manual Version 15.0 available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures.

A 275-day time period is used to include up to three quarterly OBRA assessments. The earliest of these assessments would have a look-back period of up to 93 days, which would cover a total of about 1 year. To calculate the measure, we scan these target assessments and any qualifying earlier assessments described in the previous paragraph for indicators of falls with major injury.

(5) Risk Adjustment

The Falls with Major Injury (Long-Stay) measure is not risk-adjusted. We considered risk adjustment during measure development, and we tested various risk-adjustment models, but none had sufficient predictive ability.

(6) Measure Calculation

The Falls with Major Injury (Long-Stay) measure is calculated and reported at the facility level. Specifically, to calculate the measure score, we proposed to first determine the measure denominator by identifying the total number of long-stay residents with a qualifying target assessment (OBRA, PPS, or discharge), one or more look-back scan assessments, and who do not meet the exclusion criteria. Using that set of residents, we calculate the numerator by identifying the total number of those residents with one or more look-back scan assessments that indicate one or more falls that resulted in major injury. We then divide the numerator by the denominator and multiply the resulting ratio by 100 to obtain the percentage of long-stay residents who experience one or more falls with major injury. A lower measure rate indicates better performance on the measure. For additional details on the calculation method, we refer readers to the specifications for the Falls with Major Injury (Long-Stay) measure included in the MDS 3.0 Quality Measures User's Manual available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures.

We solicited public comment on our proposal to adopt the Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) measure beginning with the FY 2027 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: Several commenters expressed support for the proposed Falls with Major Injury (Long-Stay) measure.

Response: We thank the commenters for their support.

Comment: Several commenters expressed concerns about the proposed measure. One commenter did not believe that MDS data were sufficiently valid for the SNF VBP program without an auditing program. One commenter expressed concern that the measure is not risk-adjusted. Another commenter was uncertain about the measure's use in the SNF VBP Program because it has not been adopted in the SNF QRP. One commenter did not believe that measures of long-stay residents' care were appropriate for the Program. Another commenter worried that facilities may restrict residents' movements to avoid falls and injuries, which would reduce residents' quality of life and affect their physical strength, balance, and flexibility.

Response: We thank the commenters for this feedback. We proposed to adopt a validation process for SNF VBP measures that are calculated using MDS data and refer readers to section VIII.G.4. of this final rule for additional details regarding that proposal, which we are finalizing, as well as our responses to comments on it.

We appreciate the commenter's concern about risk adjustment. As we explained in the proposed rule (88 FR 21371), we tested risk-adjustment models for this measure but found that none had sufficient predictive ability. Injurious falls are one of the leading causes of disability and death for all nursing home residents, and falls have serious health consequences, such as reduced quality of life, decreased functional abilities, anxiety and depression, serious injuries, and increased risk of morbidity and mortality. Based on these risks, we continue to believe that the measure is appropriate for adoption in the SNF VBP Program as part of our ongoing efforts to ensure nursing home residents' safety in that care setting. We will continue assessing the feasibility of risk-adjustment for this measure in the future.

We proposed to adopt this measure in the SNF VBP Program because falls represent a significant risk to nursing home residents. We believe that the SNF VBP Program's structure will provide strong incentives for SNFs to protect residents from those falls. We further note that, as we discussed in the proposed rule (88 FR 21370), we have adopted a similar measure for the SNF QRP. We also explained our reasoning for applying measures of long-stay residents' care in the proposed rule (88 FR 21370), where we stated that we believe long-stay measures better capture the quality of care provided to the entirety of the population residing in facilities that are dually certified as SNFs and nursing facilities. Even though Medicare Part A does not cover nursing facility stays, long-stay residents who are enrolled in Medicare Part B can still obtain Medicare Part B coverage of certain services, such as physical therapy, that are provided by nursing facilities.

Finally, while we agree with the commenter that no facility should restrict residents' movement to maximize its performance on this measure, we do not believe that

facilities will violate their duties to their residents' care and safety in such a manner. We believe that facilities will take appropriate steps to protect their residents from injurious falls while providing them with the support they need to maintain mobility, physical strength, balance, and flexibility. We further add that we are also adopting the DC Function measure, in which facilities must improve their resident function from admission to perform well on the measure which may reduce the incentive to restrict patient movements. We will monitor performance on the measure as well as potential unintended consequences carefully.

Comment: One commenter suggested that CMS monitor all injurious falls based on the risk of injury associated with them. The commenter also suggested that CMS adopt requirements for SNFs to develop protective interventions to protect residents from injury. Another commenter urged CMS to require Medicare Advantage (MA) plans to report falls data. One commenter suggested that CMS consider providing positive incentives for SNFs to encourage them to create falls management programs and protocols. One commenter expressed concern about the risk of facilities cherry-picking residents to avoid poor performance on this measure.

Response: We have not developed a measure of all falls for the SNF VBP Program at this time, nor are we aware of other measure developers having developed that type of measure. We will consider whether such a measure is appropriate for the Program in the future. We intend to work with Quality Improvement Organizations (QIOs) to promote safety initiatives in the nursing facility setting. Further, while we do not currently incorporate a measure of falls in our Star Ratings system for MA plans, we will consider whether such a measure would be appropriate in the future.

We note that patient safety is both one of the measure categories described at section 1888(h)(2)(A)(ii) and that prevention of falls specifically is a patient safety issue and one of the agency's priorities. We believe the positive incentives provided by the Program, including the policy changes we have proposed this year related to the Health Equity Adjustment and increase in payback percentage, provide strong incentives for SNFs to design and implement safety protocols, including falls management.

We share the commenter's concern about facilities' potentially cherry-picking residents to avoid poor performance on this measure and will monitor performance and any unintended consequences carefully.

Comment: Several commenters opposed the proposal to adopt the Falls with Major Injury (Long-Stay) measure. Some commenters were concerned that MDS data are not sufficiently accurate for quality measurement and suggested that CMS adopt a claims-based measure of falls instead. One commenter believed that the measure does not align with the SNF VBP Program's intent to link FFS reimbursement with care and outcomes of FFS beneficiaries. Another commenter opposed the measure's adoption based on population differences and suggested that CMS adopt the SNF QRP's Falls with Major Injury instead, which they stated is better aligned with Part A reimbursements affected by the SNF VBP Program. One commenter opposed the measure because it is already publicly reported and available to consumers.

Response: We appreciate the commenters' concerns. As explained below, we are finalizing a proposal to validate the MDS data used to calculate SNF VBP measures, and we believe that this policy will help to ensure that those data are accurate for quality purposes.

We disagree with the commenter's assertion that this measure does not align with the SNF VBP Program's intent. As we described in the proposed rule (88 FR 21370), we believe that this measure better captures the quality of care provided to the entirety of the population that resides in facilities that are dually certified as SNFs and nursing facilities, including long-stay residents who continue to receive Medicare coverage for certain services provided by nursing facilities. While we considered the SNF QRP's measure on a similar topic, we noted in the proposed rule that the SNF QRP's measure excludes long-stay residents and that we believe it is important to hold SNFs accountable for the quality of care they provide to long-stay residents since the majority of long-term care facilities are dually certified as SNFs and nursing facilities.

Finally, we agree with the commenter's reasoning that public reporting of quality data is an important feature of quality programs. We continue to believe, however, that providing financial incentives for quality performance through our pay-for-performance programs takes the next step beyond public reporting and provides direct incentives for quality improvement in clinical care.

After consideration of public comments, we are finalizing adoption of the Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) measure beginning with the FY 2027 SNF VBP program year.

d. Adoption of the Discharge Function Score Measure Beginning With the FY 2027 SNF VBP Program Year

We proposed to adopt the Discharge Function Score (“DC Function”) measure beginning with the FY 2027 SNF VBP Program. We also proposed to adopt this measure in the SNF QRP (see section VII. of this final rule).

(1) Background

Maintenance or improvement of physical function among older adults is increasingly an important focus of healthcare. Adults aged 65 years and older constitute the most rapidly growing population in the United States, and functional capacity in physical (non-psychological) domains has been shown to decline with age. Moreover, impaired functional capacity is associated with poorer quality of life and an increased risk of all-cause mortality, postoperative complications, and cognitive impairment, the latter of which can complicate the return of a resident to the community from post-acute care. Nonetheless, evidence suggests that physical

functional abilities, including mobility and self-care, are modifiable predictors of resident outcomes across PAC settings, including functional recovery or decline after post-acute care, rehospitalization rates, discharge to community, and falls. Because evidence shows that older adults experience aging heterogeneously and require individualized and comprehensive healthcare, functional status can serve as a vital component in informing the provision of healthcare and thus indicate a SNF's quality of care.

As stated in section VII. of this final rule, we proposed this measure for the SNF QRP, and we also proposed it for adoption in the SNF VBP Program under section 1888(h)(2)(A)(ii) of the Act. We believe it is important to measure quality across the full range of outcomes for Medicare beneficiaries during a SNF stay. Further, adoption of this measure will ensure that the SNF VBP Program's measure set aligns with the Person-Centered Care domain of CMS' Meaningful Measures 2.0 Framework.

We included the DC Function measure on the 2022–2023 MUC list for the Inpatient Rehabilitation Facility QRP, Home Health QRP, Long Term Care Hospital QRP, SNF QRP, and SNF VBP Program. While the DC Function measure is not yet implemented in the SNF QRP or other PAC programs, SNFs already report many of the elements that will be used to calculate this measure. As such, we believe SNFs have had sufficient time to ensure successful reporting of the data elements needed for this measure.

(2) Overview of Measure

The DC Function measure is an outcome measure that estimates the percentage of SNF residents who meet or exceed an expected discharge score during the reporting period. The DC Function measure's numerator is the number of SNF stays with an observed discharge function score that is equal to or higher than the calculated expected discharge function score. The observed discharge function score is the sum of individual function items at discharge. The expected discharge function score is computed by risk adjusting the observed discharge function score for each SNF stay. Risk adjustment controls for resident characteristics, such as admission function score, age, and clinical conditions. The denominator is the total number of SNF stays with a MDS record in the measure target period (four rolling quarters) which do not meet the measure exclusion criteria. For additional details regarding the numerator, denominator, risk adjustment, and exclusion criteria, we refer readers to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report.

The DC Function measure implements a statistical imputation approach for handling “missing” standardized functional assessment data elements. The coding guidance for standardized functional assessment data elements allows for using “Activity Not Attempted” (ANA) codes, resulting in “missing” information about a patient's functional ability on at least some items, at admission and/or discharge, for a substantive portion of SNF patients. Currently, functional outcome measures in the SNF QRP use a simple imputation method whereby all ANA codes or otherwise missing scores, on both admission and discharge records, are recoded to “1” or “most dependent.” Statistical imputation, on the other hand, replaces these missing values for a variable based on the values of other, non-missing variables in the data and which are otherwise similar to the assessment with a missing value. Specifically, the DC Function measure's statistical imputation allows missing values (for example, the ANA codes) to be replaced with any value from 1 to 6, based on a patient's clinical characteristics and codes assigned on other standardized functional assessment data elements. The measure implements separate imputation models for each standardized functional assessment data elements used in measure construction at admission and discharge. Relative to the current simple imputation method, this statistical imputation approach increases the precision and accuracy and reduces the bias in estimates for missing item scores. We refer readers to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report for measure specifications and additional details. We also refer readers to the SNF QRP section VII.C.1.b.(1) of this final rule for additional information on Measure Importance and Measure Testing.

(a) Interested Parties and TEP Input

We convened two TEP meetings (July 2021 and January 2022), as well as a Patient and Family Engagement Listening Session, to collect feedback from interested parties on the measure's potential use in quality programs in the future. The TEP members expressed support for the measure's validity and agreed with the conceptual and operational definition of the measure.

The feedback we received during the Patient and Family Engagement Listening Session demonstrated that this measure resonates with patients and caregivers. For example, participants' views of self-care and mobility were aligned with the functional domains captured by the measure, and participants found that those domains included critical aspects of care in post-acute care settings. Participants also emphasized the importance of measuring functional outcomes when assessing quality for SNF residents. We refer readers to the SNF QRP section VII.C.1.b.(3) of this final rule for additional discussion on the TEP.

(b) MAP Review

The DC Function measure was included as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List.” The MAP offered conditional support of the DC Function measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure will add value to the Program because there are currently no measures related to functional status in the Program, and this measure serves as an indicator for whether the care provided is effective and high quality. We refer readers to section VII.C.1.b.(4) of this final rule for further details on the MAP's recommendations and the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.

We solicited public comment on our proposal to adopt the Discharge Function Score measure beginning with the FY 2027 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: Many commenters supported adoption of the DC Function measure in the SNF VBP Program because it assesses performance on both self-care and mobility items. One commenter stated that implementing the measure in the FY 2027 program year allows SNFs enough time to evaluate their current performance on the measure.

Response: We thank the commenters for their feedback. We also note that many of the same commenters expressed support for the inclusion of this measure in both the SNF QRP and SNF VBP. We responded to those more general comments in section VII.C.1.b. of this final rule.

Comment: One commenter supported the proposal to adopt this measure for the SNF VBP Program, but they recommended that the measure be scored on the resident's change in the DC Function score so that the Program rewards facilities based on the degree of a resident's improvement in function rather than if they met or exceeded an expected discharge score.

Response: We appreciate the commenter's recommendation however, we believe the measure as proposed is the best measure for the Program at this time because it has strong reliability and validity, has received positive feedback from a TEP and other interested parties, and has high reportability and usability. We also do not believe at this time that rewarding facilities for any improvement in resident function, especially those residents who may not achieve a discharge function benchmark, are sufficient incentives for improving the quality of care for SNF residents. While we agree that it is important for facilities to track the amount of change that occurs over the course of a stay for its residents, we would like to point out that “Change in Score” measures are not as intuitive to interpret because the units of change and what constitutes a meaningful change has not been determined for residents with differing diagnoses and clinical complexities that seek care at SNFs. This is in contrast to the proposed Discharge Function Score measure which is presented as a simple proportion.

As stated in section VII.C.1.b.(3) of the proposed rule, a TEP was convened and asked whether they prefer a measure that is modeled after the currently adopted Discharge Mobility Score and Discharge Self Care Score measures, or one that is modeled after the currently adopted Change in Mobility Score and Change in Self Care Score measures. We note that the Discharge Mobility Score and Change in Mobility Score measures were highly correlated and did not appear to measure unique concepts. The Discharge Self Care Score and Change in Self Care Score measures were also highly correlated and did not appear to measure unique concepts. Because both the discharge and change measure types did not appear to measure unique concepts, the TEP favored the Discharge Mobility Score and Discharge Self Care Score measures over the Change in Mobility Score and Change in Self Care Score measures. Based on the TEP's recommendation to our contractor, we made a policy decision to pursue the DC Function measure for the measure of functional status in the SNF VBP Program.

Comment: A few commenters who supported the DC Function measure recommended that CMS include the expected discharge function score, a score that is already calculated during the measure evaluation, along with the observed function score on the provider reports, so that providers have transparency into their performance.

Response: We will take this feedback into consideration as we develop our quarterly confidential feedback reports that are provided after the end of the data submission period. We also note that many of the same commenters expressed this recommendation for both the SNF QRP and SNF VBP. We responded to those comments in section VII.C.1.b. of this final rule.

Comment: A few commenters did not support the adoption of the DC Function measure in the SNF VBP Program because the MDS-data are not validated for accuracy, and providers have not had enough time using the measure prior to use in a performance-based program.

Response: We thank the commenters for their feedback. As explained below, we are finalizing a proposal to validate the MDS data used to calculate SNF VBP measures, and we believe that this policy will help to ensure that those data are accurate for quality purposes. As stated in section VII.F.2 of this final rule, the SNF QRP is adopting this measure in FY 2025 SNF QRP year with data collection beginning with October 1, 2023 discharges. We are finalizing the adoption of this measure for the SNF VBP Program beginning with the FY 2027 program year, with data collection beginning with October 1, 2024 discharges. This timeline will enable SNFs to report the data for a full year in the SNF QRP before they are required to report them for the SNF VBP Program. We believe that reporting this measure in the SNF QRP for one year is sufficient time for providers to gain familiarity with the measure. As we stated in the proposed rule (88 FR 21372), the DC Function measure contains similar data elements to the Discharge Self-Care Score and Discharge Mobility Score measures, which have been included in the SNF QRP measure set for several years. We believe that SNFs are well acquainted with the Self-Care Score and Discharge Mobility Score measures so adopting the DC Function measure at a similar time for both the SNF QRP and SNF VBP Program is reasonable. We also note that many of the same commenters did not support the inclusion of this measure in both the SNF QRP and SNF VBP Program. We responded to those more general comments in section VII.C.1.b. of this final rule.

Comment: One commenter believed that SNFs will need to update their software in order to create and implement the measure's complex calculations, as well as to monitor the expected and observed discharge function score progression. This commenter also stated SNFs will need to provide additional training and education for clinical and administrative personnel with the adoption of new measures.

Response: We interpret the commenter to be saying that SNFs will need to update their software to perform the measure calculations prior to receiving the CMS generated reports, as well as provide training and education to their clinical staff on the DC Function measure and their administrative personnel on reporting the data or monitoring the data.

We acknowledge the commenter's concern regarding updating software; however, SNFs are not required to update their own software to successfully report the MDS items or monitor their performance on the DC Function measure. Additionally, we disagree that the adoption of the proposed measure would result in additional burden or require additional training. We did not propose to change the items SNFs report for the measure calculation nor the frequency at which SNFs would report these items. In fact, this measure uses the same set of MDS items that SNFs have been reporting at admission and discharge since October 1, 2018. We also will calculate this measure and provide SNFs with various educational resources on the DC Function measure they can use in preparation for reviewing and monitoring their own performance on this measure, thus eliminating the need for SNFs to create training and education for their clinical and administrative personnel.

After consideration of public comments, we are finalizing adoption of the Discharge Function Score measure for the SNF VBP Program beginning with the FY 2027 program year.

e. Adoption of the Number of Hospitalizations per 1,000 Long-Stay Resident Days Measure Beginning With the FY 2027 SNF VBP Program Year

(1) Background

Unplanned hospitalizations of long-stay residents can be disruptive and burdensome to residents. “They can cause discomfort for residents, anxiety for loved ones, morbidity due to iatrogenic events, and excess healthcare costs.” Studies have found that many unplanned hospitalizations could have been safely avoided by early intervention by the facility. For example, one structured review by expert clinicians of hospitalizations of SNF residents found that two-thirds were potentially avoidable, citing a lack of primary care clinicians on-site and delays in assessments and lab orders as primary reasons behind unplanned hospitalizations. Another study found that standardizing advanced care planning and physician availability has a considerable impact on reducing hospitalizations. The Missouri Quality Initiative reduced hospitalizations by 30 percent by having a clinical resource embedded to influence resident care outcomes. Another study found that reducing hospitalizations did not increase the mortality risk for long-stay nursing home residents.

A review of data that were publicly reported on Care Compare shows that there is considerable variation in performance across nursing homes when it comes to unplanned hospitalizations, suggesting that improvement is possible through modification of facility-led processes and interventions. Specifically, performance on this measure ranges from 0.841 hospital admissions per 1,000 long-stay resident days at the 10th percentile to 2.656 hospital admissions per 1,000 long-stay resident days at the 90th percentile. In other words, the top decile of performers (10th percentile) has less than half the number of hospitalizations compared to the bottom decile (90th percentile). We also reported in 2020 that the rate of unplanned hospitalizations was 1.4 per 1,000 nursing home resident days, suggesting these disruptive events are fairly common. Adopting this measure will align measures between Care Compare and the SNF VBP program without increasing the reporting burden.

Although the Long Stay Hospitalization measure is not specified under section 1899B(c)(1) of the Act, it aligns with the topics listed under section 1888(h)(2)(A)(ii) of the Act. We believe this outcome measure supports the Program's goals to improve the quality of care provided to Medicare beneficiaries throughout their entire SNF stay. Furthermore, the measure will align the Program with the Care Coordination domain of CMS' Meaningful Measures 2.0 Framework.

We examined the relationship between long-stay hospitalization rates and other measures of quality from CMS' Five-Star Quality Rating System using data from the December 2019 Nursing Home Compare update. Analyses showed that facilities with lower hospitalization rates tend to perform better on other dimensions of quality such as health inspection survey results, staffing level, other quality measures, and overall ratings.

Although the Long Stay Hospitalization measure is a long-stay measure, we believe that including a long-stay measure in the SNF VBP Program is appropriate because it will better capture the quality of care provided to the entirety of the population that resides in facilities that are dually certified as SNFs and nursing facilities, including long-stay residents who continue to receive Medicare coverage for certain services provided by nursing facilities. We discussed the potential of including long-stay measures in the SNF VBP Program in the FY 2022 SNF PPS final rule Summary of Comments Received on Potential Future Measures for the SNF VBP Program (86 FR 42507 through 42510). Specifically, we stated that the majority of long-stay residents are Medicare beneficiaries, regardless of whether they are in a Medicare Part A SNF stay, because they are enrolled in Medicare Part B and receive Medicare coverage of certain services provided by long-term care facilities even if they are a long-stay resident. We did not receive any negative comments on inclusion of this specific Long Stay Hospitalization measure or long-stay measures generally in the Program in response to the request for comment.

(2) Overview of Measure

The Long Stay Hospitalization measure calculates the number of unplanned inpatient admissions to an acute care hospital or critical access hospital, or outpatient observation stays that occurred among long-stay residents per 1,000 long-stay resident days using 1 year of Medicare fee-for-service (FFS) claims data. A long-stay day is defined as any day after a resident's one-hundredth cumulative day in the nursing home or the beginning of the 12-month target period (whichever is later) and until the day of discharge, the day of death, or the end of the 12-month target period (whichever is earlier). We proposed to risk adjust this measure, as explained in more detail below.

(a) Measure Applications Partnership (MAP) Review

We included the Long Stay Hospitalization measure in the publicly available “2022 Measures Under Consideration List.” The MAP offered conditional support of the Long Stay Hospitalization measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure will add value to the Program because unplanned hospitalizations are disruptive and burdensome to long-stay residents. We refer readers to the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.

(3) Data Sources

The Long Stay Hospitalization measure is calculated using Medicare FFS claims data. We use the inpatient hospital claims data to determine the hospital admission, outpatient hospital claims data to determine the outpatient observation stay, and items from the Minimum Data Set for building resident stays and for risk-adjustment.

(4) Inclusion and Exclusion Criteria

All Medicare beneficiaries enrolled in both Part A and Part B are included. The measure excludes any resident enrolled in Medicare managed care during any portion of the resident's stay. The measure also excludes all days and any hospital admissions during which the resident was enrolled in hospice.

The measure does not count days prior to a resident's 101st cumulative day, which is when the resident meets long-stay criteria. Furthermore, we do not include any long-stay days prior to the beginning of the applicable performance period. For example, if a resident becomes a long-stay resident on September 25, 2024, and is discharged on October 5, 2024, we would only count 5 days in the denominator during the performance period for the FY 2027 program year.

Any days a resident was not in the facility for any reason will not be counted in the denominator, defined as the total observed number of long stay days at the facility. This means we do not count in the denominator any days the resident is admitted to another type of inpatient facility, or days temporarily residing in the community, so long as the NF with beds that are also certified as SNF beds submits an MDS discharge assessment for the temporary discharge. For example, if a resident became a long-stay resident on December 20, but stayed with family on December 24 and December 25 but returned to the facility on December 26, we would not count those two days (24 and 25) in the denominator because the NF with beds that are also certified as SNF beds completed an MDS discharge assessment. We would also not count the days when a resident was admitted to a hospital, and therefore, is not residing at the facility in the denominator.

We will not count an observed hospitalization of a resident, the numerator count, if the hospitalization occurred while the resident was not in the facility and had a completed MDS discharge assessment for the temporary discharge. In the example in the prior paragraph, if the resident was admitted to the hospital on December 25, during which they were residing with family with a completed MDS temporary discharge assessment, the admission would not be counted as a hospitalization for the NF with beds that are also certified as SNF beds (in the numerator). If, however, the resident returned to the NF with beds that are also certified as SNF beds on December 26 and was admitted to the hospital on December 27, then it would count as a hospitalization (in the numerator).

If a resident spends 31 or more days in a row residing outside the NF with beds that are also certified as SNF beds, which could be in another facility or in the community, we will consider the resident discharged and they will no longer meet long-stay status. If a resident is discharged and then admitted to the same facility within 30 days, we will consider the resident still in a long-stay status, and we will count the days in this admission in the measure denominator.

The measure numerator includes all admissions to an acute care hospital or critical access hospital, for an inpatient or outpatient observation stay, that occur while the resident meets the long-stay status criteria. Observation stays are included in the numerator regardless of diagnosis. Planned inpatient admissions are not counted in the numerator since they are unrelated to the quality of care at the facility. Hospitalizations are classified as planned or unplanned using the same version of CMS' Planned Readmissions Algorithm that is used to calculate the percentage of short-stay residents who were re-hospitalized after a nursing home admission in the Nursing Home Compare Five-Star Rating System. The algorithm identifies planned admission using the principal discharge diagnosis category and all procedure codes listed on inpatient claims, coded using the AHRQ Clinical Classification System (CCS) software.

(5) Risk Adjustment

The risk adjustment model used for this measure is a negative binomial regression. Specifically, we proposed to risk adjust the observed number of hospitalizations after the resident met the long-stay status to determine the expected number of hospitalizations for each long-stay resident given the resident's clinical and demographic profile. The goal of risk adjustment is to account for differences across facilities in medical acuity, functional impairment, and frailty of the long-stay residents but not factors related to the quality of care provided by the facility. The data for the risk adjustment model are derived from Medicare inpatient claims data prior to the day the resident became a long-stay resident and from the most recent quarterly or comprehensive MDS assessment within 120 days prior to the day the resident became a long-stay resident.

The risk adjustment variables derived from the claims-based data include age, sex, number of hospitalizations in the 365 days before the day the resident became a long-stay resident or beginning of the 1-year measurement period (whichever is later), and an outcome-specific comorbidity index. The MDS-based covariates span multiple domains including functional status, clinical conditions, clinical treatments, and clinical diagnoses.

We refer readers to the measure specifications for additional details on the risk-adjustment model for this measure available at https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/CertificationandComplianc/Downloads/Nursing-Home-Compare-Claims-based-Measures-Technical-Specifications-April-2019.pdf.

(6) Measure Calculation

To get the risk adjusted rate (risk standardized rate), we take the observed Long Stay Hospitalization rate divided by the expected Long Stay Hospitalization rate, multiplied by the national Long Stay Hospitalization rate, as shown by the following formula:

The observed Long Stay Hospitalization rate is the actual number of hospital admissions or observation stays that met the previously discussed inclusion criteria divided by the actual total number of long-stay days that met the previously discussed inclusion criteria divided by 1,000 days. The observed rate is shown by the following formula:

The expected Long Stay Hospitalization rate is the expected number of hospital admission or observation stays that were calculated using the risk adjustment methodology discussed in section VIII.B.4.e.(5) of this final rule, divided by the actual total number of long-stay days that met the previously discussed inclusion criteria divided by 1,000 days. The expected Long Stay Hospitalization rate is shown by the following formula:

The national Long Stay Hospitalization rate is the total number of inpatient hospital admission or observation stays meeting the numerator criteria, divided by the total number of all long stay days that met the denominator criteria divided by 1,000. The national Long Stay Hospitalization rate is shown by the following formula:

We refer readers to the measure specifications for additional details for this measure calculation available at https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/CertificationandComplianc/Downloads/Nursing-Home-Compare-Claims-based-Measures-Technical-Specifications-April-2019.pdf.

We solicited public comment on our proposal to adopt the Number of Hospitalizations per 1,000 Long-Stay Resident Days measure beginning with the FY 2027 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: Several commenters expressed support for the proposal to adopt the measure. One commenter suggested that CMS monitor rates of hospitalization for long-stay residents to assess whether this measure will remain appropriate in the long-term.

Response: We thank the commenters for their support. We agree with the suggestion and intend to monitor all SNF VBP Program measures to ensure that they remain relevant to the care quality provided to Medicare beneficiaries in this setting.

Comment: Some commenters supported the measure's adoption but expressed concerns about its use in the Program. One commenter wondered what this measure adds to the Program that isn't captured by the proposed SNF WS PPR measure. Another commenter stated its belief that CMS should focus the SNF VBP Program on Medicare Part A patients, which does not include long-stay residents, because the Program itself affects payments for Part A services. Two commenters were concerned that the measure excludes Medicare Advantage residents, thus not covering a significant portion of Medicare beneficiaries.

Response: We thank the commenters for their feedback. As we stated in the proposed rule (88 FR 21373 through 21374), our analysis of the relationship between long-stay hospitalization rates and other measures of quality from CMS's Five-Star Quality Rating System showed that facilities with lower hospitalization rates tend to perform better on other dimensions of quality such as health inspection survey results, staffing level, other quality measures, and overall ratings. We further explained our reasoning for including a long-stay measure in the SNF VBP Program in the proposed rule (88 FR 21370), where we stated that we believe long-stay measures better capture the quality of care provided to the entirety of the population that resides in facilities that are dually certified as SNFs and nursing facilities. Long-stay residents who are enrolled in Medicare Part B receive Medicare Part B coverage for certain services provided by nursing facilities. We believe that presenting more quality information for beneficiaries helps improve the care they receive and the health system generally. We would also like to clarify that the SNF WS PPR assesses readmission rates for SNF residents who are admitted to a short-stay acute care hospital or long-term care hospital with a principal diagnosis considered to be unplanned and potentially preventable while within SNF care, while the Long-Stay Hospitalization measure focuses on the risks experienced by long-stay residents. We therefore view these measures as complementary assessments of readmissions in dually certified facilities. The majority of long-stay residents are enrolled in Medicare Part B. For those residents, Medicare Part B provides coverage of certain services, such as physical therapy, that are provided by the nursing facility. We therefore believe that the measure is appropriate for the Program.

We also appreciate commenters' concerns about Medicare Advantage residents. However, we would like to clarify that our Star Ratings system provides quality information to Medicare beneficiaries about the care they receive from the specific facility regardless of whether the beneficiary is enrolled in the Medicare FFS program or in a Medicare Advantage plan. We are also interested in including Medicare Advantage beneficiaries in the measure's calculations, but Medicare Advantage claims are not generally available for our use on the same timing or in the same way that FFS claims are used to calculate this measure.

Comment: Some commenters opposed the proposal to adopt this measure. One commenter did not believe the measure aligned with the Program's intent to link Medicare FFS reimbursement with care and outcomes experienced by Medicare FFS beneficiaries. A few commenters were concerned about assessing facilities using long-stay measures for a short-stay Medicare benefit. One commenter worried that the measure would impose additional burdens on SNFs.

Response: We thank the commenters for this feedback. However, as we explained in the proposed rule (88 FR 21373 through 21374), performance on the Long Stay Hospitalization measure is correlated with numerous other measures of quality in the SNF sector, meaning that, in our view, the measure supports quality improvement in the SNF sector. We continue to believe that measures like this one provide significant benefits to Medicare beneficiaries.

We would also like to clarify that the Long Stay Hospitalization measure is calculated using Medicare claims data, so it imposes no additional reporting or validation burden on SNFs.

After consideration of public comments, we are finalizing adoption of the Number of Hospitalizations per 1,000 Long-Stay Resident Days measure beginning with the FY 2027 SNF VBP program year.

f. Scoring of SNF Performance on the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), and Long Stay Hospitalization Measures

(1) Background

In the FY 2017 SNF PPS final rule (81 FR 52000 through 52001), we finalized a policy to invert SNFRM measure rates such that a higher measure rate reflects better performance on the SNFRM. In that final rule, we also stated our belief that this inversion is important for incentivizing improvement in a clear and understandable manner because a “lower is better” rate could cause confusion among SNFs and the public. In the FY 2023 SNF PPS final rule (87 FR 47568), we applied this policy to the SNF HAI measure such that a higher measure rate reflects better performance on the SNF HAI measure. We also stated our intent to apply this inversion scoring policy to all measures in the Program for which the calculation produces a “lower is better” measure rate. We continue to believe that inverting measure rates such that a higher measure rate reflects better performance on a measure is important for incentivizing improvement in a clear and understandable manner.

This measure rate inversion scoring policy does not change the measure specifications or the calculation method. We use this measure rate inversion as part of the scoring methodology under the SNF VBP Program. The measure rate inversion is part of the methodology we use to generate measure scores, and resulting SNF Performance Scores, that are clear and understandable for SNFs and the public.

(2) Inversion of the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), and Long Stay Hospitalization Measures Rates for SNF VBP Program Scoring Purposes

In sections VII.B.4.b., VII.B.4.c., and VII.B.4.e. of the proposed rule, we stated that a lower measure rate for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measures indicate better performance on those measures. Therefore, we proposed to apply our measure rate inversion scoring policy to these measures. We proposed to calculate the score for these measures for the SNF VBP Program by inverting the measure rates using the calculations shown in Table 16. We did not propose to apply this policy to the DC Function measure because that measure, as currently specified and calculated, produces a “higher is better” measure rate.

We believe that inverting the measure rates for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measure is important for incentivizing improvement in a clear and understandable manner, and for ensuring a consistent message that a higher measure rate reflects better performance on the measures.

We solicited public comment on our proposal to invert the measure rates for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measures for the purposes of scoring under the SNF VBP Program.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: One commenter supported the proposal to invert the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measure rates for SNF VBP program scoring purposes because the proposal is important for incentivizing improvement in a clear and understandable manner, and for ensuring a consistent message that a higher measure rate reflects better performance.

Response: We thank this commenter for their support. We agree that this proposed score inversion will provide a clearer depiction of quality in our performance scoring.

Comment: One commenter recommended that in addition to the proposed inversion of the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measure rates for SNF VBP Program scoring purposes, non-inverted rates be included in feedback reports to providers to help them track their performance relative to benchmark rates in their quality improvement effort.

Response: We thank this commenter for their recommendation. We note that we currently include the non-inverted rates for the SNFRM in the quarterly confidential feedback reports, and we intend to continue that practice for all new measures for which we invert the measure rates for scoring purposes. As mentioned in the proposed rule (88 FR 21376), the measure rate inversion is solely part of the methodology we use to generate measure scores and resulting SNF Performance Scores.

Comment: One commenter opposed the proposal to invert the nursing staff turnover, falls with major injury (long-stay), and long stay hospitalization measure rates for SNF VBP program scoring purposes. This commenter believes the proposed score inversion overly complicates an already complex quality initiative. The commenter further expressed that the application of inverted scores is inconsistent with public reporting for other measures.

Response: We believe that our policy to invert measure rates such that a higher measure rate reflects better performance is important for incentivizing improvement through clear and understandable SNF Performance Scores. This measure rate inversion scoring policy is only used for the purposes of generating SNF Performance Scores under the SNF VBP Program's scoring methodology. The measure rate inversions do not change the measure specifications and are not publicly reported.

After consideration of public comments, we are finalizing our proposal to invert the measure rates for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measures for the purposes of scoring under the SNF VBP Program.

g. Confidential Feedback Reports and Public Reporting for Quality Measures

Our confidential feedback reports and public reporting policies are codified at § 413.338(f) of our regulations. In the FY 2023 SNF PPS final rule (87 FR 47591 through 47592), we revised our regulations such that the confidential feedback reports and public reporting policies apply to each measure specified for a fiscal year, which includes the Nursing Staff Turnover measure beginning with the FY 2026 program year, and the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year.

We did not propose any changes to these policies in the proposed rule.

C. SNF VBP Performance Periods and Baseline Periods

1. Background

We refer readers to the FY 2016 SNF PPS final rule (80 FR 46422) for a discussion of our considerations for determining performance periods and baseline periods under the SNF VBP Program. In the FY 2019 SNF PPS final rule (83 FR 39277 through 39278), we adopted a policy whereby we will automatically adopt the performance period and baseline period for a SNF VBP program year by advancing the performance period and baseline period by 1 year from the previous program year. In the FY 2023 SNF PPS final rule (87 FR 47580 through 47583), we adopted performance periods and baseline periods for three new quality measures beginning with the FY 2026 program year: (1) SNF HAI measure, (2) Total Nurse Staffing measure, and (3) DTC PAC SNF measure, and finalized the application of our policy to automatically adopt performance periods and baseline periods for subsequent program years to those new measures.

2. SNFRM Performance and Baseline Periods for the FY 2024 SNF VBP Program Year

Under the policy finalized in the FY 2019 SNF PPS final rule (83 FR 39277 through 39278), the baseline period for the SNFRM for the FY 2024 program year would be FY 2020 and the performance period for the SNFRM for the FY 2024 program year would be FY 2022. However, in the FY 2022 SNF PPS final rule (85 FR 42512 through 42513), we updated the FY 2024 baseline period for the SNFRM to FY 2019 since the ECE we granted on March 22, 2020, due to the PHE for COVID–19, excepted qualifying claims for a 6-month period in FY 2020 (January 1, 2020 through June 30, 2020) from the calculation of the SNFRM. We refer readers to that final rule for additional discussion of our considerations for updating the FY 2024 baseline period for the SNFRM. Therefore, for the FY 2024 program year, the baseline period for the SNFRM is FY 2019 and the performance period for the SNFRM is FY 2022.

3. Performance Periods and Baseline Periods for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization Measures

a. Performance Periods for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization Measures

In considering the appropriate performance periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures, we recognize that we must balance the length of the performance periods with our need to calculate valid and reliable performance scores and announce the resulting payment adjustments no later than 60 days prior to the program year involved, in accordance with section 1888(h)(7) of the Act. In addition, we refer readers to the FY 2017 SNF PPS final rule (81 FR 51998 through 51999) for a discussion of the factors we should consider when specifying performance periods for the SNF VBP Program, as well as our stated preference for 1-year performance periods. Based on these considerations, we believe that 1-year performance periods for these measures would be operationally feasible for the SNF VBP Program and would provide sufficiently accurate and reliable measure rates and resulting performance scores for the measures.

We also recognize that we must balance our desire to specify performance periods for a fiscal year as close to the fiscal year's start date as possible to ensure clear connections between quality measurement and value-based payment with our need to announce the net results of the Program's adjustments to Medicare payments not later than 60 days prior to the fiscal year involved, in accordance with section 1888(h)(7) of the Act. In considering these constraints, and in alignment with other SNF VBP measures, we believe that performance periods that occur 2 fiscal years prior to the applicable fiscal program year is most appropriate for these measures.

For these reasons, we proposed to adopt the following performance periods:

• FY 2024 (October 1, 2023 through September 30, 2024) as the performance period for the Nursing Staff Turnover measure for the FY 2026 SNF VBP program year.
• FY 2025 (October 1, 2024, through September 30, 2025) as the performance period for the Falls with Major Injury (Long-Stay) measure for the FY 2027 SNF VBP program year.
• FY 2025 (October 1, 2024 through September 30, 2025) as the performance period for the DC Function measure for the FY 2027 SNF VBP program year.
• FY 2025 (October 1, 2024 through September 30, 2025) as the performance period for the Long Stay Hospitalization measure for the FY 2027 SNF VBP program year.

In alignment with the previously adopted SNF VBP measures, we also proposed that, for these measures, we will automatically adopt the performance period for a SNF VBP program year by advancing the beginning of the performance period by 1 year from the previous program year.

We solicited public comment on our proposals to adopt performance periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. We provide a summary of the comments we received and our responses in the next section. As stated in that section, we are finalizing the performance periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures.

b. Baseline Periods for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization Measures

In the FY 2016 SNF PPS final rule (80 FR 46422) we discussed that, as with other Medicare quality programs, we generally adopt baseline periods for a fiscal year that occurs prior to the performance periods for that fiscal year to establish measure performance standards. We also discussed our intent to adopt baseline periods that are as close as possible in duration as performance periods for a fiscal year, as well as our intent to seasonally align baseline periods with performance periods to avoid any effects on quality measurement that may result from tracking SNF performance during different times in a year. Therefore, to align with the performance period length for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures, we proposed to adopt 1-year baseline periods for those measures.

We also recognize that we are required, under section 1888(h)(3)(C) of the Act, to calculate and announce performance standards no later than 60 days prior to the start of performance periods. Therefore, we believe that baseline periods that occur 4 fiscal years prior to the applicable fiscal program year, and 2 fiscal years prior to the performance periods, is most appropriate for these measures and will provide sufficient time to calculate and announce performance standards prior to the start of the performance periods.

For these reasons, we proposed to adopt the following baseline periods:

• FY 2022 (October 1, 2021 through September 30, 2022) as the baseline period for the Nursing Staff Turnover measure for the FY 2026 SNF VBP program year.
• FY 2023 (October 1, 2022 through September 30, 2023) as the baseline period for the Falls with Major Injury (Long-Stay) measure for the FY 2027 SNF VBP program year.
• FY 2023 (October 1, 2022 through September 30, 2023) as the baseline period for the DC Function measure for the FY 2027 SNF VBP program year.
• FY 2023 (October 1, 2022 through September 30, 2023) as the baseline period for the Long Stay Hospitalization measure for the FY 2027 SNF VBP program year.

In alignment with the previously adopted SNF VBP measures, we also proposed that, for these measures, we will automatically adopt the baseline period for a SNF VBP program year by advancing the beginning of the baseline period by 1 year from the previous program year.

We solicited public comment on our proposals to adopt baseline periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: One commenter supported the performance periods and baseline periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures as proposed.

Response: We thank the commenter for their support of the performance periods and baseline periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures.

After consideration of public comments, we are finalizing the performance periods and baseline periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures.

4. Performance Periods and Baseline Periods for the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

a. Performance Periods for the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

The SNF WS PPR measure is calculated using 2 consecutive years of Medicare FFS claims data, and therefore, we proposed to adopt a 2-year performance period for this measure. During the re-specification process for the SNF WS PPR measure, we determined that using 2 years of data improved the measure reliability. Specifically, the intraclass correlation coefficient (with the Spearman-Brown correction applied) for the SNF WS PPR measure was 0.71 compared to 0.56 for the SNFRM. We refer readers to section VIII.B.2. of this final rule and the SNF WS PPR measure technical specifications, available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf, for additional details.

Accordingly, we proposed to adopt October 1, 2024 through September 30, 2026 (FY 2025 and FY 2026) as the performance period for the SNF WS PPR measure for the FY 2028 SNF VBP program year. We believe that using October 1, 2024 through September 30, 2026 (FY 2025 and FY 2026) as the performance period for the FY 2028 program year best balances our need for sufficient data to calculate valid and reliable performance scores with our requirement under section 1888(h)(7) of the Act to announce the resulting payment adjustments no later than 60 days prior to the program year involved.

In alignment with the previously adopted SNF VBP measures, we also proposed that for the SNF WS PPR measure, we will automatically adopt the performance period for a SNF VBP program year by advancing the beginning of the performance period by 1 year from the previous program year.

We solicited public comment on our proposals related to the performance periods for the SNF WS PPR measure beginning with the FY 2028 program year. We provide a summary of the comments we received and our responses in the next section. As stated in that section, we are finalizing the performance periods for the SNF WS PPR measure beginning with the FY 2028 program year.

b. Baseline Periods for the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

Our policy is to generally adopt a baseline period for a fiscal year that occurs prior to the performance period for that fiscal year in order to establish a measure's performance standards. We also generally adopt baseline periods that are as close as possible in duration as the performance period for a fiscal year, as well as seasonally aligning the baseline periods with performance periods to avoid any effects on quality measurement that may result from tracking SNF performance during different times in a year. Therefore, to align with the performance period length for the SNF WS PPR measure, we proposed a 2-year baseline period for this measure.

We also recognize that we are required, under section 1888(h)(3)(C) of the Act, to calculate and announce performance standards no later than 60 days prior to the start of the performance period. Therefore, we believe that a baseline period that begins 6 fiscal years prior to the applicable fiscal program year, and 3 fiscal years prior to the applicable performance period, is most appropriate for the SNF WS PPR measure and will provide sufficient time to calculate and announce performance standards prior to the start of the performance period. For these reasons, we proposed to adopt October 1, 2021 through September 30, 2023 (FY 2022 and FY 2023) as the baseline period for the SNF WS PPR measure for the FY 2028 SNF VBP program year.

In alignment with the previously adopted SNF VBP measures, we also proposed that for the SNF WS PPR measure, we will automatically adopt the baseline period for a SNF VBP program year by advancing the beginning of the baseline period by 1 year from the previous program year.

We solicited public comment on our proposals related to the baseline periods for the SNF WS PPR measure beginning with FY 2028 program year.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: One commenter supported the proposed performance periods and baseline periods for the SNF WS PPR measure.

Response: We thank the commenter for their support of the performance periods and baseline periods for the SNF WS PPR measure beginning with the FY 2028 program year.

After consideration of public comments, we are finalizing the performance periods and baseline periods for the SNF WS PPR measure beginning with the FY 2028 program year.

c. SNFRM and SNF WS PPR Performance Period and Baseline Period Considerations

As discussed in the previous section, we are finalizing our proposal that the first performance period for the SNF WS PPR measure will be October 1, 2024 through September 30, 2026 (FY 2025 and FY 2026), and the first baseline period will be October 1, 2021 through September 30, 2023 (FY 2022 and FY 2023). In section VIII.B.3. of this final rule, we are finalizing our proposal to replace the SNFRM with the SNF WS PPR beginning with the FY 2028 program year. Therefore, the last program year that will include the SNFRM will be FY 2027. The last performance period for the SNFRM will be FY 2025 and the last baseline period will be FY 2023. We note that because the SNF WS PPR measure is a 2-year measure and the SNFRM is a 1-year measure, the data used to calculate the baseline and performance period for the SNF WS PPR measure for the FY 2028 program year will include data that is also used to calculate the baseline and performance period for the SNFRM for the FY 2027 program year. We believe the overlap is necessary to ensure that we can transition from the SNFRM to the SNF WS PPR seamlessly, without any gaps in the use of either measure.

D. SNF VBP Performance Standards

1. Background

We refer readers to the FY 2017 SNF PPS final rule (81 FR 51995 through 51998) for a summary of the statutory provisions governing performance standards under the SNF VBP Program and our finalized performance standards policy. In the FY 2019 SNF PPS final rule (83 FR 39276 through 39277), we also adopted a policy allowing us to correct the numerical values of the performance standards. Further, in the FY 2023 SNF PPS final rule (87 FR 47583 through 47584), we amended the definition of “Performance Standards,” redesignated that definition as § 413.338(a)(12) and added additional detail for our performance standards correction policy at § 413.338(d)(6).

We adopted the final numerical values for the FY 2024 performance standards in the FY 2022 SNF PPS final rule (86 FR 42513) and adopted the final numerical values for the FY 2025 performance standards in the FY 2023 SNF PPS final rule (87 FR 47584).

We did not propose any changes to these performance standards policies.

2. Performance Standards for the FY 2026 Program Year

In the FY 2023 SNF PPS final rule (87 FR 47564 through 47576), we adopted two new quality measures for the FY 2026 program year: SNF HAI and Total Nurse Staffing measures. In section VIII.B.4.b. of this final rule, we are also finalizing adoption of the Nursing Staff Turnover measure beginning with the FY 2026 program year. We are finalizing that the performance period for the Nursing Staff Turnover measure for the FY 2026 program year will be FY 2024 (October 1, 2023 through September 30, 2024). Therefore, the FY 2026 program year will consist of four measures (SNFRM, SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures).

To meet the requirements at section 1888(h)(3)(C) of the Act, we are providing the final numerical performance standards for the FY 2026 program year for the three previously adopted measures (SNFRM, SNF HAI, and Total Nurse Staffing measures), as well as the Nursing Staff Turnover measure. In accordance with our previously finalized methodology for calculating performance standards (81 FR 51996 through 51998), the final numerical values for the FY 2026 program year performance standards are shown in Table 17.

3. Performance Standards for the DTC PAC SNF Measure for the FY 2027 Program Year

In the FY 2023 SNF PPS final rule (87 FR 47576 through 47580), we adopted the DTC PAC SNF measure beginning with the FY 2027 program year. In that final rule (87 FR 47582 through 47583), we also finalized that the baseline and performance periods for the DTC PAC SNF measures would be 2 consecutive years, and that FY 2024 and FY 2025 would be the performance period for the DTC PAC SNF measure for the FY 2027 program year.

To meet the requirements at section 1888(h)(3)(c) of Act, we are providing the final numerical performance standards for the DTC PAC SNF measure for the FY 2027 program year. In accordance with our previously finalized methodology for calculating performance standards (81 FR 51996 through 51998), the final numerical values for the DTC PAC SNF measure for the FY 2027 program year performance standards are shown in Table 18.

We note that we will provide the estimated numerical performance standard values for the remaining measures applicable in the FY 2027 program year in the FY 2025 SNF PPS proposed rule.

E. SNF VBP Performance Scoring Methodology

1. Background

Our performance scoring policies are codified at § 413.338(d) and (e) of our regulations. We also refer readers to the following prior final rules for detailed background on the scoring methodology for the SNF VBP Program:

• In the FY 2017 SNF PPS final rule (81 FR 52000 through 52005), we finalized several scoring methodology policies, including a policy to use the higher of a SNF's achievement and improvement scores as that SNF's performance score for a given program year.
• In the FY 2018 SNF PPS final rule (82 FR 36614 through 36616), we finalized: (1) a rounding policy, (2) a logistic exchange function, (3) a 60 percent payback percentage, and (4) a SNF performance ranking policy.
• In the FY 2019 SNF PPS final rule (83 FR 39278 through 39281), we finalized several scoring methodology policies, including a scoring policy for SNFs without sufficient baseline period data and an extraordinary circumstances exception policy.
• In the FY 2022 SNF PPS final rule (86 FR 42513 through 42515), we finalized a special scoring and payment policy for the FY 2022 SNF VBP Program due to the impact of the PHE for COVID–19.

• In the FY 2023 SNF PPS final rule (87 FR 47584 through 47590), we finalized a special scoring and payment policy for the FY 2023 SNF VBP Program due to the continued impact of the PHE for COVID–19. In that final rule, we also finalized several scoring methodology policies to accommodate the addition of new measures to the Program, including: (1) case minimum and measure minimum policies, including case minimums for the SNFRM, SNF HAI, Total Nurse Staffing, and DTC PAC SNF measures, (2) updates to the scoring policy for SNFs without sufficient baseline period data, (3) removal of the low-volume adjustment policy, and (4) a measure-level and normalization scoring policy to replace the previously adopted scoring methodology policies beginning with the FY 2026 program year.

2. Case Minimum and Measure Minimum Policies

a. Background

We refer readers to the FY 2023 SNF PPS final rule (87 FR 47585 through 47587) for a detailed description of our considerations for adopting case minimums and measure minimums. Our case minimum and measure minimum policies are also codified at § 413.338(b) of our regulations.

We proposed to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year; the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year; and the SNF WS PPR measure beginning with the FY 2028 program year. Therefore, we also proposed to adopt case minimums for the new measures and proposed to update the previously finalized measure minimum for the FY 2027 program year. Although the addition of the Nursing Staff Turnover measure beginning with FY 2026 will increase the total number of measures for that program year, we believe that the previously finalized measure minimum of two measures remains sufficient for that program year.

b. Case Minimums During a Performance Period for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, Long Stay Hospitalization, and SNF WS PPR Measures

We proposed to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year; the Falls with Major Injury (Long-Stay), Long Stay Hospitalization, and DC Function measures beginning with the FY 2027 program year; and the SNF WS PPR measure beginning with the FY 2028 program year. Therefore, to meet the requirements at section 1888(h)(1)(C)(i) of the Act, we also proposed to adopt case minimums for those proposed measures.

For the Nursing Staff Turnover measure, we proposed that SNFs must have a minimum of 1 eligible stay during the 1-year performance period and at least 5 eligible nursing staff (RNs, LPNs, and nurse aides) during the 3 quarters of PBJ data included in the measure denominator. SNFs must meet both of these requirements in order to be eligible to receive a score on the measure for the applicable program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses and the measure specifications. For example, using FY 2021 data, we estimated that 80 percent of SNFs met the 5-eligible nursing staff minimum. In addition, we note that the 1-eligible stay and 5-eligible nursing staff minimums were determined to be appropriate for publicly reporting this measure on the Care Compare website.

For the Falls with Major Injury (Long-Stay) measure, we proposed that SNFs must have a minimum of 20 residents in the measure denominator during the 1-year performance period to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, using FY 2021 data, we estimated that nearly 96 percent of SNFs met the 20-resident minimum. In addition, testing results indicated that a 20-resident minimum produced moderately reliable measure rates for the purposes of public reporting.

For the Long Stay Hospitalization measure, we proposed that SNFs must have a minimum of 20 eligible stays during the 1-year performance period to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, using CY 2021 data, we estimated that approximately 80 percent of SNFs met the 20-eligible stay minimum. In addition, we note that the 20-eligible stay minimum was determined to be appropriate for publicly reporting this measure under the Five-Star Quality Rating System.

For the DC Function measure, we proposed that SNFs must have a minimum of 20 eligible stays during the 1-year performance period in order to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, testing results, which used FY 2019 data, found that nearly 84 percent of SNFs met the 20-eligible stay minimum. In addition, those testing results indicated that a 20-eligible stay minimum produced sufficiently reliable measure rates.

For the SNF WS PPR measure, we proposed that SNFs must have a minimum of 25 eligible stays during the 2-year performance period in order to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, using FY 2020 through FY 2021 data, we estimated that nearly 91 percent of non-swing bed SNFs met the 25-eligible stay minimum. In addition, testing results indicated that a 25-eligible stay minimum produced sufficiently reliable measure rates.

We believe these case minimum standards for public reporting purposes are also appropriate standards for establishing a case minimum for these measures under the SNF VBP Program. We also believe these case minimum requirements support our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on these measures.

We solicited public comment on our proposal to adopt case minimums for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), Long Stay Hospitalization, DC Function, and SNF WS PPR measures.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: One commenter supported the proposed case minimums during a performance period for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, Long Stay Hospitalization, and SNF WS PPR measures based on the rationale that the proposed case minimums are appropriate and consistent with measure testing analyses and appropriately balance quality measure reliability with the desire to score as many SNFs as possible on these measures, which is further detailed in section VII.E.2. of the proposed rule (88 FR 21379 through 21380).

Response: We thank the commenters for their support. We agree that these case minimums are consistent with the findings of the measure testing analyses we referenced in section VII.E.2. of the proposed rule (88 FR 21379 through 21380), and support our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on these measures.

Comment: One commenter recommended that CMS adopt case minimum requirements that meet a reliability standard of 0.7. This commenter further recommended that CMS could expand the number of SNFs meeting this higher reliability standard by including multiple years in a performance period, adding that more recent years could be weighted more heavily than preceding years.

Response: We believe that the proposed case minimums ensure that SNF VBP measures are sufficiently reliable for purposes of scoring and payment adjustments under the Program. Our testing has also indicated that increasing the case minimum requirements to achieve the reliability standard of 0.7 would result in minimal improvements to a measure's reliability while simultaneously increasing the number of SNFs that would not meet the higher case minimum requirement, which does not align with our goal to ensure as many SNFs as possible have the opportunity to receive a score on a given measure. Therefore, we do not believe it is currently necessary or feasible to adopt case minimum requirements that meet a reliability standard of 0.7.

We acknowledge the commenter's recommendation to increase measure reliability using longer performance periods and baseline periods and agree that this could increase measure reliability. However, we stated our preference in the FY 2016 SNF PPS final rule (80 FR 46422) and the FY 2017 SNF PPS final rule (81 FR 51998 through 51999), to adopt 1-year performance and baseline periods because that length of time typically provides sufficient levels of data accuracy and reliability for scoring performance, while also allowing us to link SNF performance on a measure as closely as possible to the payment year to ensure clear connections between quality measurement and value-based payment. Where appropriate, we have extended the performance periods and baseline periods for purposes of improving individual measure reliability. For example, in section VIII.C.4. of this final rule, we are finalizing 2-year performance periods and baseline periods for the SNF WS PPR measure because our analytical testing found that using 2-years of data improve the measure's statistical reliability relative to one year of data. In finalizing the 2-year performance periods and baseline periods for the SNF WS PPR measure, we believe that we are appropriately balancing measure reliability with recency of data. We intend to continue considering the balance of these factors when proposing performance periods and baseline periods for any future SNF VBP measure.

After consideration of public comments, we are finalizing the case minimums for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), Long Stay Hospitalization, DC Function, and SNF WS PPR measures.

c. FY 2026 Measure Minimum

In the FY 2023 SNF PPS final rule (87 FR 47587), we finalized the measure minimum for the FY 2026 program year. Specifically, we finalized that for the FY 2026 program year, SNFs must report the minimum number of cases for two of the three measures during the applicable performance period to receive a SNF Performance Score and value-based incentive payment.

We proposed to adopt an additional measure for the FY 2026 program year: Nursing Staff Turnover measure, which means the FY 2026 SNF VBP measure set will consist of a total of four measures. Although we proposed the Nursing Staff Turnover measure beginning with the FY 2026 program year, which will increase the total number of measures applicable in FY 2026, we believe that our previously finalized minimum of two measures for FY 2026 remains sufficient because if we required a minimum of three or four measures, all swing-bed facilities would be excluded from the Program. Two of the four measures that will be included in the FY 2026 program year are PBJ-based measures. Since swing-bed facilities do not submit PBJ data, those facilities will not meet the measure minimum of reporting three or four measures to the Program. Therefore, to ensure swing-bed facilities continue to have the opportunity to be included in the Program, we did not propose to update the measure minimum for the FY 2026 program year. SNFs must report the minimum number of cases for two of the four measures during the performance period to be included in the FY 2026 program year.

While we did not propose any changes to the measure minimum for FY 2026, we did receive one comment. The following is a summary of the comment and our response.

Comment: One commenter supported the measure minimum for FY 2026.

Response: We thank the commenter for their support of the measure minimum for FY 2026.

d. Updates to the FY 2027 Measure Minimum

In the FY 2023 SNF PPS final rule (87 FR 47587), we finalized the measure minimum for the FY 2027 program year. Specifically, we finalized that for the FY 2027 program year, SNFs must report the minimum number of cases for three of the four measures during the performance period to receive a SNF Performance Score and value-based incentive payment.

In addition to the Nursing Staff Turnover measure beginning with the FY 2026 program year, we also proposed to adopt three additional measures beginning with the FY 2027 program year: Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. Therefore, the FY 2027 SNF VBP measure set will consist of a total of eight measures. Given the changes to the number of measures applicable in FY 2027, we also proposed to update the measure minimum for the FY 2027 program year.

Specifically, we proposed that for the FY 2027 program year, SNFs must report the minimum number of cases for four of the eight measures during the performance period to receive a SNF Performance Score and value-based incentive payment. SNFs that do not meet these minimum requirements will be excluded from the FY 2027 program and will receive their adjusted Federal per diem rate for that fiscal year. Under these measure minimum requirements, we estimate that approximately 8 percent of SNFs would be excluded from the FY 2027 Program. We found that increasing the measure minimum requirement from three to four measures out of a total of eight measures would cause the number of SNFs excluded from the Program to increase from approximately 3 percent to 8 percent of SNFs for FY 2027. However, the measure minimum requirement that we finalized for FY 2027 in the FY 2023 SNF PPS final rule (87 FR 47587), which was based on a measure set of four measures, excluded approximately 16 percent of SNFs. We also found that increasing the measure minimum requirement would have little effect on the percentage of SNFs that would receive a net-positive incentive payment multiplier (IPM) of the overall distribution of IPMs. Based on these testing results, we believe the updates to the measure minimum for FY 2027 aligns with our desire to ensure that as many SNFs as possible can receive a reliable SNF Performance Score and value-based incentive payment.

We solicited public comment on our proposal to update the measure minimum for the FY 2027 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: One commenter supported the proposed FY 2027 measure minimum.

Response: We thank the commenter for their support of the updated measure minimum for FY 2027.

After consideration of public comments, we are finalizing the update to the measure minimum for the FY 2027 SNF VBP program year.

3. Application of the SNF VBP Scoring Methodology to Proposed Measures

a. Background

In the FY 2023 SNF PPS final rule (87 FR 47588 through 47590), we finalized several updates to the scoring methodology for the SNF VBP Program beginning with the FY 2026 program year. We finalized a measure-level scoring policy such that SNFs have the opportunity to earn a maximum of 10 points on each measure for achievement, and a maximum of nine points on each measure for improvement. The higher of these two scores will then be the SNF's score for each measure and used to calculate the SNF Performance Score, except if the SNF does not meet the case minimum for a given measure during the applicable baseline period, in which case that SNF will only be scored on achievement for that measure. We also finalized a normalization policy such that we will calculate a raw point total for each SNF by adding up that SNF's score on each of the measures applicable for the given program year. We will then normalize the raw point totals such that the SNF Performance Score is reflected on a 100-point scale.

We proposed to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year; and the Falls with Major Injury (Long-Stay), Long Stay Hospitalization, and DC Function measures beginning with the FY 2027 program year. To accommodate those measures in our scoring methodology, we proposed to adjust our scoring methodology for the FY 2026 and FY 2027 program years, which we discuss in the next section.

We also note that we proposed to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year, which will not affect the total number of measures applicable in the Program for FY 2028. We intend to address the FY 2028 performance scoring methodology in future rulemaking.

b. FY 2026 Performance Scoring

We proposed the Nursing Staff Turnover measure beginning with the FY 2026 program year, and therefore, the FY 2026 program year measure set will include four measures (SNFRM, SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures).

We proposed to apply our previously finalized scoring methodology, which is codified at § 413.338(e) of our regulations, to the Nursing Staff Turnover measure. Specifically, we will award up to 10 points based on achievement, and up to nine points based on improvement, so long as the SNF meets the case minimum for the measure. The higher of these two scores will be the SNF's score for the measure for FY 2026, except in the instance that the SNF does not meet the case minimum for the measure during the applicable baseline period, in which case that SNF will only be scored on achievement for the measure.

As previously finalized, we will then add the score for each of the four measures for which the SNF met the case minimum to get the raw point total. The maximum raw point total for the FY 2026 program year will be 40 points. We will then normalize each SNF's raw point total, based on the number of measures for which that SNF met the case minimum, to get a SNF Performance Score that is on a 100-point scale using our previously finalized normalization policy. We will only award a SNF Performance Score to SNFs that meet the measure minimum for FY 2026.

We solicited public comment on our proposal to apply our previously finalized scoring methodology to the Nursing Staff Turnover measure beginning with the FY 2026 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: One commenter, while supporting the FY 2026 performance scoring methodology proposal, disagrees with the using the mean of the top decile of SNFs during the baseline period as the benchmark performance standard.

Response: In the FY 2017 SNF PPS final rule (81 FR 51996 through 51997) we stated that our finalized definition of the benchmark represents a demonstrably high but achievable standard of excellence for all SNFs. We refer readers to that final rule for additional details on that policy. We continue to believe that our definition of the benchmark is appropriate for incentivizing high-quality care across SNFs.

Comment: One commenter opposed the FY 2026 performance scoring proposal and recommended that CMS score SNFs on achievement only.

Response: We disagree with the recommendation to score SNFs on achievement only as we are required under section 1888(h)(3)(B) of the Act to include levels of achievement and improvement in the performance standards we use to assess SNF performance under the SNF VBP.

After consideration of public comments, we are finalizing the application of our previously finalized scoring methodology to the Nursing Staff Turnover measure beginning with the FY 2026 SNF VBP program year.

c. FY 2027 Performance Scoring

We proposed the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year, and therefore, the FY 2027 program year measure set will include eight measures.

Our current scoring methodology is codified at § 413.338(e) of our regulations. Under that scoring methodology, we award up to 10 points for each measure based on achievement, and up to nine points for each measure based on improvement, so long as the SNF meets the case minimum for a given measure. The higher of these two scores is the SNF's score on that measure for FY 2027, except in the instance that the SNF does not meet the case minimum for a given measure during the applicable baseline period, in which case that SNF is only scored on achievement for that measure. As previously finalized, we then sum the scores for each of the eight measures for which the SNF met the case minimum to get the raw measure point total. The maximum raw measure point total for the FY 2027 program year will be 80 points.

We proposed to apply these elements of the scoring methodology to Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. In addition, and as discussed further in section VIII.E.4. of this final rule, we proposed to adopt a Health Equity Adjustment in which eligible SNFs could earn a maximum of two points for each measure (including all previously finalized and newly proposed measures) if they are a top tier performing SNF, which we proposed to define as a SNF whose score on the measure for the program year falls in the top third of performance (greater than or equal to the 66.67th percentile) on a given measure, and the SNF's resident population during the performance period that applies to the program year includes at least 20 percent of residents with dual eligibility status (DES). This combination of a SNF's performance and proportion of residents with DES would be used to determine a SNF's Health Equity Adjustment (HEA) bonus points. We would then add the total number of HEA bonus points to the normalized measure point total on a scale from 0 to 100, and that total would be the SNF Performance Score earned by the SNF for the program year. We will only award a SNF Performance Score to SNFs that meet the proposed measure minimum for FY 2027.

We solicited public comment on our proposal to apply our previously finalized scoring methodology to the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 SNF VBP program year.

We received public comments on this proposal. The following is a summary of the comments we received on our proposal to apply our previously finalized scoring methodology to the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures and our responses. We provide a summary of comments related to the Health Equity Adjustment, and our responses, in section VIII.E.4. of this final rule.

Comment: A few commenters supported the proposal to apply the previously finalized scoring methodology to the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year noting that these changes are needed to accommodate the new quality measures in the SNF VBP Program scoring methodology.

Response: We thank the commenters for their support. We agree that applying our scoring methodology to these measures will incentivize high-quality care across all SNFs.

Comment: One commenter, while supporting the FY 2027 performance scoring methodology proposal, disagrees with the using the mean of the top decile of SNFs during the baseline period as the benchmark performance standard.

Response: In the FY 2017 SNF PPS final rule (81 FR 51996 through 51997) we stated that our finalized definition of the benchmark represents a demonstrably high but achievable standard of excellence for all SNFs. We refer readers to that final rule for additional details on that policy. We continue to believe that our definition of the benchmark is appropriate for incentivizing high-quality care across SNFs.

After consideration of public comments, we are finalizing our proposal to apply our previously finalized scoring methodology to the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 SNF VBP program year.

4. Incorporating Health Equity Into the SNF VBP Program Scoring Methodology Beginning With the FY 2027 Program Year

a. Background

Significant and persistent inequities in health outcomes exist in the U.S. Belonging to a racial or ethnic minority group; living with a disability; being a member of the lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI+) communities; living in a rural area; being a member of a religious minority; being near or below the poverty level; or being dually enrolled in Medicare and Medicaid, is often associated with worse health outcomes. Executive Order 13985 on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government, (January 20, 2021) defines “equity” as “the consistent and systematic fair, just, and impartial treatment of all individuals, including individuals who belong to underserved communities that have been denied such treatment, such as Black, Latino, and Indigenous and Native American persons, Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; lesbian, gay, bisexual, transgender, queer, [and intersex] (LGBTQ[I] +); persons with disabilities; persons who live in rural areas; and persons otherwise adversely affected by persistent poverty or inequality” (86 FR 7009). CMS defines “health equity” as the “attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes.”

Advancing health equity is a key pillar of our strategic vision, and we are working to advance health equity by designing, implementing, and operationalizing policies and programs aimed at identifying and reducing health disparities. This includes the CMS Mapping Medicare Disparities Tool, the CMS Innovation Center's Accountable Health Communities Model, the CMS Disparity Methods stratified reporting program, the collection of standardized patient assessment data elements in the post-

acute care setting, and health equity program adjustments like the Medicare Shared Savings Program's recently adopted health equity adjustment for Accountable Care Organizations that report all-payer eCQMs/MIPS CQMs (87 FR 69838 through 69857). Further, the 2022–2032 CMS Framework for Health Equity outlines CMS' priorities to advance health equity, expand coverage, and improve health outcomes for the more than 170 million individuals supported by CMS programs. We also recently updated the CMS National Quality Strategy (NQS), which includes advancing health equity as one of eight strategic goals. As we continue to leverage our programs to improve quality of care, we note it is important to implement strategies that “create aligned incentives that drive providers to improve health outcomes for all beneficiaries.”

Prioritizing the achievement of health equity is essential in the SNF VBP Program because disparities in SNFs appear to be widespread, from admissions to quality of care to nurse staffing and turnover. In the 2016 Report to Congress, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) reported that individuals with social risk factors, such as dual eligibility status, had worse outcomes and were more likely to be cared for by lower-quality SNFs. Individuals with dual eligibility status (DES) are those who are eligible for both Medicare and Medicaid coverage. Individuals with DES are more likely to have disabilities or functional impairments, more likely to be medically complex, more likely to have greater social needs, and have a greater risk of negative health outcomes compared to individuals without DES. They are also more likely to be admitted to SNFs that have lower staffing levels, have a higher share of residents who are enrolled in Medicaid in their total resident population, and experience resource constraints. In addition, studies have found that DES is an important predictor of admission to a low-quality SNF. All of these factors indicate that individuals with DES represent an underserved population that is more clinically complex, has greater social needs and is more often admitted to lower-resourced SNFs than those without DES. This presents significant challenges to provide quality care to patients with greater resource-intensive needs by providers that may have fewer resources, as effectively implementing quality improvement initiatives requires time, money, staff, and technology. As a result, competitive programs, like the current SNF VBP Program, may place some SNFs that serve this underserved population at a disadvantage.

In the FY 2023 SNF PPS proposed rule (87 FR 22789), we requested public comment on policy changes that we should consider on the topic of health equity. In the FY 2023 SNF PPS final rule (87 FR 47596 through 47597), we provided a detailed summary of the feedback we received on this topic. Commenters overwhelmingly supported our commitment to advancing health equity for SNF residents, with some suggesting that we examine factors that may lead to care inequities. One commenter suggested we adopt risk adjustment or incentive payments for SNFs that admit individuals that other SNFs will not admit. Another commenter recommended pairing clinical data measures with social risk metrics to help providers deliver more comprehensive care. Overall, commenters were interested in understanding where disparities may exist and wanted us to work with SNFs and other interested parties to understand the greatest needs in achieving health equity to ensure any revisions to the Program could be implemented with minimal data burden. We considered all the comments we received as we developed our Health Equity Adjustment for the SNF VBP Program described below.

We believe that SNFs and providers across all settings can consistently perform well even when caring for a high proportion of individuals who are underserved, and, with the right program components, VBP programs can create meaningful incentives for SNFs that serve a high proportion of individuals who are underserved to

deliver high quality care. We believe updating the scoring methodology, as detailed in the following sections, would appropriately measure performance and create these meaningful incentives for SNFs that care for a high proportions of residents with DES.

b. Health Equity Adjustment Summary

Section 1888(h)(4)(A) of the Act requires the Secretary to develop a methodology for assessing the total performance of each SNF based on performance standards established under section 1888(h)(3) of the Act with respect to the measures applied under section 1888(h)(2) of the Act. To further align with our goals to achieve health equity, address health disparities, and assess SNF performance more accurately and completely under the SNF VBP Program, we proposed to apply an adjustment that will be added to the normalized sum of a SNF's measure points on SNF VBP Program measures. As described previously, residents with DES are an underserved population that is clinically complex, has significant social needs and is more frequently admitted to SNFs that have larger populations of Medicaid residents and fewer resources than SNFs that do not care for individuals with DES. These lower-resourced SNFs are less likely to receive positive payment adjustments, which is a considerable limitation of the current SNF VBP program's ability to incentivize equitable care. Careful consideration must be taken to modify the Program in a way that addresses this issue and ensures that we provide appropriate rewards and incentives to all SNFs, including those that serve residents with DES. The goal of this Health Equity Adjustment is to not only appropriately measure performance by rewarding SNFs that overcome the challenges of caring for higher proportions of SNF residents with DES but also to incentivize those who have not achieved such high-quality care to work towards improvement. We believe this Health Equity Adjustment incentivizes high-quality care across all SNFs. We also believe this scoring change, through the adoption of an adjustment designed to award points based on the quality of care provided and the proportion of residents with DES, is consistent with our strategy to advance health equity.

The Health Equity Adjustment (HEA) will be calculated using a methodology that considers both the SNF's performance on the SNF VBP Program measures, and the proportion of residents with DES out of the total resident population in a given program year at each SNF. To be eligible to receive HEA bonus points, a SNF's performance will need to meet or exceed a certain threshold and its resident population during the applicable performance period for the program year will have to include at least 20 percent of residents with DES. Thus, SNFs that perform well on quality measures and serve a higher proportion of SNF residents with DES will receive a larger adjustment. We provide the HEA calculation methodology in section VIII.E.4.d. of this final rule. By providing this HEA to SNFs that serve higher proportions of SNF residents with DES and that perform well on quality measures, we believe we can appropriately recognize the resource intensity expended to achieve high performance on quality measures by SNFs that serve a high proportion of SNF residents with DES, while also mitigating the worse health outcomes experienced by underserved populations through incentivizing better care across all SNFs.

An analysis of payment from October 2018 for the SNF VBP Program found that SNFs that served higher proportions of Medicaid residents were less likely to receive positive payment adjustments. As noted previously, residents with DES are more likely to be admitted to SNFs with higher proportions of Medicaid residents suggesting that SNFs serving higher proportions of SNF residents with DES face challenges in utilizing their limited resources to improve the quality of care for their complex residents. Thus, we aimed to adjust the current program scoring methodology to ensure that all SNF residents, including those with DES, receive high-quality care. We conducted an analysis utilizing FY 2018 through FY 2021 measure data for our previously finalized and newly proposed measures, including a simulation of performance on all 8 measures for the FY 2027 Program, and found that the HEA significantly increased the proportion of SNFs with high proportions of SNF residents with DES that received a positive value-based incentive payment adjustment indicating that this approach would modify the SNF VBP Program in the way it is intended.

We proposed to call this adjustment the Health Equity Adjustment (HEA) and to adopt it beginning with the FY 2027 program year.

c. Health Equity Adjustment Beginning With the FY 2027 SNF VBP Program Year

We proposed to define the term “underserved population” as residents with DES for purposes of this HEA. DES has been established in the literature, including research specifically looking at SNFs, and has been found to be an important factor that impacts pay for performance and other quality programs. In addition, DES is currently utilized in the Hospital Readmissions Reduction Program.

The Medicare Shared Savings Program recently adopted a health equity adjustment for Accountable Care Organizations that report all-payer eCQMs/MIPS CQMs, are high-performing on quality, and serve a large proportion of underserved beneficiaries, as defined by dual-eligibility/enrollment in the Medicare Part D low income subsidy (LIS) (meaning the individual is enrolled in a Part D plan and receives LIS) and an Area Deprivation Index (ADI) score of 85 or above, as detailed in the CY 2023 PFS final rule (87 FR 69838 through 69857). At this time, for the SNF VBP Program's HEA, we believe that it is preferable to use DES to identify SNF residents who are underserved. We also explored alternative indicators to identify populations that are underserved for purposes of this HEA, such as a resident's eligibility for the Medicare Part D Low-Income Subsidy (LIS) program or whether the resident lives in an area with high deprivation, as measured by the Area Deprivation Index (ADI), however, we determined that for the HEA, utilizing residents with DES to identify underserved populations will best serve the goals of the adjustment. Individuals who are eligible for the LIS program have incomes up to 150 percent of the Federal poverty level. Utilizing residents who are eligible for the LIS program would include most residents with DES, as well as additional residents who may be underserved; however, the data on the LIS program are only available for those enrolled in Medicare Part D, which may limit its effectiveness, and it is not uniform across both States and territories. Further, those eligible for the LIS program have not been studied extensively in the SNF setting and the effect of using those eligible for the LIS program to determine a SNF's underserved population has also not been studied extensively. Geographic-based or neighborhood-level economic indices, such as the ADI, have been utilized to look at characteristics of healthcare facilities in low-resourced areas and could be used as a proxy for negative health outcomes due to medical and social risk factors. ADI appears to be an important predictor of poor health outcomes, even when adjusting for individual characteristics, suggesting neighborhood or geography may play an even more important role in health than individual characteristics. However, there is not much literature or analysis that has been conducted linking these indices to negative health outcomes specifically in the SNF setting. Therefore, we proposed to only use DES data at this time to identify SNF residents who are underserved for this HEA, given that the DES data are readily available, are evidenced based in the SNF setting, and are already used in the Hospital Readmissions Reduction Program. We intend to consider how to best incorporate the LIS, ADI, and other indicators to identify those who are underserved in future health equity adjustment proposals for the SNF VBP Program as more research is made available. We solicited public comment, and provide a summary of the comments we received, on the potential future use of these additional indicators in section VIII.E.5 of this final rule. We provide additional detail on how we will calculate SNF residents with DES for the purpose of this adjustment later in this section.

In order to calculate the HEA, we first proposed to assign each SNF 2 points for each measure for which it is a top tier performing SNF. We proposed to define a top tier performing SNF as a SNF whose performance during the program year is in the top third (greater than or equal to the 66.67th percentile) of the performance of all SNFs on the measure during the same program year. Each measure will be assessed independently such that a SNF that is a top tier performing SNF for one measure will be assigned 2 points for that measure even if they are not a top tier performing SNF for any other measure. Similarly, if a SNF is a top tier performing SNF for all measures, that SNF will be assigned 2 points for all measures.

We also proposed to assign a measure performance scaler for each SNF that will be equal to the total number of assigned HEA points that the SNF earns on all measures as a result of its performance. Under this approach, for the FY 2027 program year, a SNF will receive a maximum measure performance scaler of 16 if the SNF is a top tier performing SNF on all 8 measures for that program year. As described in more detail in the following paragraph and in section VIII.E.4.e of this final rule, we decided on assigning a maximum point value of 2 points for each measure because we believe that it provides an appropriate incentive to top tier performing SNFs that serve a high proportion of SNF residents with DES to continue their quality efforts, as well as an incentive for all SNFs that serve SNF residents with DES to improve their quality.

Based on our calculation of measure data from FY 2018 through FY 2021, the average SNF Performance Score for SNFs in the top third of performance that care for high proportions of residents with DES (SNFs with proportions of residents with DES in the top third) is 8.4 points lower than the SNF Performance Score for SNFs in the top third of performance that do not care for high proportions of residents with DES (40.8 for high performing SNFs with high proportions of residents with DES and 49.2 for all other high performing SNFs). Allowing for a maximum measure performance scaler of 16 for the FY 2027 program year will provide an opportunity for top tier performing SNFs that treat a high proportion of SNF residents with DES to close this gap. We also considered assigning 3 points for each measure to calculate the measure performance scaler. However, we determined that the maximum measure performance scaler a SNF could earn based on the assignment of 3 points per measure, 24 points, would exceed the number of points that many SNFs receive for their SNF Performance Score based on all Program measures, which diminishes the intent of the HEA as a bonus. We further discuss this option in section VIII.E.4.e of this final rule. We also considered assigning a point value of 2 to SNFs in the middle third of performance (SNFs whose performance falls between the 33.33rd percentile and 66.67th percentile in performance) and assigning a point value of 4 to top tier performing SNFs for each measure to align with the Medicare Shared Savings Program's health equity adjustment (87 FR 69843 through 69845). This approach would provide a greater number of SNFs the opportunity to benefit from the adjustment. However, in the SNF VBP Program, this approach could reduce the size of the payment adjustment available to SNFs whose performance is in the top tier, reducing the incentives to improve and deviating considerably from the primary goal of the Program to appropriately assess performance and reward high quality performance among SNFs that care for high proportions of residents with DES.

We proposed to define the term “underserved multiplier” for a SNF as the number representing the SNF's proportion of residents with DES out of its total resident population in the applicable program year, translated using a logistic exchange function. Due to the structure of the logistic exchange function, those SNFs with lower proportions of residents with DES have smaller underserved multipliers than their actual proportion of residents with DES and those SNFs with higher proportions of SNF residents with DES have underserved multipliers higher than their proportion of SNF residents with DES. The specific logistic function used to translate the SNF's proportion of residents with DES is described in section VIII.E.4.d. of this final rule. We proposed to define the total resident population at each SNF as Medicare beneficiaries identified from the SNF's Part A claims during the performance period of the 1-year measures. We proposed to define residents with DES, for purposes of the HEA, as the percentage of Medicare SNF residents who are also eligible for Medicaid. We proposed to assign DES for any Medicare beneficiary who was deemed by Medicaid agencies to be eligible to receive Medicaid benefits for any month during the performance period of the 1-year measures. For example, during the FY 2027 program year, we will calculate the proportion of residents with DES during any month of FY 2025 (October 1, 2024 through September 30, 2025), which is the performance period for the FY 2027 program year's 1-year measures. Similarly, a SNF's total resident population of Medicare beneficiaries identified from the SNF's Part A claims will be calculated from the SNF's Part A claims during FY 2025. Data on DES is sourced from the State Medicare Modernization Act (MMA) file of dually eligible beneficiaries, which each of the 50 States and the District of Columbia submit to CMS at least monthly. This file is utilized to deem individuals with DES automatically eligible for the Medicare Part D Low Income Subsidy, as well as other CMS program needs and thus can be considered the gold standard for determining DES. We note that this is the same file used for determining DES in the Hospital Readmissions Reduction Program. Additional details on this file can be found on the CMS website at https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/DataStatisticalResources/StateMMAFile and at the Research Data Assistance Center website at https://resdac.org/cms-data/variables/monthly-medicare-medicaid-dual-eligibility-code-january.

We proposed to calculate an underserved multiplier for a SNF if that SNF's proportion of residents with DES out of its total resident population during the applicable performance period of the 1-year measures is at least 20 percent. Imposing a floor of 20 percent for the underserved multiplier for a SNF to be eligible to receive HEA bonus points, reinforces that the adjustment is intended to appropriately measure performance by rewarding SNFs that are serving higher proportions of SNF residents with DES while also achieving high levels of quality performance. We describe this 20 percent floor in further detail in section VIII.E.4.d. of this final rule. Lastly, we proposed to define HEA bonus points for a SNF as the product of the SNF's measure performance scaler and the SNF's underserved multiplier. The HEA bonus points will then be added to the normalized sum of all points a SNF is awarded for each measure.

Through the HEA bonus points, we seek to improve outcomes by providing incentives to SNFs to strive for high performance across measures, as well as to care for high proportions of residents with DES. The HEA bonus points calculation is purposefully designed to not reward poor quality. Instead, the HEA incentivizes SNFs that care for higher proportions of SNF residents with DES to improve their overall quality of care across the entire SNF population. As described more fully in section VIII.E.4.d. of this final rule, the combination of the measure performance scaler and the underserved multiplier will result in a range of possible HEA bonus points that is designed to give the highest rewards to SNFs caring for a larger proportion of SNF residents with DES and delivering high quality care.

We proposed to amend our regulations at § 413.338(a) to define these new scoring methodology terms, including underserved population, the measure performance scaler, top tier performing SNF, the underserved multiplier, and the HEA bonus points. We also proposed to codify the HEA in our regulations by adding a new paragraph (k) at § 413.338 of our regulations. We solicited public comments on these proposals. We provide a summary of the comments we received, and our responses, later in this section.

d. Alternatives Considered

In developing the HEA, we considered approaches other than providing HEA bonus points to top tier performing SNFs with a high proportion of SNF residents with DES that could be implemented in the SNF VBP Program. More specifically, we considered the addition of risk adjustment to the payment methodology, peer grouping, or providing an opportunity to earn additional improvement points. First, we considered risk adjusting the measures used in the SNF VBP program. Currently, most measures in the SNF VBP Program are risk adjusted for the clinical characteristics of the resident that are included in the calculation of the measure. We do not risk adjust for social risk factors. Although it would require us to respecify the measures and then revisit the pre-rulemaking process for each measure, it is an operationally feasible approach. However, there is a significant concern around adding additional risk adjustment to the measures in the Program to account for social risk factors. Although additional risk adjustment can help account for factors outside of a SNF's control, such as social risk factors like socioeconomic status, it can also have potential unintended consequences. For instance, in a 2021 Report to Congress on Medicare and the Health Care Delivery System, the Medicare Payment Advisory Commission (MedPAC) recommended against adjusting SNF VBP measures results for social risk factors, stating that those types of adjustments can mask disparities. This would mean that disparities that currently exist would be more challenging to identify in the data, and thus harder for providers or the Program to eliminate. Additionally, in an analysis conducted by ASPE, it did not appear that additional risk adjustment would significantly impact SNF performance in the Program. Thus, we decided against incorporating additional risk adjustment into the SNF VBP Program at this time.

Second, we considered adding a peer grouping component to our scoring methodology, under which we would divide SNFs into groups based on the proportion of residents with DES that a SNF serves. With this peer grouping, different performance standards would then be set for each group, and thus payment adjustments would be made based on the group or strata in which a SNF falls. However, ASPE noted in their second report to congress on Social Risk Factors and Performance in Medicare's Value-Based Purchasing Program that although they support stratifying quality measures by DES to identify disparities, they had concerns that peer grouping could risk setting different standards of care for SNFs caring for underserved populations.

Finally, we considered an approach of adding additional improvement points to the Program. This could be achieved by either providing bonus points to SNFs for measures in which they had significant improvement or by increasing the points available for improvement from 9 points to some higher quantity, such as 15 points. It is important that even poorer performing SNFs be provided incentives to improve as all residents should have the opportunity to receive high quality care, and currently lower performers have the greatest opportunity for improvement. Since SNFs that care for higher proportions of SNF residents with DES tend to have lower SNF Performance Scores compared to SNFs that do not care for higher proportions of SNF residents with DES, this Program adjustment could address health equity by providing lower performing SNFs that care for higher proportions of SNF residents with DES additional incentives to improve the care they provide. However, we had concerns with this approach. First, this approach is not focused specifically on populations that are underserved, and it is unclear whether the additional improvement points available would provide sufficient incentives for SNFs that care for higher proportions of SNF residents with DES to invest the limited resources they have to make the changes necessary to benefit from it. We were also concerned that this change could primarily incentivize poorer performing SNFs that do not care for a higher proportion of SNF residents with DES. Although we aim to incentivize improvement in care for all SNFs, this alternative approach has a significant risk of not meeting the goals of a health equity-focused adjustment in the Program. Therefore, in considering how to modify the existing SNF VBP Program to advance health equity, we believe that rather than utilizing risk adjustment, peer grouping or adjusting the improvement point allocation process, it would be more appropriate to adopt an approach that rewards overall high-quality performance and incentivizes health equity.

In conclusion, we believe the HEA proposal allows us to appropriately measure performance by rewarding SNFs that overcome the challenges of caring for higher proportions of SNF residents with DES and to incentivize those who have not achieved such high-quality care to work towards improvement. As the Program expands beyond one measure, we believe this HEA will support high-quality care for all populations and recognize top tier performing SNFs serving residents with DES.

e. HEA Calculation Steps and Examples

In this section, we outline the calculation steps and provide examples of the determination of HEA bonus points and the application of these HEA bonus points to the normalized sum of a SNF's measure points. These example calculations illustrate possible HEA bonus points resulting from this approach, which accounts for both a SNF's quality performance and its proportion of residents with DES. For each SNF, the HEA bonus points would be calculated according to the following formula:

HEA bonus points = measure performance scaler × underserved multiplier

The calculation of the HEA bonus points will be as follows:

Step One—Calculate the Measure Performance Scaler for Each SNF

We will first calculate a measure performance scaler based on a SNF's score on each of the SNF VBP program measures. We will assign a point value of 2 for each measure where a SNF is a top tier performing SNF on that measure, such that for the FY 2027 program year, a SNF could receive a maximum 16-point measure performance scaler for being a top tier performing SNF for each of the 8 measures. Top tier performance on each measure is calculated by determining the percentile that the SNF falls in based on their score on the measure as compared to the score earned by other SNFs who are eligible to receive a score on the measure. A SNF whose score is greater than or equal to the 66.67th (two-thirds) percentile on a given measure compared to all other SNFs will be considered a top tier performing SNF and will be assigned a point value of 2 for that measure. This is depicted in Table 19 for the FY 2027 program year. We note that if a SNF performs in the bottom two-thirds (less than 66.67th percentile) of performance on all measures, that SNF would be assigned a point value of 0 for each measure, resulting in a measure performance scaler of 0.

As described previously, we proposed to assign to each SNF a point value of 2 for each measure for which it is a top tier performing SNF, and we proposed that the measure performance scaler would be the sum of the point values assigned to each measure in the SNF VBP Program. We modeled this measure performance scaler after the performance scaler finalized in the Medicare Shared Savings Program's health equity adjustment (87 FR 69843 through 69845) for consistency across CMS programs, although that adjustment allows for a middle performance group as well. However, as described previously, because we aim to specifically target the highest performing SNFs for this adjustment, we are limiting our adjustment to the top third of performers only.

Step Two—Calculate the Underserved Multiplier

We proposed to calculate an underserved multiplier, which, as stated previously, we proposed to define as, for a SNF, the number representing the SNF's proportion of residents with DES out of its total resident population in the applicable program year, translated using a logistic exchange function. As stated previously, the primary goal of the adjustment is to appropriately measure performance by rewarding SNFs that are able to overcome the challenges of caring for high proportions of residents with DES while still providing high quality care. We can also accomplish the goal of this adjustment by utilizing a logistic exchange function to calculate the underserved multiplier, which will provide SNFs who care for the highest proportions of SNF residents with DES with the most HEA bonus points. Thus, we proposed to utilize a logistic exchange function to calculate the underserved multiplier for scoring SNFs such that there would be a lower rate of increase at the beginning and the end of the curve. The formula for the underserved multiplier using a logistic exchange function would be as follows:

Due to the structure of the logistic exchange function, those SNFs with lower proportions of residents with DES have smaller underserved multipliers than their actual proportion of residents with DES and those SNFs with higher proportions of SNF residents with DES have underserved multipliers higher than their proportion of SNF residents with DES. A logistic exchange function assumes a large difference between SNFs treating the most and fewest residents with DES. Therefore, the logistic exchange function provides higher HEA bonus points to SNFs serving greater proportions of SNF residents with DES. For example, as shown in Figure A, if a SNF serves 70 percent of SNF residents with DES, the SNF would receive an underserved multiplier of 0.78.

We proposed that SNFs will receive an underserved multiplier of 0 if the SNF's proportions of SNF residents with DES is less than 20 percent, thereby establishing a “floor” on the magnitude of the SNF's underserved population proportion in order for the SNF to be eligible for any HEA bonus points. Because SNFs with proportions of SNF residents with DES below 20 percent receive a value of 0 for their underserved multiplier, any multiplication with the measure performance scaler will be 0 and will lead to those SNFs receiving no HEA bonus points. Imposing a floor of 20 percent for the underserved multiplier for a SNF to be eligible to receive HEA bonus points, reinforces that the adjustment is intended to appropriately measure performance by rewarding SNFs that are serving higher proportions of SNF residents with DES while also achieving high levels of quality performance. We believe this approach is necessary to remain consistent with the goal to reward high quality care specifically among SNFs that care for higher proportions of SNF residents with DES. We anticipate the vast majority of SNFs will be able to earn HEA bonus points despite this floor, and we expect the percent of SNFs meeting the 20 percent floor for the underserved multiplier may increase over time, as existing SNFs seek to expand their resident population to earn HEA bonus points. We also believe that the challenges associated with caring for residents with DES, a complex resident population, will be negligible if 80 percent of a SNF's resident population is not underserved. This 20 percent floor is consistent with the new health equity adjustment for ACOs that report all payer eCQMs/MIPS CQMs, as finalized in the CY 2023 PFS final rule (87 FR 69849 through 69852).

Alternatively, we considered establishing a floor of 60 percent such that all SNFs with proportions of SNF residents with DES below 60 percent would receive an underserved multiplier of 0, and therefore, would not receive any HEA bonus points. Although this would provide a greater value-based incentive payment amount to top tier performing SNFs that serve the highest proportions of SNF residents with DES and thus would support the primary goal of the adjustment, it would also mean SNFs that care for high proportions of SNF residents with DES who likely face similar challenges, albeit to a lesser extent, would receive no adjustment at all.

Step Three—Calculate the HEA Bonus Points

We proposed to calculate the HEA bonus points that apply to a SNF for a program year by multiplying the measure performance scaler by the underserved multiplier. We believe that combining the measure performance scaler and the underserved multiplier to calculate the HEA bonus points allows for us to reward those SNFs with high quality that are also serving high proportions of SNF residents with DES, while incentivizing other SNFs to improve their performance (by a higher measure performance scaler) and serve more SNF residents with DES (by a higher underserved multiplier) in order to earn more HEA bonus points. Table 20 shows examples of how the measure performance scaler and underserved multiplier would be used to calculate the HEA bonus points. It also demonstrates how the logistic exchange function that we proposed to use to calculate the underserved multiplier interacts with the measure performance scaler and results in SNFs serving higher proportion of SNF residents with DES receiving more HEA bonus points. For instance, example SNF 1 with 16 points and a proportion of residents with DES of 50 percent received a measure performance scaler of 16 and an underserved multiplier of 0.22. In other words, they would receive 22 percent of the points from their measure performance scaler because of how the logistic exchange function translates their proportion of residents with DES. Their measure performance scaler of 16 and underserved multiplier of 0.22 would then be multiplied together to get their HEA bonus points of 3.52. Alternatively, example SNF 2 with 14 points and a proportion of residents with DES of 70 percent, received an underserved multiplier of 0.78. Their measure performance scaler of 14 and underserved multiplier of 0.78 would then be multiplied together to get their HEA bonus points of 10.92. Note that although SNF 1 had a higher measure performance scaler, they received fewer HEA bonus points because they had a lower proportion of residents with DES. Finally, example SNF 3 had a proportion of SNF residents with DES of less than 20 percent and so they received an underserved multiplier of 0, resulting in no HEA bonus points

HEA bonus points = Measure Performance Scaler × Underserved Multiplier

Step Four—Add HEA Bonus Points to the Normalized Sum of all Points Awarded for each Measure

Finally, we proposed that we will add a SNF's HEA bonus points as calculated in Step Three of this section to the normalized sum of all points awarded to a SNF across all measures. This resulting sum will be the SNF Performance Score earned by the SNF for the program year, except that we will cap the SNF's Performance Score at 100 points to ensure the HEA creates a balanced incentive that has the potential to increase the SNF Performance Score without dominating the score and creating unintended incentives. Table 21 displays the final HEA bonus points added to the normalized sum of all points awarded to a SNF for each measure for 4 example SNFs.

By adding these HEA bonus points to the normalized sum of all points awarded to a SNF for each measure, SNFs can be rewarded for delivering excellent care to all residents they serve and can be appropriately recognized for the resource intensity expended to achieve high performance when caring for higher proportion of SNF residents with DES. We believe this scoring adjustment, designed to advance health equity through the SNF VBP Program, is consistent with CMS's goal to incentivize greater inclusion of underserved populations, as well as the delivery of high-quality care to all.

We proposed the scoring change and calculations including the use of the measure performance scaler, underserved multiplier, and HEA bonus points. We also proposed to codify this proposal by adding a new paragraph (k) at § 413.338 of our regulations and by updating § 413.338(e) of our regulations to incorporate the health equity scoring adjustment into our performance scoring methodology. We solicited public comment on the HEA.

We received public comments on the HEA proposal. The following is a summary of the comments we received and our responses.

Comment: Many commenters supported our HEA noting that it appropriately recognizes the additional challenges and increased resource utilization in meeting the healthcare needs of the underserved population while also rewarding high quality performance for all residents.

Response: We agree that this adjustment recognizes the resource intensity required to care for residents with DES while also supporting high quality care for all residents.

Comment: A few commenters supported the HEA and also suggested next steps for CMS. One commenter encouraged CMS to adequately fund State Medicaid programs. One commenter urged CMS to increase scrutiny on how SNFs that are eligible for the HEA spend their Medicare and Medicaid funds. Another commenter recommended that CMS monitor the HEA for unintended consequences. One commenter suggested that CMS consider whether adjustments to the scoring methodology are necessary to account for an organization's performance specifically within the DES population if it differs from the performance in the rest of the patient population. One commenter requested that CMS consider how the HEA compares to a peer grouping approach.

Response: We intend to closely monitor the data for potential unintended consequences that could arise as a result of the HEA. We agree that it is also important to consider an organization's performance specifically within the DES population, although that is not what this HEA is intended to do. As we explained in the proposed rule (88 FR 21392), we have concerns with utilizing a peer grouping approach because it may set different standards of care. We will take these suggestions into consideration as we develop additional ways to incorporate health equity into the Program.

Comment: A few commenters supported adjusting the SNF VBP Program for health equity but expressed concerns about the details of the proposed HEA. One commenter believed the scoring methodology was too complex and stated that complexity in measures makes changes at the facility level more challenging. One commenter was concerned that high performing facilities with high proportions of residents with DES will get payment adjustments and lower performing facilities with high proportions of residents with DES will not get payment adjustments. The same commenter requested that CMS explore how these lower performing facilities might access scoring adjustments. One commenter was concerned that the HEA may reward facilities for their resident population instead of their quality scores. One commenter suggested CMS use the term “patient” instead of “resident” to describe the population of SNF short -stay patients with original Medicare-covered stays.

Response: We disagree that the HEA is too complex. We believe that the scoring methodology addresses the challenges of adding a HEA to high performing SNFs that also care for high proportions of residents with DES in a straightforward way. As stated in the proposed rule (88 FR 21382 through 21392), if a SNF, relative to other SNFs, is in the top third of performance for any measure, they are eligible for HEA bonus points. The number of HEA bonus points that a SNF is eligible to receive depends on its proportion of residents with DES. The HEA bonus points are then incorporated into the calculation of the SNF Performance Score, which is used to determine a SNF's payment adjustment. A SNF that provides care for high proportions of residents with DES and performs well on any measure is likely to receive a higher adjustment due to this addition to the program. Resources will be developed to support SNFs in understanding this new adjustment.

We also reiterate that the HEA is intended to reward high quality performance and not solely adjust for resident population, which may leave lower performing facilities with high proportions of residents with DES without a payment adjustment. We do not intend to reward lower quality performance and we believe the proposed HEA incentivizes lower performing facilities to improve their quality scores. We also agree that it is important to measure health equity in other ways, which is why we included in the proposed rule a request for information on additional ways to incorporate health equity into the Program.

We disagree that the adjustment may reward facilities for their resident population instead of their quality scores as we specifically designed the adjustment to first determine whether the provider is high performing and then apply the underserved multiplier. Lastly, we have used the term “resident” to refer to both short- and long-stay residents when referencing the HEA because we use this language throughout the entire proposed and final rules for all measures, including both short and long-stay measures.

Comment: A few commenters did not support our proposed HEA. One commenter believed it was premature to add a health equity component into a payment program and also believed that the long stay measures are unrelated to health equity because the DES population is calculated using Medicare Part A claims. The same commenter also believed the HEA does not provide meaningful data to address health equity, and that the HEA doesn't appropriately incentivize SNFs with a low proportion of residents who are in a Medicare Part A stay or SNFs with a large population of residents enrolled in Medicare Advantage. One commenter believed the proposal is discriminatory and does not consider health equity and instead stated that CMS should include social determinants of health as part of the new quality measures.

Response: We believe the HEA is inclusive as all SNFs that meet the proposed floor of 20 percent of residents with DES are eligible to earn HEA bonus points. As we explained in the proposed rule, there is considerable literature linking negative health outcomes to residents with DES specifically in the SNF setting (88 FR 21383). We designed the HEA to reward high quality care for all residents and to recognize the resource intensity required to care for residents with DES, who are more likely to have disabilities or functional impairments, more likely to be medically complex, more likely to have greater social needs, and have a greater risk of negative health outcomes compared to individuals without DES. We disagree that it is premature to add a health equity component into a payment program. We note that the HEA will not be included until the FY 2027 program year, and we believe it is imperative to incentivize high quality care for all residents in the Program without additional delay. Further, as described above, advancing health equity is a key pillar of our strategic vision and we have already been working to advance health equity by designing, implementing, and operationalizing policies and programs aimed at identifying and reducing health disparities.

We also disagree that long stay measures are unrelated to health equity because the DES population is calculated using Medicare Part A claims. The HEA aims to incentivize high quality care under the SNF VBP Program, while recognizing the resource intensity required to care for residents with DES, by providing health equity bonus points to SNFs that perform well on Program measures and have at least 20 percent of residents with DES. SNFs with a higher proportion of residents with DES also have a higher share of residents who are enrolled in Medicaid in their total resident population, which adds to their resource constraints. Many long-stay residents are enrolled in Medicare Part B, which covers certain services provided by nursing facilities. Thus, to accomplish the goals of the HEA, we feel it is appropriate to include all measures in the SNF VBP Program, including long-stay measures when calculating the HEA.

Regarding the data provided by the HEA, we reiterate the intent of the HEA is not to specifically incentivize improvement among residents with DES but rather incentivize high quality care among all residents in the facility and to recognize the additional resources required to care for residents with DES. Current data relating to the Program, available on the Provider Data Catalog website, provide SNFs with information on their quality performance. We believe the HEA is an important first step in adding a health equity component to the Program; however, we also intend to explore additional ways to incorporate health equity into the Program, which we intend to allow commenters to provide feedback on in future rulemaking.

We disagree with concerns that this HEA might not appropriately incentivize SNFs that have large populations of residents enrolled in Medicare Advantage. We believe this HEA has the ability to improve care for all residents in a SNF as SNFs will need to perform in the top third of performance for at least one measure to be eligible to receive the HEA. Further, SNFs that have a low proportion of Medicare Part A beneficiaries will still be able to earn the HEA based on the proportion of those Medicare Part A beneficiaries who have DES and their performance under the Program. However, we will continue to monitor the HEA after implementation.

We will take the commenter's suggestion to include social determinants of health as part of the new quality measures into consideration as we develop additional ways to incorporate health equity into the Program.

We received public comments on our proposal to utilize DES to define the term “underserved population”. The following is a summary of the comments we received and our responses.

Comment: Many commenters supported using dual eligibility status (DES) to define the underserved population because it is consistently recorded in administrative data, has a strong link to other social drivers of health, and reflects those who face the most significant social needs.

Response: We thank commenters for their support and agree DES is an important indicator of social need because individuals with DES are more likely to have disabilities or functional impairments, more likely to be medically complex, more likely to have greater social needs, and have a greater risk of negative health outcomes compared to individuals without DES.

Comment: Many commenters encouraged CMS generally to explore other options for defining the underserved population in the future as there are many other social risk factors that impact resident outcomes. A few commenters suggested considering the proportion of Medicaid residents in a facility as part of the definition of “underserved.” A few commenters suggested CMS encourage collection of race and ethnicity data and adjust based on the racial composition of facilities.

Response: We thank the commenters for these suggestions.

Comment: A few commenters requested CMS consider adding additional indicators to the definition of “underserved” before implementing the HEA in order to create multiple ways to recognize the challenges residents and SNFs may face in achieving better outcomes. One commenter requested the Low-Income Subsidy (LIS) be included in the definition, and one commenter suggested both the LIS and Area Deprivation Index (ADI) be included in the definition of “underserved.”

Response: As we explained in the proposed rule (88 FR 21384 through 21385), we are concerned that including the ADI or residents eligible for the LIS program as part of our definition of “underserved” in the HEA is premature until more research is conducted linking these indicators to negative health outcomes specifically in the SNF setting. We intend to consider these and other indicators as we explore additional ways to incorporate health equity into the Program.

Comment: A few commenters expressed concern over using DES alone to define the underserved population because Medicaid eligibility varies by State. One commenter requested that CMS consider how fluctuations in the number of residents with DES within a SNF over time would impact the scoring methodology and whether this indicator would be stable over the time the measures are collected.

Response: As explained in the proposed rule (88 FR 21386), we proposed to define residents with DES, for purposes of this proposal, as the percentage of Medicare SNF residents who are also eligible for Medicaid. We proposed to assign DES for any Medicare beneficiary who was deemed by Medicaid agencies to be eligible to receive Medicaid benefits for any month during the performance period of the 1-year measures. Because of the concern that Medicaid eligibility varies by state, we are clarifying in this final rule that this definition includes beneficiaries with partial DES. Residents with full DES qualify for full Medicare and Medicaid benefits, whereas residents with partial DES qualify fully for Medicare, but only for some Medicaid benefits, as they have higher amounts of assets and income. We believe this expanded definition of dual eligibility is appropriate for SNF VBP as it allows for the inclusion of a larger number of residents who are underserved. In our modeling that includes residents with partial and full DES, we also considered using eligibility for the Medicare Low Income Subsidy to meet the 20 percent threshold, which does not differ by State and may capture different low-income beneficiaries and found only a small increase in SNFs that became eligible to receive the HEA, compared to only using those with partial and full DES. Given this, we believe that using the definition of DES, which includes residents with both partial and full DES, captures a sufficient proportion of low-income Medicare beneficiaries and is sufficiently consistent across States.

As requested by the commenter, we would like to explain further how fluctuations in the number of residents with DES, including both partial and full DES, within a SNF over time would impact the scoring methodology. We proposed to define the underserved multiplier as the number representing the SNF's proportion of residents with DES out of its total resident population in the applicable program year, translated using a logistic exchange function (88 FR 21385 through 21386). We further defined the total resident population as Medicare beneficiaries identified from the SNF's Part A claims during the performance period of the 1-year measures (88 FR 21385 through 21386). In SNF VBP, the program year refers to the year in which a SNF's payment is impacted and has a corresponding baseline and performance period for each measure. Thus, because the calculation of the program year payment adjustment is dependent on both the performance period and baseline period, we would like to clarify that the underserved multiplier is for a SNF, the mathematical result of applying a logistic function to the number of SNF residents who are members of the underserved population out of the SNF's total Medicare population, as identified from the SNF's Part A claims, during the performance period that applies to the 1-year measures for the applicable program year. A single underserved multiplier will be calculated using the performance period of the 1-year measures and will be applied to all measures in the Program. The periods for calculating measure performance and calculating the proportion of residents with DES therefore overlap. This means that a SNF's proportion of residents with DES may change for each SNF VBP program year, and thus the SNF's underserved multiplier may change for each program year, in the same way that the set of residents used to calculate measure scores for each measure changes. For example, as a SNF's proportion of residents with DES increases, if their performance remains in the top third for the same measure or measures, they will likely receive additional HEA bonus points. As a SNF's proportion of residents with DES decreases, even if their performance remains in the top third for the same measure or measures from previous program years, they will likely receive fewer HEA bonus points. The combination of a SNF's proportion of residents with DES and performance on each measure will determine how many HEA bonus points a SNF receives, and both proportion of residents and performance on each measure can change from year to year.

Comment: One commenter did not support using DES until additional research is conducted as they believe utilizing DES to define the underserved population could lead to unintended consequences. Specifically, they believe CMS may unintentionally increase the financial disparity that exists between for-profit and not-for-profit nursing homes by rewarding for-profit nursing homes with higher DES percentages and not rewarding not-for-profit nursing homes that care for higher proportions of Medicaid-only residents.

Response: We disagree that the HEA will necessarily increase the disparity between SNFs that care for higher proportions of residents with DES compared to those with higher proportions of Medicaid-only residents as our definition of DES includes the total resident population, which we further defined as Medicare beneficiaries identified from the SNF's Part A claims (88 FR 21386), as the denominator. Thus, although a SNF may have lower proportions of residents with Medicare overall, the proportion of DES only takes into consideration the proportion of residents with Medicare who also have Medicaid. Additionally, we note that the HEA is intended to recognize and reward all SNFs for providing excellent care to higher proportions of residents with DES.

We also solicited public comments on utilizing a measure performance scaler, assigning a point value of 2 for each measure for which a SNF is a top tier performing SNF, and defining a top tier performing SNF as a SNF whose performance for the program year is in the top third of the performance of all SNFs on the measure for the same program year. We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: One commenter supported this proposal to recognize SNFs that perform in the top third.

Response: We agree that recognizing performance in the top third is appropriate because it strikes a balance between rewarding high quality performance and providing an appropriate payment adjustment to those who perform well and serve a high proportion of residents with DES while incentivizing lower performing SNFs to improve.

Comment: A few commenters suggested CMS limit those receiving a bonus to SNFs in the top 20 percent of performance instead of the top third.

Response: We thank the commenters for their recommendation but believe recognizing performance in the top third strikes a balance between rewarding high quality performance and providing an appropriate payment adjustment to those who perform well and serve a high proportion of residents with DES while still incentivizing lower performing SNFs to improve. Further, as explained in the proposed rule (88 FR 21385) based on our calculation of measure data from FY 2018 to 2021, the average SNF Performance Score for SNFs in the top third of performance that care for high proportions of residents with DES (SNFs with proportions of residents with DES in the top third) is 8.4 points lower than the SNF Performance Score for SNFs in the top third of performance that do not care for high proportions of residents with DES (40.8 for high performing SNFs with high proportions of residents with DES and 49.2 for all other high performing SNFs). Because of these existing performance disparities between SNFs that serve a high proportion of residents with DES and those that do not, setting the performance threshold too high may inadvertently exclude SNFs that serve a high proportion of residents with DES from the HEA. In the future, we may consider raising the performance threshold for the HEA based on ongoing monitoring of SNF performance, especially among those in the top tier.

Comment: One commenter expressed concern that if there is low variability in a measure score between the top and bottom third, there may not be a clinically meaningful difference.

Response: Although we recognize that some measures may have low variability in performance, we aim to reward high performing SNFs and incentivize lower performing SNFs to improve, even if those are small improvements. We believe setting the high-performance threshold at the top third strikes this balance regardless of variability in the measure.

Comment: A few commenters expressed their support for assigning a point value of 2 for each measure and noted their interest in commenting on future rulemaking if this changes as the program expands.

Response: We thank the commenters for their support. We agree that assigning a point value of 2 is appropriate at this time and would use rulemaking to propose any revisions to this policy.

We also solicited public comments on using an underserved multiplier to calculate the HEA, utilizing a logistic exchange function to calculate the underserved multiplier, and setting a floor of 20 percent for a SNF to be eligible for any HEA bonus points. We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: One commenter supported the use of a logistic exchange function to calculate the underserved multiplier.

Response: We thank the commenter for their support.

Comment: A few commenters supported the proposal that a SNF's population must include at least 20 percent of residents with DES in order to be eligible for the underserved multiplier especially since those who do not meet this floor will not be penalized.

Response: We thank commenters for their support of the 20 percent floor.

Comment: One commenter expressed concerns about the 20 percent floor noting that they would prefer for there to be no floor.

Response: We disagree that it would be preferable to not have a 20 percent floor. As noted in the proposed rule (88 FR 21388), we strongly believe a floor of 20 percent allows us to accomplish our goals of this adjustment. Specifically, the 20 percent floor reinforces that the adjustment is intended to appropriately measure performance by rewarding SNFs that are serving higher proportions of SNF residents with DES while also achieving high performance. We believe this approach is necessary to remain consistent with the goal to reward high quality care specifically among SNFs that care for higher proportions of SNF residents with DES. We anticipate the vast majority of SNFs will be able to earn HEA bonus points despite this floor. We also believe that the challenges associated with caring for residents with DES, a complex resident population, would be negligible if greater than 80 percent of a SNF's resident population is not underserved because residents with DES are more likely to have disabilities or functional impairments, more likely to be medically complex, more likely to have greater social needs, and have a greater risk of negative health outcomes compared to those without DES.

After consideration of public comments, we are finalizing the Health Equity Adjustment for the SNF VBP Program beginning with the FY 2027 program year.

We are also finalizing our definition of “underserved multiplier” as the mathematical result of applying a logistic function to the number of SNF residents who are members of the underserved population out of the SNF's total Medicare population, as identified from the SNF's Part A claims, during the performance period that applies to the 1-year measures for the applicable program year. We are also finalizing our definition of “underserved population” as Medicare beneficiaries who are SNF residents in a Medicare Part A stay who are also dually eligible, both partial and full, for Medicaid.

Further, in an effort to minimize burden on providers, we aim to align our Health Equity Adjustment to a similar adjustment proposed for inclusion in the Hospital Value Based Purchasing Program as is feasible and appropriate. As part of this alignment, we are making a technical change to our definition of the health equity adjustment bonus points so the definition is as follows: the points that a SNF can earn for a program year based on its performance and proportion of SNF residents who are members of the underserved population.

We are also finalizing the updates to our regulations at § 413.338 to reflect this Health Equity Adjustment, including the clarified definitions of the “underserved multiplier,” “underserved population,” and “health equity adjustment bonus points.”

e. Increasing the Payback Percentage To Support the HEA

We previously adopted 60 percent as the SNF VBP Program's payback percentage for FY 2019 and subsequent fiscal years, subject to increases as needed to implement the Program's Low-Volume Adjustment policy for SNFs without sufficient data on which to base measure scores. We based this decision on numerous considerations, including our estimates of the number of SNFs that receive a positive payment adjustment under the Program, the marginal incentives for all SNFs to reduce hospital readmissions and make quality improvements, and the Medicare Program's long-term sustainability. We also stated that we intended to monitor the effects of the payback percentage policy on Medicare beneficiaries, on participating SNFs, and on their measured performance, and we stated that we intended to consider any adjustments to the payback percentage in future rulemaking.

In previous rules, we have received many public comments urging us to increase the payback percentage. For example, in the FY 2018 SNF PPS final rule (82 FR 36620), we responded to comments urging us to finalize a 70 percent payback percentage. We stated at that time that we did not believe that a 70 percent payback percentage appropriately balanced the policies that we considered when we proposed the 60 percent policy. We responded to similar comments in the FY 2019 SNF PPS final rule (83 FR 39281), where commenters urged us to revisit the payback percentage policy and adopt 70 percent as the Program's policy. We reiterated that we did not believe it was appropriate to revisit the payback percentage at that time, which was prior to the Program's first incentive payments taking effect on October 1, 2018.

As part of our ongoing monitoring and evaluation efforts associated with the SNF VBP Program, we considered whether to update the Program's payback percentage policy to support the proposed HEA. After our consideration, and in conjunction with the HEA bonus points, we proposed to increase the total amount available for a fiscal year to fund the value-based incentive payment amounts beginning with the FY 2027 program year.

We proposed this update to our payback percentage policy both to increase SNFs' incentives under the Program to undertake quality improvement efforts and to minimize the impact of the proposed HEA on the distribution of value-based incentive payments to SNFs that do not earn the HEA. Because the SNF VBP Program's value-based incentive payment amounts depend on the distribution of SNF Performance Scores in each SNF VBP program year, providing additional incentives to SNFs serving higher proportions of SNF residents with DES without increasing the payback percentage could reduce other SNFs' value-based incentive payment amounts. While we do not believe that those reductions would be significant, we view that a change to the payback percentage will further increase SNFs' incentivizes to implement effective quality improvement programs.

In determining how to modify the payback percentage, we considered the maximum number of HEA bonus points that would be awarded, as it is important that those points translate into meaningful enough rewards for SNFs to meet our goals of this adjustment to appropriately measure performance by rewarding SNFs that overcome the challenges of caring for higher proportions of SNF residents with DES and to incentivize SNFs who have not achieved such high-quality care to work towards improvement. However, we also have to ensure that the additional HEA bonus points available do not lead to value-based incentive payments that exceed the maximum 70 percent payback percentage authorized under section 1888(h)(5)(C)(ii)(III) of the Act. Additionally, we considered the maximum number of HEA bonus points that would be awarded in comparison to the average SNF Performance Score as we believe providing more HEA bonus points for the HEA relative to the average a SNF receives for their performance on the Program measures could undermine the incentives for SNFs to perform in the SNF VBP Program.

We conducted an analysis utilizing FY 2018 through FY 2021 measure data for our previously finalized and new measures, including a simulation of performance from all 8 measures for the FY 2027 Program, to determine what would be the greatest amount we could increase the payback percentage by for the HEA while not exceeding the 70 percent maximum or allowing for too many HEA bonus points. We examined the interaction of the two factors that directly impact the size of the incentives, the assigned point value for each measure and the payback percentage. For the first factor, as stated previously, we proposed to assign 2 points per measure to each SNF that is a top tier performing SNF for that measure. This assigned point value would be used to calculate the measure performance scaler and resulting HEA bonus points. In this analysis, we also tested alternatives of assigning a point value of 1 or 3 per measure to determine how each option would impact the payback percentage and resulting value-based incentive payment amounts. For the payback percentage factor, we tested increasing the payback percentage to a fixed amount of 65 percent. We also tested an option in which we allow the payback percentage to vary based on performance data such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

Table 22 has three columns representing possible point values assigned to each measure that are then used to calculate the measure performance scaler. As shown in Table 22, regardless of the assigned points per measure, 78 percent of SNFs would receive the HEA in this analysis. This means that 78 percent of SNFs were top tier performing SNFs for at least 1 measure and had at least 20 percent of their residents with DES, and therefore would have received some HEA bonus points. Table 22 also shows the mean number of HEA bonus points per SNF receiving the HEA, as well as the HEA bonus points at the 90th percentile and the maximum HEA bonus points that would have been received for the HEA. Table 22 then provides an estimate of the payback percentage that would have been required such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent. This analysis also identified that the average SNF, prior to the implementation of the HEA, would have received a SNF Performance Score of 31.6 and that the 90th percentile SNF Performance Score was 49.7.

As stated previously, we proposed to assign a point value of 2 for each measure in which a SNF is a top tier performing SNF. Table 22 shows that assigning a point value of 2 per measure would have resulted in a 66 percent payback percentage, meaning once all SNFs have been awarded HEA bonus points, the value-based incentive payment amounts would result in a payback percentage of 66 percent. Assigning a point value of any higher number, such as 3 points per measure could result in the payback percentage exceeding the 70 percent maximum. This is because the amount of HEA bonus points would vary with performance, and so we expect the HEA bonus points to vary from year to year, creating a significant risk that assigning a point value of 3 for each measure would result in a payback percentage above the 70 percent maximum. Further, assigning a point value of 3 for each measure would result in HEA bonus points as high as 20. Considering the average SNF Performance Score during this same time period would have been 31.6, the addition of 20 bonus points puts far too much weight on the HEA compared to each of the Program measures.

Because we proposed to assign a point value of 2 for each measure in the Program and based on this analysis, we proposed that the payback percentage would vary by program year to account for the application of the HEA such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent. Utilizing a variable approach ensures a very limited number of SNFs (if any) that do not receive HEA bonus points will experience a downward payment adjustment. For a given program year, we proposed to calculate the final payback percentage using the following steps. First, we will calculate SNF value-based incentive payment amounts with a payback percentage of 60 percent and without the application of the proposed HEA. Second, we will identify which SNFs receive the HEA, and which do not based on their proportion of residents with DES and individual measure performance. Third, while maintaining the value-based incentive payment amounts calculated in the first step for those SNFs that do not receive the HEA, we will calculate the payback percentage needed to apply the HEA as described in section VIII.E.4.d. of this final rule. As shown in Table 23, through our analysis, we estimated that assigning 2 points per measure would require an increase in the 60 percent payback percentage of 6.02 percentage points for the FY 2027 program year and 5.40 percentage points for the FY 2028 program year. These are estimates and we would expect some variation that could be the result of SNFs with high proportions of residents with DES significantly changing their performance, changes in Medicaid eligibility requirements such that the proportions of residents with DES changes, changes to the Program such as adding additional measures which could add additional points available for the HEA, and other possible factors. For the last factor, increasing the points available could result in an increased payback percentage beyond the 70 percent maximum; however, we intend to adjust the number of points available through the rulemaking process if we add measures to the Program. With our current proposal of assigning a point value of 2 for each measure, we do not anticipate that any factors will result in an increase in payback beyond the 70 percent maximum. However, we will continue to monitor the data closely and intend to make further proposals if necessary, in future rulemaking. Thus, as shown in Table 23, a variable payback percentage will allow all SNFs that receive the HEA to also receive increased value-based incentive payment amounts, and also means that SNFs that do not receive the HEA will not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

We also explored setting a fixed payback percentage of 65 percent. This would mean that despite assigning higher point values for each measure, the resulting value-based incentive payment amounts would be capped to ensure the payback percentage would not exceed 65 percent. This would ensure that the payback percentage is below the 70 percent maximum. However, as shown in Table 23, including a fixed percentage point payback would result in some SNFs, including SNFs that care for the highest quintile of residents with DES and almost one-third of rural SNFs, receiving reduced value-based incentive payment amounts compared to the absence of the HEA in the Program. This would be a significant negative consequence of this proposal, and our proposal is structured to avoid this outcome. We do not want SNFs that provide high quality care and that serve large proportions of residents who are underserved to be disadvantaged by this HEA.

We proposed to adopt a variable payback percentage and proposed to amend our regulations at § 413.338(c)(2)(i) to reflect this change to the payback percentage for FY 2027 and subsequent fiscal years. We solicited public comment on these proposals.

We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: Many commenters supported the proposal to increase the payback percentage. A few of these commenters also urged CMS to pay out the full 70 percent allowable by statute.

Response: We thank commenters for their support. As noted in the FY 2018 rule (82 FR 36619 through 36620), the 60 percent payback percentage was set to appropriately balance the number of SNFs that receive a positive payment adjustment, the marginal incentives for all SNFs to reduce hospital readmissions and make broad-based care quality improvements, and the Medicare Program's long-term sustainability through the additional estimated Medicare trust fund savings. We continue to hold those goals for the payback percentage as we have expanded the Program. We believe it is appropriate to utilize the additional payback to specifically target the HEA, but we continue to balance each of the considerations listed above and do not believe it is appropriate to increase the payback percentage beyond what will be used to fund the HEA at this time.

Comment: A few commenters supported the use of a variable payback percentage as long as it stays under the 70 percent threshold allowable by statute.

Response: We thank the commenters for their support of the variable payback percentage and agree that we do not intend to allow the payback percentage to increase beyond the 70 percent threshold. We reiterate we will continue to monitor the data closely and intend to make further proposals if necessary, in future rulemaking.

After consideration of public comments, we are finalizing the updates to the payback percentage and codifying those updates in our regulations.

5. Health Equity Approaches Under Consideration for Future Program Years: Request for Information (RFI)

We are committed to achieving equity in health outcomes for residents by promoting SNF accountability for health disparities, supporting SNFs' quality improvement activities to reduce these disparities, and incentivizing better care for all residents. The Health Equity Adjustment, as described previously, will revise the SNF VBP scoring methodology to reward SNFs that provide high quality care to residents with DES and create an incentive for all SNFs to treat residents with DES. We also aim to incentivize the achievement of health equity in the SNF VBP Program in other ways, including focusing specifically on reducing disparities to ensure we are incentivizing improving care for all populations, including residents who may be underserved. In order to do so, we solicited public comment on possible health equity advancement approaches to incorporate into the Program in future program years that could supplement the Health Equity Adjustment described in section VIII.E.4 of this final rule. We are also seeking input on potential ways to assess improvements in health equity in SNFs.

As is the case across healthcare settings, significant disparities persist in the skilled nursing environment. The goal of explicitly incorporating health equity-focused components into the Program is to both measure and incentivize equitable care in SNFs. By doing so, we not only aim to encourage SNFs to focus on achieving equity for all residents, but also to afford individuals and families the opportunity to make more informed decisions about their healthcare.

The RFI consists of four main sections. The first section requested input on resident-level demographic and social risk indicators, as well as geographic-level indices that could be used to assess health equity gaps. The second section requested input on possible health equity advancement approaches that could be added to the Program and describes questions that should be considered for each. The third section requested input on other approaches that could be considered for inclusion in the SNF VBP Program in conjunction with the approaches described in the second section. Finally, the fourth section requested input on adopting domains that could incorporate health equity.

a. Resident-Level Indicators and Geographic-Level Indices To Assess Disparities in Healthcare Quality

To identify SNFs that care for residents who are underserved and determine their performance among these populations, we need to select an appropriate indicator of such. Identifying and prioritizing social risk or demographic variables to consider for measuring equity can be challenging. This is due to the high number of variables that have been identified in the literature as risk factors for poorer health outcomes and the limited availability or quality of standardized data. Each source of data has advantages and disadvantages in identifying populations to assess the presence of underlying disparities. Income-based indicators are a frequently used measure for assessing disparities, but other social risk indicators can also provide important insights. As described in section VIII.E.4. of this final rule, we proposed to utilize dual eligibility status (DES) to measure the underserved population in SNFs, as this data is readily available and DES as a metric has been used extensively to study the SNF population. However, as additional data and research becomes available, we may be able to utilize other social risk factors to define the underserved population. We refer readers to the ASPE Report to Congress on Social Risk Factors and Performance Under Medicare's Value-Based Purchasing Programs for additional indicators we could consider for use in the Program, including the LIS Program, ADI, and others. We solicited comment on which demographic variables, social risk indicators, or combination of indicators would be most appropriate for assessing disparities and measuring improvements in health equity in the SNF VBP Program for the health equity approaches described in this RFI. We provide a summary of the comments we received, and our responses, later in this section.

b. Approaches To Assessing Health Equity Advancement in the SNF VBP Program

We are interested in developing approaches that would incentivize the advancement of health equity for all SNFs, focusing on improving care for all residents, including those who may currently face disparities in their care. Such an approach would aim to include as many SNFs as possible and would not be restricted to those serving 20 percent or more of residents with DES like the Health Equity Adjustment we discuss in section VIII.E.4. of this final rule. There are many different ways to add a health equity-focused component or adjustment to the Program to meet these objectives. In the FY 2023 SNF PPS proposed rule (87 FR 22789), we requested commenters' views on which adjustments would be most effective for the SNF VBP Program to account for any equity gaps that we may observe in the SNF setting. Although many commenters were supportive of incorporating health equity-focused adjustments into the Program, there was no clear consensus on the type of adjustment that would be most effective. Therefore, we requested additional comments on potential approaches to assessing health equity advancement in the Program. We have outlined approaches to assess underlying equity gaps or designed to promote health equity, which may be considered for use in the Program and grouped them into three broad categories for assessment: applying points to current measures, equity-focused measures, and composite measures. The remainder of this section discusses these categories and relevant questions to consider for each. We also highlight two methods used for calculating disparities.

We identified four key considerations that we should consider when employing quality measurement as a tool to address health disparities and advance health equity. When considering which equity-focused measures could be prioritized for development for SNF VBP, we examined past reports that assess such measures and encouraged commenters to review each category against the following considerations:

• To what extent does the approach support consumer choice? It is essential that quality measures reflect consumer needs and allow consumers to make informed choices about their care. In the Program, measure data is available on the Provider Data Catalog website. Having access to and understanding this data would empower consumers with more information in selecting their optimal SNF, including one that demonstrates greater performance in advancing equity.

• How long would it take to include this approach in the program? Some approaches may take considerably longer than others to include in the Program. For instance, we intend to consult the consensus-based entity for any new measures we proposed to ensure to have appropriate feedback, which would add additional time to their development. Although we do not want this time to deter interested parties from recommending measures for inclusion in the program, we are interested in understanding commenters' prioritization of measures as it relates to the amount of time they may take to implement when deciding on the best approach for the Program.

• Is this approach aligned with other Medicare quality reporting and VBP programs? Implementing quality initiatives requires time and resources. It is one of our top priorities to ensure alignment between quality programs to limit the burden of quality reporting and implementation. Thus, it is important for us to consider when developing a health equity component, if and how other programs are incorporating health equity to align and standardize measures wherever possible.

• What is the impact on populations that are underserved or the SNFs that serve these populations? Although the goal of a health equity-focused adjustment to the Program would be to decrease disparities and incentivize high-quality care for all populations including those who are underserved, we also want to create appropriate guardrails that protect SNFs against potential unintended consequences. It is important for us to understand if any proposed approach may create potential negative consequences for residents who are underserved or the SNFs that treat these individuals and any steps we can take to mitigate that.

(1) Applying Points to Current Measures To Assess Health Equity

The first category of health equity advancement approaches we requested comments on are mechanisms that apply points to current measures to assess health equity, rewarding SNFs based on the extent to which they provide equitable care. This category affords each SNF the ability to score additional points for all measures where they demonstrate a high level of equity or a reduction in disparities over time. An approach that applies points to current measures to assess health equity could include, but is not limited to, the following:

• Points applied to one, some, or all measures for SNFs that achieve higher health equity performance on those measures. This would include measuring a SNF's performance on each measure for residents who are undeserved and comparing that to the same SNF's performance among all other residents on the same measures effectively assessing health equity gaps. This approach would utilize a Within-Facility Disparity method for assessing disparities, as described in more detail later in this section.
• Points applied to one, some, or all measures for SNFs that have better performance among residents who are underserved. This would include only measuring performance among residents who are underserved and comparing that performance across all SNFs. This approach would utilize an Across-Facility Disparity method for assessing disparities, as described in more detail later in this section.
• Points applied to one, some, or all measures based on a weighted average of each SNF's performance among resident groups with the worst and best outcomes for each measure. We could define resident groups by any social risk indicator, for example DES. This approach measures performance among all residents in the SNF and places greater weight on the performance of the worst performing group, with the goal of raising the quality floor at every SNF.

We note that any social risk indicator could be used to assess health equity gaps. We welcomed comments on any approach outlined in this section or any other approach that applies additional points to current measures to assess health equity that should be considered for inclusion in the SNF VBP Program.

(2) New Measure Approach

The second category of health equity advancement approaches we requested comments on is a new health equity-focused measure, which would be included as one of the 10 allowable measures in the Program. This category includes the development of a new measure that assesses health equity and could include a structural, process, or outcome measure. A health equity-focused measure would be included as one of the measures in the program and thus would be included in the scoring calculations like other measures. A health equity-focused measure could include, but is not limited to, the following:

• A structural measure. For example, a facility commitment to health equity measure, in which SNFs are assessed on factors like leadership engagement, data collection, and improvement activities that support addressing disparities in quality outcomes. This measure could be similar to the “Hospital Commitment to Health Equity” measure that was finalized in the FY 2023 Inpatient Prospective Payment System/Long Term Care Hospital Prospective Payment System final rule (87 FR 48785).
• A process measure. For example, a drivers of health measure, in which residents are screened for specific health-related social needs (HRSNs) to ensure a successful transition home, like transportation or food insecurity. This measure could be similar to the “Screening for Social Drivers of Health” measure that was finalized in the FY 2023 Inpatient Prospective Payment System/Long Term Care Hospital Prospective Payment System final rule (87 FR 48785).
• An outcome measure. For example, a measure that is calculated using data stratified for specific populations that are underserved, such as residents with DES.

We note that each of these possible measures are only suggestions for what might be included in the Program. We welcomed comments on any measures that should be considered for inclusion in the SNF VBP Program including the ones described in this section and what data sources should be considered to construct those measures.

(3) Composite Measure Approach

The third category of health equity advancement approaches we requested comments on is the development and implementation of a new health equity-focused composite measure. An equity-focused composite measure would be included as one of the 10 allowable measures in the program and thus would be included in the scoring calculations like other measures. Generally, a composite measure can provide a simplified view of a rather complex topic by combining multiple factors into one measure. A composite measure could include, but is not limited to, the following:

• A composite of all measure scores for residents who are underserved to compare across all SNFs. This could utilize an Across-Facility Disparity method for assessing disparities, as described in more detail later in this section.
• A composite of the health disparity performance within each SNF for some or all measures. This approach could utilize a Within-Facility Disparity method for assessing disparities, as described in more detail later in this section.

We noted that any social risk indicator could be used to assess health equity gaps. We welcomed comments on each of the composite measures described in this section. We also welcomed comments on the specific factors or measures that should be included in a composite measure.

In considering whether to include in the Program any of the approaches described in this section, points applied to current measures based on equity, new measures, or composite measures, we encouraged commenters to consider the following questions:

To what extent do these approaches support consumer choice? What approaches described in this section best support consumer choice? Would any approach be easier to interpret than others? Would any of the approaches described in this section provide information that other approaches would not that would aid consumer choice? Are there other factors we should consider in developing any of the approaches described in this section that are easiest for consumers to utilize and understand? How should any of the approaches described in this section be displayed and shared with consumers to facilitate understanding of how to interpret the approach?

How long would it take to include this approach in the program? If some approaches would take longer to implement, should they still be considered for inclusion in the Program or should a different approach be prioritized? For instance, a measure that is already being utilized by another program could be implemented sooner than a measure that still needs to be developed. Should any of the approaches described in this section be considered regardless of the time it would take to include the approach in the Program?

Is this approach aligned with other Medicare quality reporting and VBP programs? Are there similar approaches to those described in this section that are aligned with other programs that we should consider for SNF VBP? If any of the approaches described in this section are not aligned with other programs, should they still be considered for inclusion in the Program? If these approaches are only aligned somewhat with other programs, should they still be considered for inclusion in the Program? Several other programs, including the End-Stage Renal Disease Quality Incentive Program, the Merit-based Incentive Payment System, the Hospital Inpatient Quality Reporting Program, the Inpatient Psychiatric Facility Quality Reporting Program, and the PPS-Exempt Cancer Hospital Quality Reporting Program also submitted equity-focused measures to the 2022 MUC List that could be considered for the Program. Further, we are in the process of developing a Hospital Equity Index. Should any of these measures be considered for SNF VBP?

What is the impact on populations that are underserved or the SNFs that serve these populations? Are there any potential impacts, including negative or positive unintended consequences, that could occur when implementing the approaches described in this section? Are there steps we should take to mitigate any potential negative unintended consequences? How can we ensure these approaches provide a strong enough incentive to improve care for all populations by identifying areas of inequities? We are interested in all perspectives and particularly of those living in and serving underserved communities.

(4) Disparity Method Approaches

Many of the approaches described previously in this section would rely on calculating disparities. There are several different conceptual approaches to calculating disparities to assess health equity gaps. Currently in the acute care setting, two complementary approaches are used to confidentially provide disparity information to hospitals for a subset of existing measures. The first approach, referred to as the Within-Facility Disparity method, compares measure performance results for a single measure between subgroups of patients with and without a given factor. This type of comparison directly estimates disparities in outcomes between subgroups and can be helpful to identify potential disparities in care. This type of approach can be used with most measures that include patient-level data. The second approach, referred to as the Across-Facility Disparity method, provides performance on measures for only the subgroup of patients with a particular social risk factor. These approaches can be used by a SNF to compare their own measure performance on a particular subgroup of patients against subgroup-specific State and national benchmarks. Alone, each approach may provide an incomplete picture of disparities in care for a particular measure, but when reported together with overall quality performance, these approaches may provide detailed information about where differences in care may exist or where additional scrutiny may be appropriate. For example, the Across-Facility Disparity method indicates that a SNF underperformed (when compared to other SNFs on average) for patients with a given social risk indicator, which would signal the need to improve care for this population. However, if the SNF also underperformed for patients without that social risk indicator (the Within-Facility Disparity method, as described earlier in this section), the measured difference, or disparity in care, could be negligible even though performance for the group that particular social risk factor remains poor. We refer readers to the technical report describing the CMS Disparity Methods in detail, as well as the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through 38407) and the posted Disparity Methods Updates and Specifications Report posted on the QualityNet website at https://qualitynet.cms.gov/inpatient/measures/disparity-methods.

We solicited comments on all of the approaches to assessing health equity advancement described above, as well as whether similar approaches to the two discussed in the previous paragraph could be used for calculating disparities to assess health equity in a SNF. These calculations would then be used for scoring purposes for each of the approaches described previously in this section, either to calculate a SNF's performance on a new measure or a composite measure, or to determine the amount of points that should be applied to current measures to assess heath equity. We provide a summary of the comments we received, and our responses, later in this section.

c. Other Approaches To Assessing Health Equity Advancement in the SNF VBP Program

There are also many other health equity approaches that could be considered for inclusion in the Program. In particular, we explored risk adjustment, stratification/peer grouping, and adding improvement points when developing the Health Equity Adjustment discussed in section VIII.E.4. of this final rule. We have specific concerns when applying each of those approaches to the SNF VBP Program independently; however, we solicited comment on the potential of incorporating these approaches. We provide a summary of the comments we received, and our responses, later in this section.

d. Development of Domains and Domain Weighting for Inclusion in the SNF VBP Program

As we expand the number of measures on which we assess performance under the SNF VBP Program, we are considering whether we should group the measures into measure domains. Creating domains would align the SNF VBP Program with other CMS programs such as the Hospital Value-Based Purchasing (VBP) Program. The Hospital VBP Program currently groups its measures into four domains that are defined based on measure type, and then weights the sum of a hospital's performance score on each measure in the domain such that the domain is weighted at 25 percent of the hospital's total performance score. Although the Hospital VBP Program uses four domains, each with a 25 percent weight, we could consider for the SNF VBP Program, grouping measures into a different number of domains and then weighting each domain by different amounts.

We solicited comments on whether we should consider proposing the addition of quality domains for future program years. We also solicited comments on if those domains should be utilized to advance health equity in the Program.

The following is a summary of all the comments we received on this health equity RFI including resident-level indicators and geographic-level indices to assess disparities in healthcare quality, approaches to assessing health equity, other approaches to assessing health equity, and the development of domains and domain weighting.

Comment: A few commenters supported CMS implementing policies in the SNF VBP Program to address health equity. One commenter recommended that CMS make facility level data on race and ethnicity available to help SNFs address inequities. One commenter suggested CMS align SDOH data across all care settings for future health equity measures to ease reporting burden. One commenter suggested CMS prioritize measures that address recurring resident and caregiver complaints as a way to address health inequities. A few commenters expressed concerns about the Program utilizing these types of indices to assess disparities as current measure designs may mask regional and individual disparities. One commenter supported CMS applying points to the Program measures to incentivize improving health equity. One commenter recommended CMS expand the scope of practice for advanced practice providers to help support health equity efforts. A few commenters recommended CMS create domain weights to address health equity as they believe that some measures and data are more impacted by inequity than others.

Response: We will take this feedback into consideration as we develop potential future health equity-related policies.

F. Updates to the Extraordinary Circumstances Exception Policy Regulation Text

In the FY 2019 SNF PPS final rule (83 FR 39280 through 39281), we adopted an Extraordinary Circumstances Exception (ECE) policy for the SNF VBP Program. We have also codified this policy in our regulations at § 413.338(d)(4).

To accommodate the SNF VBP Program's expansion to additional quality measures and apply the ECE policy to those measures, we proposed to update our regulations at § 413.338(d)(4)(v) to remove the specific reference to the SNF Readmission Measure. We proposed that the new language will specify, in part, that we would calculate a SNF performance score for a program year that does not include the SNF's “performance during the calendar months affected by the extraordinary circumstance.”

We solicited public comment on this proposal.

We did not receive public comments on this provision and therefore, we are finalizing as proposed.

G. Updates to the Validation Processes for the SNF VBP Program

1. Background

Section 1888(h)(12) of the Act requires the Secretary to apply a validation process to SNF VBP Program measures and “the data submitted under [section 1888(e)(6)] [. . .] as appropriate[. . .].”

We previously finalized a validation approach for the SNFRM and codified that approach at § 413.338(j) of our regulations. In the FY 2023 SNF PPS proposed rule (87 FR 22788 through 22789), we requested comments on the validation of additional SNF measures and assessment data. In the FY 2023 SNF PPS final rule (87 FR 47595 through 47596), we summarized commenters' views and stated that we would take this feedback into consideration as we develop our policies for future rulemaking.

Beginning with the FY 2026 program year, the SNFRM will no longer be the only measure in the SNF VBP Program. We adopted a second claims-based measure, SNF HAI, beginning with that program year and proposed to replace the SNFRM with another claims-based measure, the SNF WS PPR measure, beginning with the FY 2028 program year. We also adopted the DTC PAC SNF measure, another claims-based measure, beginning with the FY 2027 program year and proposed a fourth claims-based measure, Long Stay Hospitalization, beginning with that program year. We adopted the Total Nurse Staffing measure, which is calculated using Payroll Based Journal (PBJ) data, beginning with the FY 2026 program year and proposed to adopt the Nursing Staff Turnover measure, which is also calculated using PBJ data, beginning with the FY 2026 program year. We also proposed to adopt the DC Function and the Falls with Major Injury (Long-Stay) measures calculated using Minimum Data Set (MDS) data beginning with the FY 2027 program year. The addition of measures calculated from these data sources has prompted us to consider the most feasible way to expand our validation program under the SNF VBP Program.

After considering our existing validation process and the data sources for the new measures, and for the reasons discussed more fully below, we proposed to: (1) apply the validation process we previously adopted for the SNFRM to include all claims-based measures; (2) adopt a validation process that applies to SNF VBP measures for which the data source is PBJ data; and (3) adopt a validation process that applies to SNF VBP measures for which the data source is MDS data. We believe these new validation policies will ensure that the data we use to calculate the SNF VBP measures are accurate for quality measurement purposes.

We note that these new validation policies will apply only to the SNF VBP Program, and we intend to propose a validation process that would apply to the data SNFs report under the SNF QRP, in future rulemaking.

2. Application of the Existing Validation Process for the SNFRM to All Claims-Based Measures Reported in the SNF VBP Program

Beginning with the FY 2026 program year, we will need to validate the SNF HAI measure and beginning with the FY 2027 program year, we will need to validate the Long Stay Hospitalization and DTC PAC SNF measures to meet our statutory requirements. Beginning with the FY 2028 program year, we will also need to validate the SNF WS PPR measure. Therefore, we proposed to expand the previously adopted SNFRM validation process to include all claims-based measures, including the SNF HAI, Long Stay Hospitalization, DTC PAC SNF, and SNF WS PPR measures, as well as any other claims-based measures we may adopt for the SNF VBP Program in the future.

The SNF HAI measure is calculated using Medicare SNF FFS claims data and Medicare inpatient hospital claims data. As discussed in the FY 2023 SNF PPS final rule (87 FR 47590), information reported through claims are validated for accuracy by Medicare Administrative Contractors (MACs) who use software to determine whether billed services are medically necessary and should be covered by Medicare, review claims to identify any ambiguities or irregularities, and use a quality assurance process to help ensure quality and consistency in claim review and processing. They conduct prepayment and post-payment audits of Medicare claims, using both random selection and targeted reviews based on analyses of claims data.

Beginning with the FY 2027 program year, we proposed to adopt the Long Stay Hospitalization measure in the SNF VBP Program. This measure utilizes SNF FFS claims and inpatient hospital claims data. We believe that adopting the existing MAC's process of validating claims for medical necessity through targeted and random audits, as detailed in the prior paragraph, satisfies our statutory requirement to adopt a validation process for the Long Stay Hospitalization measure for the SNF VBP Program.

The DTC PAC SNF measure also uses claims-based data, including data from the “Patient Discharge Status Code.” We refer readers to the FY 2023 SNF PPS final rule (87 FR 47577 through 47578) for additional discussion of the data source for the DTC PAC SNF measure. We also refer readers to the FY 2017 SNF PPS final rule (81 FR 52021 through 52029) for a thorough analysis on the accuracy of utilizing the discharge status field. We believe that adopting the existing MAC's process for validating the claims portion of the DTC PAC SNF measure for payment accuracy satisfies our statutory requirement to adopt a validation process for the SNF VBP Program because MACs review claims for medical necessity, ambiguities, and quality assurance through random and targeted reviews, as detailed in the second paragraph of this section.

Beginning with the FY 2028 program year, we proposed to replace the SNFRM with the SNF WS PPR measure. The SNFRM and SNF WS PPR measure utilize the same claims-based data sources. Therefore, the SNFRM's validation process based on data that are validated for accuracy by MACs as detailed in the second paragraph of this section, satisfies the statutory requirement to adopt a validation process for the SNF WS PPR measure for the SNF VBP Program.

We solicited public comment on the proposed application of our previously finalized validation process to all claim-based measures in the SNF VBP Program and also proposed to codify it at § 413.338(j) of our regulations.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: A few commenters supported our proposal to apply our previously finalized validation process to all claim-based measures in the SNF VBP Program.

Response: We thank commenters for their support.

After consideration of public comments, we are finalizing the application of our previously finalized validation process to all claims-based measures in the SNF VBP Program.

3. Adoption of a Validation Process That Applies to SNF VBP Measures That Are Calculated Using PBJ Data

Beginning with the FY 2026 program year, the Total Nurse Staffing measure, adopted in the FY 2023 SNF PPS final rule, and the Nursing Staff Turnover measure, are calculated using PBJ data that nursing facilities with SNF beds are already required to report to CMS. PBJ data includes direct care staffing information (including agency and contract staff) based on payroll and other auditable data. CMS conducts quarterly audits aimed at verifying that the staffing hours submitted by facilities are aligned with the hours staff were paid to work over the same timeframe. The PBJ audit process requires selected facilities to submit documentation, that may include payroll, invoice, or contractual obligation data, supporting the staffing hours reported in the PBJ data. This documentation of hours is compared against the reported PBJ staffing hours data and a facility whose audit identifies significant inaccuracies between the hours reported and the hours verified will be presumed to have low levels of staffing. We believe that this existing PBJ data audit process is sufficient to ensure that the PBJ data we use to calculate the Total Nurse Staffing and Nursing Staff Turnover measures are an accurate representation of a facility's staffing. Accordingly, we proposed to adopt that process for purposes of validating SNF VBP measures that are calculated using PBJ data. We also proposed to codify this policy at § 413.338(j) of our regulations.

We solicited public comment on our proposal to adopt the above validation process that applies to measures calculated using the PBJ data.

We received public comments on this proposal. The following is a summary of the comments we received and our responses.

Comment: A few commenters supported our proposed approach to validate PBJ-based measures with existing processes.

Response: We thank commenters for their support.

After consideration of public comments, we are finalizing the validation process for SNF VBP measures that are calculated using PBJ data as proposed.

4. Adoption of a Validation Process That Applies to SNF VBP Measures That Are Calculated Using MDS Data

We proposed to adopt two MDS measures in the SNF VBP Program, the DC Function and Falls with Major Injury (Long-Stay) measures beginning with the FY 2027 program year/FY 2025 performance period. The MDS is a federally mandated resident assessment instrument that is required to be completed for all residents in a Medicare or Medicaid certified nursing facility, and for residents whose stay is covered under SNF PPS in a non-critical access hospital swing bed facility. The MDS “includes the resident in the assessment process, and uses standard protocols used in other settings . . . supporting the primary legislative intent that MDS be a tool to improve clinical assessment and supports the credibility of programs that rely on MDS.” There is no current process to verify that the MDS data submitted by providers to CMS for quality measure calculations is accurate for use in our SNF quality reporting and value-based purchasing programs. While MDS data are audited to ensure accurate payments, we do not believe that this audit process focuses sufficiently on the Program's quality measurement data for use in a quality reporting or value-based purchasing program. While the update to MDS 3.0 was designed to improve the reliability, accuracy, and usefulness of reporting than prior versions, we believe we need to validate MDS data when those data are used for the purpose of a quality reporting or value-based purchasing program. Therefore, we proposed to adopt a new validation method that we will apply to the SNF VBP measures that are calculated using MDS data to meet our statutory requirement. This method is similar to the method we use to validate measures reported by hospitals under the Hospital Inpatient Quality Reporting Program.

We proposed to validate the MDS data used to calculate these measures as follows:

• We proposed to randomly select, on an annual basis, up to 1,500 active and current SNFs, including non-critical access hospital swing bed facilities providing SNF-level services, that submit at least one MDS record in the calendar year 3 years prior to the fiscal year of the relevant program year or were included in the SNF VBP Program in the year prior to the relevant program year. For example, for the FY 2027 SNF VBP Program, we would choose up to 1,500 SNFs that submitted at least one MDS record in calendar year 2024 or were participating in the FY 2026 SNF VBP Program/FY 2024 performance period for validation in FY 2025.
• We proposed that the validation contractor will, for each quarter that applies to validation, request up to 10 randomly selected medical charts from each of the selected SNFs.
• We proposed that the validation contractor will request either digital or paper copies of the randomly selected medical charts from each SNF selected for audit. The SNF will have 45 days from the date of the request (as documented on the request) to submit the requested records to the validation contractor. If the SNF has not complied within 30 days, the validation contractor will send the SNF a reminder to inform the SNF that it must return digital or paper copies of the requested medical records within 45 calendar days following the date of the initial validation contractor medical record request.

We believe the process will be minimally burdensome on SNFs selected to submit up to 10 charts.

We intend to propose a penalty that applies to a SNF that either does not submit the requested number of charts or that we otherwise conclude has not achieved a certain validation threshold in future rulemaking. We also intend to propose in future rulemaking the process by which we would evaluate the submitted medical charts against the MDS to determine the validity of the MDS data used to calculate the measure results. We invited public comment on what that process could include.

We solicited public comments on our proposal to adopt the above validation process for MDS measures beginning with the FY 2027 program year. The following is a summary of the comments we received and our responses.

Comment: Several commenters supported the proposed approach to validate MDS-based measures through random audits. One commenter recommended CMS include family and caregiver feedback into the development of this process.

Response: We thank the commenters for their support.

Comment: A few commenters supported the proposal to validate MDS data for the SNF QRP to ensure data submitted is not erroneous or incomplete.

Response: We thank the commenters for their support.

Comment: A few commenters who supported validation of MDS data recommended that CMS implement validation of MDS data prior to using MDS-based measures in the SNF VBP Program.

Response: We believe it is not feasible to begin validating MDS data submitted for program years before the FY 2027 SNF VBP program year. We do not believe that delaying the expansion of the SNF VBP Program until MDS data validation is in place is appropriate because MDS-based measures have been used within the SNF QRP for many years. Because SNFs have had extensive experience with MDS-based quality measurement through participation in the SNF QRP, we believe that SNFs have had ample time to ensure the data's accuracy prior to use in the SNF VBP Program and that it is appropriate to move forward with using these measure types in parallel with our implementation of new validation processes.

Comment: A few commenters recommended that CMS not include a penalty for SNFs that fail validation of MDS-based measures because facilities are already penalized through the withholding of funds.

Response: We will take this comment into consideration as we develop additional validation policies for the SNF VBP Program. However, we do not agree that we should hold SNFs harmless for failing validation. We believe that a robust validation program ensures that the most accurate quality data possible are scored for purposes of the SNF VBP Program.

Comment: A few commenters did not support the proposal to validate MDS-based measures. One commenter recommended CMS phase out self-reported measures instead of implementing a validation process. A few commenters expressed that MDS based data are extensively validated through other means (State audits and surveys) and that a new process is an inefficient use of funds. One commenter stated that they believed the rationale for validating MDS-based measures contradicts the rationale used to validate the claims-based measures.

Response: We believe that prioritizing validation for those data submissions already required of SNFs represents a more practical, less burdensome policy for SNFs than adopting new measures to replace MDS-based measurement. MDS data are statutorily required to be submitted to the SNF QRP by SNFs under section 1888(e)(6) of the Act. Because SNFs already submit MDS data pursuant to other quality reporting requirements, we believe that MDS-based measures strike an appropriate balance between effective quality measurement and reporting burden.

We recognize that MDS audits are being completed though other means. We believe that these audits, which are effective for their use cases, are insufficient to ensure the accuracy of MDS data elements used for the SNF VBP Program's current and future quality measures. For example, State surveyors may review MDS data to ensure that it meets State standards, which may not align with ensuring the data are accurate for use in the Program's quality measures. We believe that a validation process is needed for the SNF VBP Program that includes auditing the MDS data elements that are used in the measures to ensure the data are accurate. Additionally, we believe that ensuring the Program's data are an accurate representation of a SNFs quality of care is an effective use of funds. Ensuring accurate data means that our beneficiaries can trust the publicly available quality data and make better informed decisions about their care.

We interpret the comment “contradicting rationale” to be questioning why the audit of MDS data for payment purposes does not focus sufficiently on the Program's quality measurement data for use in a quality reporting or value-based purchasing program as stated in the proposed rule (88 FR 21398). We note that PBJ measures must be auditable under 42 CFR 483.70 and SNF claims and other payment-related information must be audited under section 1983 of the Act. Therefore, we believe that the claims and PBJ measure data elements that are audited for their respective purposes are sufficient with the SNF VBP Program's statutory requirement for validating claims-based and PBJ-based quality measures. For example, the hospitalizations and staffing hours data elements included in the SNF WS PPR, Total Nurse Staffing and Nursing Staff Turnover measures are the core tenets of both their respective measures, and ensuring that claims are valid for payment or ensuring that staffing is capture for regulatory oversite. Although MDS data is audited for other purposes, we feel that a more comprehensive validation process is required for MDS-based quality measures. We further clarify that these existing MDS data audits only review a portion of MDS elements used in the current measures and that the Program's MDS-based quality measures are calculated using data elements that are not consistently reviewed in these audits. We believe that a new validation process is necessary because exiting payment audits do not audit all the MDS data elements needed for the quality measures.

Comment: A few commenters did not support CMS pulling up to 10 charts per SNF as they do not believe it is minimally burdensome.

Response: We proposed this 10-chart maximum because we believe that it strikes the appropriate balance between creating a relatively reliable annual validation estimate with a quantity of charts that are least burdensome to SNFs. The 10 chart maximum is also generally consistent with similar policies we have adopted for the Hospital IQR Program and HAC Reduction Program. For the FY 2026 program year, we request up to 8 charts per quarter for the clinical process of care category of measures and up to 8 charts per quarter for the eCQM category of measures, for a total of up to 16 charts per quarter for the Hospital IQR Program validation, and we request up to 10 charts per quarter for the Hospital-Acquired Condition Reduction Program validation ( https://qualitynet.cms.gov/files/648726a004f753001cd0577b?filename=IP_FY26_ValFactSheet_05082023.pdf).

After consideration of public comments, we are finalizing the validation process for MDS-based measures in the SNF VBP Program as proposed.

H. SNF Value-Based Incentive Payments for FY 2024

We refer readers to the FY 2018 SNF PPS final rule (82 FR 36616 through 36621) for discussion of the exchange function methodology that we have adopted for the Program, as well as the specific form of the exchange function (logistic, or S-shaped curve) that we finalized, and the payback percentage of 60 percent of the amounts withheld from SNFs' Medicare payments as required by the SNF VBP Program statute.

We also discussed the process that we undertake for reducing SNFs' adjusted Federal per diem rates under the Medicare SNF PPS and awarding value-based incentive payments in the FY 2019 SNF PPS final rule (83 FR 39281 through 39282).

For the FY 2024 SNF VBP program year, we will reduce SNFs' adjusted Federal per diem rates for the fiscal year by the applicable percentage specified under section 1888(h)(6)(B) of the Act, 2 percent, and will remit value-based incentive payments to each SNF based on their SNF Performance Score, which is calculated based on their performance on the Program's quality measure.

I. Public Reporting on the Provider Data Catalog Website

Section 1888(g)(6) of the Act requires the Secretary to establish procedures to make SNFs' performance information on the SNFRM and the SNF WS PPR available to the public on the Nursing Home Compare website or a successor website, and to provide SNFs an opportunity to review and submit corrections to that information prior to its publication. We began publishing SNFs' performance information on the SNFRM in accordance with this provision on October 1, 2017. In December 2020, we retired the Nursing Home Compare website and are now using the Provider Data Catalog website ( https://data.cms.gov/provider-data/) to make quality data available to the public, including SNF VBP performance information. We will begin publishing performance information on the SNF WS PPR measure when that measure is implemented beginning in the FY 2028 program year.

Additionally, section 1888(h)(9)(A) of the Act requires the Secretary to make available to the public certain information on SNFs' performance under the SNF VBP Program, including their SNF Performance Scores and rankings. Section 1888(h)(9)(B) of the Act requires the Secretary to post aggregate information on the Program, including the range of SNF Performance Scores and the number of SNFs receiving value-based incentive payments, and the range and total amount of those payments.

In the FY 2017 SNF PPS final rule (81 FR 52006 through 52009), we discussed the statutory requirements governing confidential feedback reports and public reporting of SNFs' performance information under the SNF VBP Program and finalized our two-phased review and correction process. In the FY 2018 SNF PPS final rule (82 FR 36621 through 36623), we finalized additional requirements for phase two of our review and correction process, a policy to publish SNF VBP Program performance information on the Nursing Home Compare or a successor website after SNFs have had the opportunity to review and submit corrections to that information. In that final rule, we also finalized the requirements to rank SNFs and adopted data elements that are included in the ranking to provide consumers and interested parties with the necessary information to evaluate SNF's performance under the Program. In the FY 2020 SNF PPS final rule (84 FR 38823 through 38825), we finalized a policy to suppress from public display SNF VBP performance information for low-volume SNFs and finalized updates to the phase one review and correction deadline. In the FY 2021 SNF PPS final rule (85 FR 47626 through 47627), we finalized additional updates to the phase one review and correction deadline. In the FY 2022 SNF PPS final rule (86 FR 42516 through 42517), we finalized a phase one review and correction claims “snapshot” policy. In the FY 2023 SNF PPS final rule (87 FR 47591 through 47592), we finalized updates to our data suppression policy for low-volume SNFs due to the addition of new measures and case and measure minimum policies.

IX. Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

Section 488.436 provides a facility the option to waive its right to a hearing in writing and receive a 35 percent reduction in the amount of civil money penalties (CMPs) owed in lieu of contesting the enforcement action. This regulation was first adopted in a 1994 final rule (59 FR 56116, 56243), with minor corrections made to the regulation text in 1997 (62 FR 44221) and in 2011 (76 FR 15127) to implement section 6111 of the Affordable Care Act of 2010. Over the years, we have observed that most facilities who have been imposed CMPs do not request a hearing to appeal the survey findings of noncompliance on which their CMPs are based.

In CY 2016, 81 percent of LTC facilities submitted a written waiver of a hearing and an additional 15 percent of facilities did not submit a waiver although they did not contest the penalty and its basis. Only 4 percent of facilities availed themselves of the full hearing process. The data from CY 2018 and CY 2019 stayed fairly consistent with 80 percent of facilities submitting a written waiver of a hearing and 14 percent of facilities not submitting the waiver nor contesting the penalty and its basis. Only 6 percent of facilities availed themselves of the full hearing process. In CY 2020, 81 percent of facilities submitted a written waiver of the hearing, 15 percent of facilities did not submit a waiver nor contest the penalty and its basis, and only 4 percent of facilities availed themselves of the full hearing process. In CY 2021, 91 percent of facilities submitted a written waiver of the hearing, 7 percent of facilities did not submit the waiver nor contest the penalty and its basis, and only 2 percent of facilities utilized the full hearing process. Data from CY 2022 continues this trend showing that 81 percent of LTC facilities submitted a written waiver of their hearing rights and 17 percent of facilities did not submit a waiver of appeal rights but did not contest the penalty nor its basis. Again, only 2 percent of facilities availed themselves of the full hearing process in CY 2022. Therefore, based on our experience with LTC facilities with imposed CMPs and the input provided by our CMS Locations (formerly referred to as Regional Offices) that impose and collect CMPs, we proposed to revise these requirements at § 488.436 by creating a constructive waiver process.

Specifically, we proposed to revise the current written waiver process to allow a constructive waiver that retains the accompanying 35 percent penalty reduction, however, we will revisit the appropriateness of that penalty reduction in a future rulemaking, if warranted, as discussed further below. Removal of the facility's requirement to submit a separate written request to waive their right to appeal would result in a cost and time savings for CMS, which currently receives and processes these waivers. This will allow CMS to reallocate this time and funding currently spent processing these waivers to bolstering other oversight and enforcement activities, including providing additional focus on nursing home compliance, as well as to cases involving facilities that choose to contest our findings through the Departmental Appeals Board. Current budgetary constraints have tightened oversight and enforcement resources, in addition to the survey and enforcement backlog resulting from the COVID–19 PHE.

We proposed to amend the language at § 488.436(a) by eliminating the requirement to submit a written waiver and create in its place a constructive waiver process that would operate by default when a timely request for a hearing has not been received. Facilities that wish to request a hearing to contest the noncompliance leading to the imposition of the CMP would continue to follow all applicable appeals process requirements, including those at § 498.40, as currently referenced at § 488.431(d).

Specifically, we proposed to revise § 488.436(a) to state that a facility is deemed to have waived its rights to a hearing if the time period for requesting a hearing has expired and request for a hearing has not been received within the requisite submission time. We have observed that many facilities submitting a request for a waiver of hearing wait until close to the end of the 60-day timeframe within which a waiver must be submitted, thus delaying the ultimate due date of the CMP amount. Under this proposed process, the 35 percent reduction would be applied after the 60-day timeframe.

Given our finalized policy of removing the requirement to actively waive their right to a hearing, we will revisit the appropriateness of that penalty reduction, if warranted by the review, in a future rulemaking. The move to a constructive waiver process in this rule purely reflects the need to reduce costs and paperwork burden for CMS to prioritize current limited Survey and Certification resources for enforcement actions, and we will consider whether the existing penalty reduction is appropriate given this final policy.

We also note that we continue to have the opportunity under § 488.444, to settle CMP cases at any time prior to a final administrative decision for Medicare-only SNFs, State-operated facilities, or other facilities for which our enforcement action prevails, in accordance with § 488.30. This provides the opportunity to settle a case, when warranted, even if the facility's hearing right was not previously waived. Even if a hearing had been requested, if all parties can reach an agreement over deficiencies to be corrected and the CMP to be paid until corrections are made (for example, CMS agrees to lower a CMP amount based on actions the facility has taken to protect resident health and safety), then costly hearing procedures could be avoided. We believe that eliminating the current requirements for a written waiver at § 488.436 will not negatively impact facilities.

In addition to the changes to § 488.436(a), we proposed corresponding changes to §§ 488.432 and 488.442 which currently reference only the written waiver process. We proposed to make conforming changes that establish that a facility is considered to have waived its rights to a hearing if the time period for requesting a hearing has expired, in lieu of a written waiver of appeal rights. Finally, we note that the current requirements at § 488.436(b) would remain unchanged. At the same time, CMS commits to studying its procedures for reviewing and processing waivers and as necessary modernizing those procedures to reduce the amount of time required for documentation review of CMPs.

The proposed revisions were previously proposed and published in the July 18, 2019 proposed rule entitled, “Medicare and Medicaid Programs; Requirements for Long-Term Care Facilities: Regulatory Provisions to Promote Efficiency, and Transparency” (84 FR 34737, 34751). Although on July 14, 2022, we announced an extension of the timeline for publication of the final rule for the 2019 proposals ( see87 FR 42137), we are withdrawing that proposal revising § 488.436 and we re-proposed the revisions for a facility to waive its hearing rights in an effort to gather additional feedback from interested parties ( see FY 2024 SNF PPS proposed rule (88 FR 21316)). While this regulatory action is administrative in nature, in the future, we may assess whether the 35 percent penalty reduction is functioning as intended to make the civil money penalties administrative process more efficient, or whether a lesser penalty reduction is warranted.

We solicited comments from the public addressing any potential circumstances in which facilities' needs or the public interest could best be met or only be met by the use of a written waiver. We received public comments on these proposals. The following is a summary of the comments we received and our responses.

Comment: While the majority of comments received supported the constructive waiver, we did receive several comments opposing the constructive waiver provision. One commenter was concerned that if facilities are no longer required to proactively request a waiver to receive the reduction, there is no longer any corporate acknowledgement that a wrong has occurred that resulted in the penalty. The commenter stated that the reduced penalties would become a cost of doing business. Another commenter stated that the Federal nursing home regulations are the minimum standards LTC facilities agree to meet. The commenter stated that when a facility is issued a deficiency for a violation of those minimum standards, they should not automatically be given a 35 percent reduction solely because they decided to not appeal the deficiency finding, as CMPs are meant to be a deterrent and penalize LTC facilities who have violated the minimum requirements for participation. The commenter stated that an automatic 35 percent reduction serves as a reward to those facilities who flout the minimum standards and have actually been cited at actual harm or immediate jeopardy. Many commented that CMS already imposes comparatively few CMPs because, as a matter of policy, it generally limits CMPs to deficiencies that are cited for causing actual harm or putting residents in immediate jeopardy classifications of severity applied to less than 4 percent of all deficiencies observed in facility surveys. Some commenters stated that most deficiencies have no financial consequence, no matter how serious the harm to residents. They further stated that CMS provides no real rationale for the proposed rule, which creates a financial windfall of millions of dollars for LTC facilities. They were concerned that this is a signal to SNFs that compliance with regulations is not mandatory and effectively reduces the enforcement efforts of CMS. Another commenter stated that the financial repercussions facilities may face for violating regulations incentivize better care. Eliminating the requirement that facilities waive their rights to challenge CMS findings removes an incentive for facilities to comply with the regulations.

Response: We appreciate the comments raised, but we believe clarification and modernization to improve efficiencies are warranted on the current waivers process. In CY 2022, 81 percent of LTC facilities submitted a written waiver of the hearing and 17 percent of facilities did not submit a waiver but did not contest the penalty and its basis. Only 2 percent of facilities actually contested the imposed penalty and its basis. The majority of facilities are already submitting a waiver, as is currently required, and receiving the reduction; consequently, the revision to the regulation would not have a significant effect on the amount of CMPs being collected. The constructive waiver process would not affect the frequency of CMPs being imposed, CMS' ability to penalize facilities for infractions, or the publication of facility infractions through Care Compare. We believe that by improving program efficiencies we will be able to divert these resources to strengthening other oversight and enforcement activities. We also note that facilities that waive their right to a hearing may have many reasons for doing so, and the removal of this active waiver requirement is in no way an indication that we are reducing necessary oversight and enforcement activities. We note that the penalty, and the citation that led to the imposition of the penalty, will continue to be posted on Care Compare and indicate that the facility was not in compliance. This will remain the case irrespective of whether the appeal is waived affirmatively or constructively.

Moreover, as stated previously in this section of the final rule, we believe that the subsequent administrative savings from not processing written waivers would allow us to reallocate those resources to activities ensuring the health and safety of residents. However, in light of the comments submitted around the constructive waiver and the changes to the waiver process, we plan to review the appropriateness of the 35 percent penalty reduction in future rulemaking. After consideration of public comments, we are finalizing our proposed changes to the civil money penalty reduction process without modifications.

X. Waiver of Proposed Rulemaking

We ordinarily publish a notice of proposed rulemaking in the Federal Register and invite public comment on the proposed rule. The notice of proposed rulemaking includes a reference to the legal authority under which the rule is proposed, and the terms and substances of the proposed rule or a description of the subjects and issues involved. This procedure can be waived, however, if an agency finds good cause that a notice-and-comment procedure is impracticable, unnecessary, or contrary to the public interest, and incorporates a statement of the finding and its reasons in the rule issued.

In this case, we identified the need for additional conforming changes to the regulatory text after this rule was already proposed, as described in section V.D. of this proposed rule. The conforming changes are minor and necessary to implement the statute. Specifically, in the proposed rule, we revised the regulation text to implement the requirement under section 4121(a)(4) of Division FF of the CAA, 2023 to exclude marriage and family therapist (MFT) services and mental health counselor services (MHC) from SNF consolidated billing for services furnished on or after January 1, 2024. Subsequently, we identified the need for additional conforming changes to the regulatory text. In addition to adding the two new exclusions themselves to the regulation text as set forth in the proposed rule (and as described in section V.D. of this final rule), the existing exclusion for certain telehealth services needs to be revised as well, because it cross-refers to subparagraphs that are now being renumbered as a result of adding the new exclusions. Specifically, a conforming change is needed in the consolidated billing exclusion provision on telehealth services at existing § 411.15(p)(2)(xii) (which, as a result of the other regulation text changes finalized in this rule, will be redesignated § 411.15(p)(2)(xiv)) and in the parallel provider agreement provision on telehealth services at existing § 489.20(s)(12) (which, as a result of the other regulation text changes finalized in this rule, will be redesignated § 489.20(s)(14)). Because these inadvertently omitted additional provisions implement statutory language without any exercise of discretion by the Secretary, we have determined that it would be unnecessary and contrary to public interest to rely on another notice-and-comment period to issue them. We are simply correcting oversights to reflect the policies that we previously proposed, received public comment on, and subsequently finalized in the final rule. For these reasons, we believe there is good cause to waive the requirements for notice and comment.

XI. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et seq.), we are required to provide 60-day notice in the Federal Register and solicit public comment before a “collection of information” requirement is submitted to the Office of Management and Budget (OMB) for review and approval. For the purpose of the PRA and this section of the preamble, collection of information is defined under 5 CFR 1320.3(c) of the PRA's implementing regulations.

To fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the PRA requires that we solicit comment on the following issues:

• The need for the information collection and its usefulness in carrying out the proper functions of our agency.
• The accuracy of our estimate of the information collection burden.
• The quality, utility, and clarity of the information to be collected.
• Recommendations to minimize the information collection burden on the affected public, including automated collection techniques.

We solicited public comment (see section IX.D. of the FY 2024 SNF PPS proposed rule) on each of the aforementioned issues for the following sections of the rule that contained information collection requirements.

A. Wage Estimates

To derive average private sector costs, we used data from the U.S. Bureau of Labor Statistics' (BLS') May 2021 National Occupational Employment and Wage Estimates for all salary estimates ( http://www.bls.gov/oes/current/oes_nat.htm). In this regard, Table 24 presents BLS' mean hourly wage, our estimated cost of fringe benefits and other indirect costs (calculated at 100 percent of salary), and our adjusted hourly wage. See Table 25 for an estimate of the composite wage associated with removing the Application of Functional Assessment/Care Plan measure. See Table 26 for an estimate of the composite wage associated with adopting the Patient/Resident COVID 19 Vaccine measure.

As mentioned, we have adjusted the private sector's employee hourly wage by a factor of 100 percent. This is necessarily a rough adjustment, both because fringe benefits and other indirect costs vary significantly across employers, and because methods of estimating these costs vary widely across studies. Nonetheless, we believe that doubling the hourly wage to estimate total cost is a reasonably accurate estimation method.

B. Information Collection Requirements (ICRs)

1. ICRs Regarding the Skilled Nursing Facility Quality Reporting Program (SNF QRP)

When ready, we intend to account for the following changes under the standard non-rule PRA process that consists of publishing 60- and 30-day Federal Register notices that solicit comment from the public. Consistent with this final rule, the notices will be associated with OMB control number 0938–1140 (CMS–10387). The notices will account for the changes identified in Tables 28 and 29 and changes to MDS (the minimum data set).

In accordance with section 1888(e)(6)(A)(i) of the Act, the Secretary must reduce by 2-percentage points the otherwise applicable annual payment update to a SNF for a fiscal year if the SNF does not comply with the requirements of the SNF QRP for that fiscal year.

In the SNF FY 2024 PPS proposed rule (88 FR 21332 through 21354), we proposed to modify one measure, adopt three new measures, and remove three measures from the SNF QRP. In the SNF FY 2024 PPS proposed rule (88 FR 21360), we also proposed to increase the data completion thresholds for the MDS items. We discussed in detail these information collections in the SNF FY 2024 PPS proposed rule (88 FR 21400). As discussed in section VI.C.2.a.(5) of this final rule, we are not finalizing the CoreQ: SS DC measure for the SNF QRP. Consequently, the ICRs related to the CoreQ: SS DC measure proposal are omitted from this final rule.

As stated in section VII.C.1.a. of this final rule, we proposed to modify the COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP COVID–19 Vaccine) measure beginning with the FY 2025 SNF QRP. While we are not making any changes to the data submission process for the HCP COVID–19 Vaccine measure, we are requiring that for purposes of meeting FY 2025 SNF QRP compliance, SNFs will report data on the measure using the modified numerator definition for at least one self-selected week during each month of the reporting quarter beginning with reporting period of the 4th quarter of CY 2023. Under this requirement, SNFs will continue to report data for the HCP COVID–19 Vaccine measure to the CDC's National Healthcare Safety Network (NHSN) for at least one self-selected week during each month of the reporting quarter. The burden associated with the HCP COVID–19 Vaccine measure is accounted for under OMB control number 0920–1317, entitled “[NCEZID] National Healthcare Safety Network (NHSN) Coronavirus (COVID–19) Surveillance in Healthcare Facilities.” Because we are not making any updates to the form, manner, and timing of data submission for this measure, we are not making any changes to the currently approved (active) requirements or burden estimates under control number 0920–1317. See the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) for a discussion of the form, manner, and timing of data submission of this measure.

As a result of our decision to not adopt the CoreQ: SS DC measure, in this final rule, we are adopting two (instead of three) new measures and removing three measures from the SNF QRP. We present the burden associated with these proposals in the same order they were proposed in the SNF FY 2024 PPS proposed rule (88 FR 21332 through 21354).

As stated in section VII.C.1.b. of this final rule, we proposed to adopt the Discharge Function Score (DC Function) measure beginning with the FY 2025 SNF QRP. This assessment-based quality measure will be calculated using data from the minimum data set (MDS) that are already reported to the Medicare program for payment and quality reporting purposes. The burden is currently approved by OMB under control number 0938–1140 (CMS–10387). Under this requirement, there will be no additional burden for SNFs since it does not require the collection of new or revised data elements.

As stated in section VII.C.1.c. of this final rule, we proposed to remove the Application of Percent of Long-Term Care Hospital (LTCH) Patients with an Admission and Discharge Functional Assessment and a Care Plan that Addresses Function (Application of Functional Assessment/Care Plan) measure beginning with the FY 2025 SNF QRP. We believe that the removal of the measure will result in a decrease of 18 seconds (0.3 minutes or 0.005 hrs) of clinical staff time at admission beginning with the FY 2025 SNF QRP. We believe that the MDS item affected by the removal of the Application of Functional Assessment/Care Plan measure is completed by Occupational Therapists (OT), Physical Therapists (PT), Registered Nurses (RN), Licensed Practical and Licensed Vocational Nurses (LVN), and/or Speech-Language Pathologists (SLP) depending on the functional goal selected. We identified the staff type per MDS item based on past SNF burden calculations. Our assumptions for staff type were based on the categories generally necessary to perform an assessment, however, individual SNFs determine the staffing resources necessary. Therefore, we averaged BLS' National Occupational Employment and Wage Estimates (See Table 25) for these labor types and established a composite cost estimate using our adjusted wage estimates. The composite estimate of $86.21/hr was calculated by weighting each hourly wage based on the following breakdown regarding provider types most likely to collect this data: OT 45 percent at $86.04/hr; PT 45 percent at $89.34/hr; RN 5 percent at $79.56/hr; LVN 2.5 percent at $49.86/hr; and SLP 2.5 percent at $82.52/hr.

For the purpose of deriving the composite wage we also estimated 2,406,401 admission assessments from 15,471 SNFs annually.

For removing the Application of Functional Assessment/Care Plan measure, we estimate an annual decrease of minus 12,032 hours (0.005 hr × 2,406,401 admission assessments) and minus $1,037,261 (12,032 hours × $86.2085/hr) for all SNFs.

As stated in section VII.C.1.d. of this final rule, we proposed to remove the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) measure as well as the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measure beginning with the FY 2025 SNF QRP. While these assessment-based quality measures were proposed for removal, the data elements used to calculate the measures will still be reported by SNFs for other payment and quality reporting purposes. Therefore, we believe that the removal of the Change in Self-Care Score and Change in Mobility Score measures will not have any impact on our currently approved reporting burden for SNFs.

As stated in section VII.C.2.b. of this final rule, we proposed to adopt the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date (Patient/Resident COVID–19 Vaccine) measure beginning with the FY 2026 SNF QRP. This assessment-based quality measure will be collected using the MDS. One data element will be added to the MDS at discharge to allow for the collection of the Patient/Resident COVID–19 Vaccine measure. We believe this will result in an increase of 18 seconds (0.3 minutes or 0.005 hrs) of clinical staff time at discharge beginning with the FY 2026 SNF QRP. We believe that the added data element for the Patient/Resident COVID–19 Vaccine measure will be completed equally by an RN (0.0025 hr = 0.005 hr/2) and LVN (0.0025 hr = 0.005/2), however, individual SNFs determine the staffing resources necessary. Therefore, we averaged BLS' National Occupational Employment and Wage Estimates (see Table 26) for these labor types and established a composite cost estimate using our adjusted wage estimates. The composite estimate of $64.71/hr (see Table 26) was calculated by weighting each hourly wage based on the following breakdown regarding provider types most likely to collect this data: RN 0.0025 hr at $79.56/hr and LVN 0.0025 hr at $49.86/hr.

For purposes of deriving the burden impact, we estimated a total of 2,406,401 discharges from 15,471 SNFs annually.

We estimate the total burden for complying with the SNF QRP requirements will increase by 12,032 hours (0.005 hr × 2,406,401 discharge assessments) and $778,591 (12,032 hrs × $64.71/hr) for all SNFs annually based on the adoption of the Patient/Resident COVID–19 Vaccine measure.

In summary, we estimate the updated SNF QRP changes associated with the removal of the Application of Functional Assessment/Care Plan measure and the adoption of Patient/Resident COVID–19 measure will have a net zero effect on the total time to complete an MDS but will result in a decrease of $258,670 for all SNFs annually (see Table 27).

As stated in section VII.F.5. of this final rule, we proposed to increase the SNF QRP data completion thresholds for MDS data items beginning with the FY 2026 SNF QRP. SNFs will be required to report 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments they submit through the CMS designated submission system. SNFs have been required to submit MDS quality measures data and standardized patient assessment data for the SNF QRP since October 1, 2016. Since our data indicates that the majority of SNFs are already in compliance with, or exceeding this threshold, we are not making any changes to the burden that is currently approved by OMB under control number 0938–1140 (CMS–10387).

2. ICRs Regarding the Skilled Nursing Facility Value-Based Purchasing Program

In section VIII.B.3. of this final rule, we are replacing the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP program year. The measure is calculated using Medicare FFS claims data, which are the same data we use to calculate the SNFRM, and therefore, this measure will not create any new or revised burden for SNFs.

We are also adopting four new quality measures in the SNF VBP Program as discussed in section VIII.B.4. of this final rule. One of the measures is the Total Nursing Staff Turnover Measure beginning with the FY 2026 SNF VBP program year. This measure is calculated using PBJ data that nursing facilities with SNF beds currently report to us as part of the Five Star Quality Rating System, and therefore, this measure will not create new or revised burden for SNFs. We are also adopting three additional quality measures beginning with the FY 2027 SNF VBP program year: (1) Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) Measure (“Falls with Major Injury (Long-Stay) measure”), (2) Skilled Nursing Facility Cross-Setting Discharge Function Score Measure (“DC Function measure”), and (3) Number of Hospitalizations per 1,000 Long-Stay Resident Days Measure (“Long-Stay Hospitalization measure”). The Falls with Major Injury (Long-Stay) measure and the DC Function measure are calculated using MDS 3.0 data and are calculated by us under the Nursing Home Quality Initiative and SNF QRP Program, respectively. The Long-Stay Hospitalization measure is calculated using Medicare FFS claims data. Therefore, these three measures will not create new or revised burden for SNFs.

Furthermore, in section VIII.G. of this final rule, we are updating the validation process for the SNF VBP Program, including adopting a new process for the Minimum Data Set (MDS) measures beginning with the FY 2027 SNF VBP program year. As finalized, we will validate data used to calculate the measures used in the SNF VBP Program, and 1,500 randomly selected SNFs a year would be required to submit up to 10 charts that would be used to validate the MDS measures.

Finally, in section VIII.E.4. of this final rule, we are adopting a Health Equity Adjustment beginning with the FY 2027 SNF VBP program year. The source of data we would use to calculate this adjustment is the State Medicare Modernization Act (MMA) file of dual eligibility, and therefore our calculation of this adjustment would not create any additional reporting burden for SNFs.

The aforementioned FFS-related claims submission requirements and burden, which are previously mentioned in the preceding paragraphs, are active and approved by OMB under control number 0938–1140 (CMS–10387). The aforementioned MDS submission requirements and burden are active and approved by OMB under control number 0938–1140 and the burden associated with the items used to calculate the measures is already accounted for in the currently approved information collection since it is used for the SNF QRP. The aforementioned PBJ submission requirements and burden are PRA exempt (as are all nursing home requirements for participation). The increase in burden for the SNFs would be accounted for in the submission of up to 10 charts for review, and the proposed process would not begin until FY 2025. The required 60-day and 30-day notices would be published in the Federal Register and the comment periods would be separate from those associated with this rulemaking. This rule's changes will have no impact on any of the requirements and burden that are currently approved under these control numbers.

3. ICRs Regarding Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

This rule finalizes our proposal to eliminate the requirement for facilities facing a civil money penalty to actively waive their right to a hearing in writing to receive a penalty reduction. We are creating, in its place, a constructive waiver process that will operate by default when CMS has not received a timely request for a hearing. While OBRA '87 exempts the waiver requirements and burden from the PRA, the requirements and burden are scored under the RIA section of this preamble.”

C. Summary of Finalized Requirements and Associated Burden Estimates

XII. Economic Analyses

A. Regulatory Impact Analysis

1. Statement of Need

a. Statutory Provisions

This rule updates the FY 2024 SNF prospective payment rates as required under section 1888(e)(4)(E) of the Act. It also responds to section 1888(e)(4)(H) of the Act, which requires the Secretary to provide for publication in the Federal Register before the August 1 that precedes the start of each FY, the unadjusted Federal per diem rates, the case-mix classification system, and the factors to be applied in making the area wage adjustment. These are statutory provisions that prescribe a detailed methodology for calculating and disseminating payment rates under the SNF PPS, and we do not have the discretion to adopt an alternative approach on these issues.

With respect to the SNF QRP, this final rule finalizes updates beginning with the FY 2025 and FY 2026 SNF QRP. Specifically, we adopt a modification to a current measure in the SNF QRP beginning with the FY 2025 SNF QRP, which we believe will encourage healthcare personnel to remain up to date with the COVID–19 vaccine, resulting in fewer cases, less hospitalizations, and lower mortality associated with the virus. We adopt two new measures: (1) one to satisfy the requirement set forth in sections 1888(e)(6)(B)(i)(II) and 1899B(c)(1)(A) of the Act which would replace the current cross-setting process measure with one more strongly associated with desired patient functional outcomes beginning with the FY 2025 SNF QRP; and (2) one that supports the goals of CMS Meaningful Measures Initiative 2.0 to empower consumers, as well as assist SNFs leverage their care processes to increase vaccination coverage in their settings to protect residents and prevent negative outcomes beginning with the FY 2026 SNF QRP. We finalize the removal of three measures from the SNF QRP, beginning with the FY 2025 SNF QRP, as they meet the criteria specified at § 413.360(b)(2) for measure removal. We further finalize an increase to the data completion threshold for Minimum Data Set (MDS) data items, beginning with the FY 2026 SNF QRP, which we believe will improve our ability to appropriately analyze quality measure data for the purposes of monitoring SNF outcomes. For consistency in our regulations, we also finalize conforming revisions to the requirements related to these proposals under the SNF QRP at § 413.360.

With respect to the SNF VBP Program, this final rule updates the SNF VBP Program requirements for FY 2024 and subsequent years. Section 1888(h)(2)(A)(ii) of the Act (as amended by section 111(a)(2)(C) of the CAA 2021) allows the Secretary to add up to nine new measures to the SNF VBP Program. We are finalizing four new measures for the SNF VBP Program. We are finalizing one new measure beginning with the FY 2026 SNF VBP program year and three new measures beginning with the FY 2027 program year. We are also replacing the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP Program year. Additionally, to better address health disparities and achieve health equity, we are finalizing a Health Equity Adjustment (HEA) beginning with the FY 2027 program year. As part of the HEA, we are finalizing a variable payback percentage (for additional information on the HEA and the fluctuating payback percentage see section VII.E.4. of the proposed rule). Section 1888(h)(3) of the Act requires the Secretary to establish and announce performance standards for SNF VBP Program measures no later than 60 days before the performance period, and this final rule includes numerical values of the performance standards for the SNFRM, the SNF Healthcare-Associated Infection Requiring Hospitalization (SNF HAI), Total Nurse Staffing, Nursing Staff Turnover, and the Discharge to Community—Post-Acute Care (DTC PAC SNF) measures. Section 1888(h)(12)(A) of the Act requires the Secretary to apply a validation process to SNF VBP Program measures and “the data submitted under [section 1888(e)(6)] [. . .] as appropriate[. . .].” We are finalizing a new validation process for measures beginning in the FY 2027 program year.

b. Discretionary Provisions

In addition, this final rule includes the following discretionary provisions:

(1) PDPM Parity Adjustment Recalibration

In the FY 2023 SNF final rule (87 FR 47502), we finalized a recalibration of the PDPM parity adjustment with a 2-year phase-in period, resulting in a reduction of 2.3 percent, or $780 million, in FY 2023 and a planned reduction in FY 2024 of 2.3 percent. We finalized the phased-in approach to implementing this adjustment based on a significant number of comments supporting this approach. Accordingly, we are implementing the second phase of the 2-year phase-in period, resulting in a reduction of 2.3 percent, or approximately $789 million, in FY 2024.

(2) SNF Forecast Error Adjustment

Each year, we evaluate the SNF market basket forecast error for the most recent year for which historical data is available. The forecast error is determined by comparing the projected SNF market basket increase in a given year with the actual SNF market basket increase in that year. In evaluating the data for FY 2022, we found that the forecast error for FY 2022 was 3.6 percentage points, exceeding the 0.5 percentage point threshold we established in regulation for proposing adjustments to correct for forecast error. Given that the forecast error exceeds the 0.5 percentage point threshold, current regulations require that the SNF market basket percentage increase for FY 2024 be adjusted upward by 3.6 percentage points to account for forecasting error in the FY 2022 SNF market basket update.

(3) Technical Updates to ICD–10 Mappings

In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the implementation of the PDPM, effective October 1, 2019. The PDPM utilizes ICD–10 codes in several ways, including using the patient's primary diagnosis to assign patients to clinical categories under several PDPM components, specifically the PT, OT, SLP and NTA components. In this rule, we finalize several substantive changes to the PDPM ICD–10 code mapping.

(4) Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

We are finalizing our proposal to eliminate the requirement for facilities to actively waive their right to a hearing in writing and create in its place a constructive waiver process that would operate automatically when CMS has not received a timely request for a hearing. At this time, the accompanying 35 percent penalty reduction will remain, but we will review the appropriateness of this reduction and, if warranted by the review, adjust it in a future rulemaking. The accompanying 35 percent penalty reduction will remain. This revision eliminating the LTC requirement to submit a written request for a reduced penalty amount when a hearing has been waived will simplify and streamline the current requirement, while maintaining a focus on providing high quality care to residents. This provision will also ease the administrative burden for facilities that are currently submitting waiver requests to CMS locations. In CY 2022, 81 percent of facilities facing CMPs filed an appeal waiver while only 2 percent of facilities filed an appeal of their CMP with the Departmental Appeals Board. The remaining 17 percent of facilities neither waived nor timely filed an appeal. We estimate that moving to a constructive waiver process will eliminate the time and paperwork necessary to complete and send in a written waiver and will thereby result, as detailed below, in a total annual savings of $2,299,716 in administrative costs for LTC facilities facing CMPs ($861,678 + $1,438,038 = $2,299,716). Ultimately, this provision will reduce administrative burden for facilities and for CMS.

2. Introduction

We have examined the impacts of this final rule as required by Executive Order 12866 on Regulatory Planning and Review (September 30, 1993), Executive Order 13563 on Improving Regulation and Regulatory Review (January 18, 2011), Executive Order 14094 entitled “Modernizing Regulatory Review” (April 6, 2023), the Regulatory Flexibility Act (RFA, September 19, 1980, Pub. L. 96–354), section 1102(b) of the Act, section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA, March 22, 1995; Pub. L. 104–4), Executive Order 13132 on Federalism (August 4, 1999) and the Congressional Review Act (5 U.S.C. 804(2)).

Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). The Executive Order 14094 entitled “Modernizing Regulatory Review” (hereinafter, the Modernizing E.O.) amends section 3(f)(1) of Executive Order 12866 (Regulatory Planning and Review). The amended section 3(f) of Executive Order 12866 defines a “significant regulatory action” as an action that is likely to result in a rule: (1) having an annual effect on the economy of $200 million or more in any 1 year (adjusted every 3 years by the Administrator of OIRA for changes in gross domestic product), or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, territorial, or tribal governments or communities; (2) creating a serious inconsistency or otherwise interfering with an action taken or planned by another agency; (3) materially altering the budgetary impacts of entitlement grants, user fees, or loan programs or the rights and obligations of recipients thereof; or (4) raise legal or policy issues for which centralized review would meaningfully further the President's priorities or the principles set forth in this Executive order, as specifically authorized in a timely manner by the Administrator of OIRA in each case.

A regulatory impact analysis (RIA) must be prepared for major rules with significant regulatory action/s and/or with significant effects as per section 3(f)(1) ($200 million or more in any 1 year). Based on our estimates, OMB's Office of Information and Regulatory Affairs has determined this rulemaking is significant per section 3(f)(1) as measured by the $200 million or more in any 1 year, and hence also a major rule under Subtitle E of the Small Business Regulatory Enforcement Fairness Act of 1996 (also known as the Congressional Review Act). Accordingly, we have prepared a Regulatory Impact Analysis that to the best of our ability presents the costs and benefits of the rulemaking. Therefore, OMB has reviewed these proposed regulations, and the Departments have provided the following assessment of their impact.

3. Overall Impacts

This rule updates the SNF PPS rates contained in the SNF PPS final rule for FY 2023 (87 FR 47502). We estimate that the aggregate impact will be an increase of approximately $1.4 billion (4.0 percent) in Part A payments to SNFs in FY 2024. This reflects a $2.2 billion (6.4 percent) increase from the update to the payment rates and a $789 million (2.3 percent) decrease as a result of the second phase of the parity adjustment recalibration. We note in this final rule that these impact numbers do not incorporate the SNF VBP Program reductions that we estimate would total $184.85 million in FY 2024. We note that events may occur to limit the scope or accuracy of our impact analysis, as this analysis is future-oriented, and thus, very susceptible to forecasting errors due to events that may occur within the assessed impact time period.

In accordance with sections 1888(e)(4)(E) and (e)(5) of the Act and implementing regulations at § 413.337(d), we are updating the FY 2023 payment rates by a factor equal to the market basket percentage increase adjusted for the forecast error adjustment and reduced by the productivity adjustment to determine the payment rates for FY 2024. The impact to Medicare is included in the total column of Table 30. The annual update in this rule applies to SNF PPS payments in FY 2024. Accordingly, the analysis of the impact of the annual update that follows only describes the impact of this single year. Furthermore, in accordance with the requirements of the Act, we will publish a rule or notice for each subsequent FY that will provide for an update to the payment rates and include an associated impact analysis.

4. Detailed Economic Analysis

The FY 2024 SNF PPS payment impacts appear in Table 30. Using the most recently available data, in this case FY 2022 we apply the current FY 2023 CMIs, wage index and labor-related share value to the number of payment days to simulate FY 2023 payments. Then, using the same FY 2022 data, we apply the FY 2024 CMIs, wage index and labor-related share value to simulate FY 2024 payments. We tabulate the resulting payments according to the classifications in Table 30 (for example, facility type, geographic region, facility ownership), and compare the simulated FY 2023 payments to the simulated FY 2024 payments to determine the overall impact. The breakdown of the various categories of data in Table 30 is as follows:

• The first column shows the breakdown of all SNFs by urban or rural status, hospital-based or freestanding status, census region, and ownership.
• The first row of figures describes the estimated effects of the various changes contained in this final rule on all facilities. The next six rows show the effects on facilities split by hospital-based, freestanding, urban, and rural categories. The next nineteen rows show the effects on facilities by urban versus rural status by census region. The last three rows show the effects on facilities by ownership (that is, government, profit, and non-profit status).
• The second column shows the number of facilities in the impact database.
• The third column shows the effect of the second phase of the parity adjustment recalibration discussed in section IV.C. of this rule.
• The fourth column shows the effect of the annual update to the wage index. This represents the effect of using the most recent wage data available as well as accounts for the 5 percent cap on wage index transitions. The total impact of this change is 0.0 percent; however, there are distributional effects of the change.
• The fifth column shows the effect of all of the changes on the FY 2024 payments. The update of 6.4 percent is constant for all providers and, though not shown individually, is included in the total column. It is projected that aggregate payments would increase by 6.4 percent, assuming facilities do not change their care delivery and billing practices in response.

As illustrated in Table 30, the combined effects of all of the changes vary by specific types of providers and by location. For example, due to changes in this final rule, rural providers would experience a 3.0 percent increase in FY 2024 total payments.

In this chart and throughout the rule, we use a multiplicative formula to derive total percentage change. This formula is:

(1 + Parity Adjustment Percentage) * (1 + Wage Index Update Percentage) * (1 + Payment Rate Update Percentage) − 1 = Total Percentage Change

For example, the figures shown in Column 5 of Table 30 are calculated by multiplying the percentage changes using this formula. Thus, the Total Change figure for the Total Group Category is 4.0 percent, which is (1 − 2.3%) * (1 + 0.0%) * (1 + 6.4%) −1.

As a result of rounding and the use of this multiplicative formula based on percentages, derived dollar estimates may not sum.

5. Impacts for the Skilled Nursing Facility Quality Reporting Program (SNF QRP) for FY 2025 Through FY 2026

Estimated impacts for the SNF QRP are based on analysis discussed in section VII.C. of this final rule. In accordance with section 1888(e)(6)(A)(i) of the Act, the Secretary must reduce by 2 percentage points the annual payment update applicable to a SNF for a fiscal year if the SNF does not comply with the requirements of the SNF QRP for that fiscal year.

As discussed in section VII.C.1.a. of this final rule, we proposed to modify one measure in the SNF QRP beginning with the FY 2025 SNF QRP, the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP COVID–19 Vaccine) measure. We believe that the burden associated with the SNF QRP is the time and effort associated with complying with the non-claims-based measures requirements of the SNF QRP. The burden associated with the HCP COVID–19 Vaccine measure is accounted for under the CDC PRA package currently approved under OMB control number 0938–1317 (expiration January 31, 2024).

As discussed in section VII.C.1.b. of this final rule, we proposed that SNFs would collect data on one new quality measure, the Discharge Function Score (DC Function) measure, beginning with resident assessments completed on October 1, 2023. However, the DC Function measure utilizes data items that SNFs already report to CMS for payment and quality reporting purposes, and therefore, the burden is accounted for in the PRA package approved under OMB control number 0938–1140 (expiration November 30, 2025).

As discussed in section VII.C.1.c. of this final rule, we proposed to remove a measure from the SNF QRP, the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) measure, beginning with admission assessments completed on October 1, 2023. Although the proposed decrease in burden will be accounted for in a revised information collection request under OMB control number (0938–1140), we are providing impact information.

With 2,406,401 admissions from 15,471 SNFs annually, we estimated an annual burden decrease of 12,032 fewer hours (2,406,401 admissions × 0.005 hr) and a decrease of $1,037,261 (12,038 hrs × $86.2085/hr). For each SNF we estimate an annual burden decrease of 0.78 hours [(12,032 hrs/15,471 SNFs) at a savings of $67.05 ($1,037,261 total burden/15,471 SNFs).

As discussed in section VII.C.1.d. of this final rule, we proposed to remove two measures from the SNF QRP, the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) and Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measures, beginning with assessments completed on October 1, 2023. However, the data items used in the calculation of the Change in Self-Care Score and Change in Mobility Score measures are used for other payment and quality reporting purposes, and therefore there is no change in burden associated with this proposal.

As discussed in section VII.C.3.a. of this final rule, we proposed to add a second measure to the SNF QRP, the COVID–19 Vaccine: Percent of Patients/Residents Who are Up to Date (Patient/Resident COVID–19 Vaccine) measure, which would result in an increase of 0.005 hours of clinical staff time beginning with discharge assessments completed on October 1, 2024. Although the increase in burden will be accounted for in a revised information collection request under OMB control number (0938–1140), we provided impact information. With 2,406,401 discharges from 15,471 SNFs annually, we estimate an annual burden increase of 12,032 hours (2,406,401 discharges × 0.005 hr) and an increase of $778,5914 (12,032 hrs × $64.71/hr). For each SNF we estimate an annual burden increase of 0.78 hours (12,032 hrs/15,471 SNFs) at an additional cost of $50.33 ($778,591 total burden/15,471 SNFs).

We also proposed in section VII.F.5. of this final rule that SNFs would begin reporting 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments they submit through the CMS designated submission system beginning January 1, 2024. As discussed in section IX.B.1. of this final rule, this change will not affect the information collection burden for the SNF QRP.

We solicited public comments on the overall impact of the SNF QRP proposals for FY 2025 and 2026.

We did not receive public comments on this provision and therefore, we are finalizing as proposed.

6. Impacts for the SNF VBP Program

The estimated impacts of the FY 2024 SNF VBP Program are based on historical data and appear in Table 32. We modeled SNF performance in the Program using SNFRM data from FY 2019 as the baseline period and FY 2021 as the performance period. Additionally, we modeled a logistic exchange function with a payback percentage of 60 percent, as we finalized in the FY 2018 SNF PPS final rule (82 FR 36619 through 36621).

For the FY 2024 program year, we will award each participating SNF 60 percent of their 2 percent withhold. Additionally, in the FY 2023 SNF PPS final rule (87 FR 47585 through 47587), we finalized our proposal to apply a case minimum requirement for the SNFRM. As a result of these provisions, SNFs that do not meet the case minimum specified for the SNFRM for the FY 2024 program year will be excluded from the Program and will receive their adjusted Federal per diem rate for that fiscal year. As previously finalized, this policy will maintain the overall payback percentage at 60 percent for the FY 2024 program year. Based on the 60 percent payback percentage, we estimated that we would redistribute approximately $277.27 million (of the estimated $462.12 million in withheld funds) in value-based incentive payments to SNFs in FY 2024, which means that the SNF VBP Program is estimated to result in approximately $184.85 million in savings to the Medicare Program in FY 2024.

Our detailed analysis of the impacts of the FY 2024 SNF VBP Program is shown in Table 32.

In section VIII.B.4.b. of this final rule, we are adopting one additional measure (Nursing Staff Turnover measure) beginning with the FY 2026 program year. Additionally, in section VIII.E.2.b. of this final rule, we are adopting a case minimum requirement for the Nursing Staff Turnover measure. In section VIII.E.2.c. of this final rule, we are maintaining the previously finalized measure minimum for FY 2026. Therefore, we provided estimated impacts of the FY 2026 SNF VBP Program, which are based on historical data and appear in Tables 33 and 34. We modeled SNF performance in the Program using measure data from FY 2019 as the baseline period and FY 2021 as the performance period for the SNFRM, SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures. Additionally, we modeled a logistic exchange function with a payback percentage of 60 percent. Based on the 60 percent payback percentage, we estimated that we will redistribute approximately $294.75 million (of the estimated $491.24 million in withheld funds) in value-based incentive payments to SNFs in FY 2026, which means that the SNF VBP Program is estimated to result in approximately $196.50 million in savings to the Medicare Program in FY 2026.

Our detailed analysis of the impacts of the FY 2026 SNF VBP Program is shown in Tables 33 and 34.

In section VIII.B.4. of this final rule, we are adopting three additional measures (Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures) beginning with the FY 2027 program year. Additionally, in section VIII.E.2.b. of this final rule, we are adopting case minimum requirements for the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. In section VIII.E.2.d. of this final rule, we are also finalizing an update to our previously finalized measure minimum for the FY 2027 program year. Therefore, we provided estimated impacts of the FY 2027 SNF VBP Program, which are based on historical data and appear in Tables 35 and 36. We modeled SNF performance in the Program using measure data from FY 2019 (SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and DC Function measures), CY 2019 (Long Stay Hospitalization measure), and FY 2018 through FY 2019 (DTC PAC SNF measure) as the baseline period and FY 2021 (SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and DC Function measures), CY 2021 (Long Stay Hospitalization measure), and FY 2020 through FY 2021 (DTC PAC SNF measure) as the performance period. Additionally, we modeled a logistic exchange function with an approximate payback percentage of 66.02 percent for the Health Equity Adjustment, as we finalized in section VIII.E.4.e. of this final rule. Based on the increase in payback percentage, we estimated that we will redistribute approximately $324.18 million (of the estimated $491.03 million in withheld funds) in value-based incentive payments to SNFs in FY 2027, which means that the SNF VBP Program is estimated to result in approximately $166.86 million in savings to the Medicare Program in FY 2027. Of the $324.18 million, $29.56 million is due to the Health Equity Adjustment, as indicated in Table 23 in section VIII.E.4.e. of this final rule.

Our detailed analysis of the impacts of the FY 2027 SNF VBP Program is shown in Tables 35 and 36.