2022-16225. Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2023 and Updates to the IRF Quality Reporting Program

AGENCY:

Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION:

Final rule.

SUMMARY:

This final rule updates the prospective payment rates for inpatient rehabilitation facilities (IRFs) for Federal fiscal year (FY) 2023. As required by statute, this final rule includes the classification and weighting factors for the IRF prospective payment system's case-mix groups and a description of the methodologies and data used in computing the prospective payment rates for FY 2023. In addition, this final rule codifies CMS' existing teaching status adjustment policy through amendments to the regulation text and updates and clarifies the IRF teaching policy with respect to IRF hospital closures and displaced residents. This rule establishes a permanent cap policy to smooth the impact of year-to-year changes in IRF payments related to decreases in the IRF wage index. This final rule also includes updates for the IRF Quality Reporting Program (QRP).

DATES:

Effective date: These regulations are effective on October 1, 2022.

Applicability dates: The updated IRF prospective payment rates are applicable for IRF discharges occurring on or after October 1, 2022, and on or before September 30, 2023 (FY 2023).

FOR FURTHER INFORMATION CONTACT:

Gwendolyn Johnson, [phone], for general information.

Catie Cooksey, [phone], for information about the IRF payment policies and payment rates.

Kim Schwartz, [phone], and Gwendolyn Johnson, [phone], for information about the IRF coverage policies.

Ariel Cress, [phone], for information about the IRF quality reporting program.

SUPPLEMENTARY INFORMATION:

Availability of Certain Information Through the Internet on the CMS Website

The IRF prospective payment system (IRF PPS) Addenda along with other supporting documents and tables referenced in this final rule are available through the internet on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

We note that prior to 2020, each rule or notice issued under the IRF PPS has included a detailed reiteration of the various regulatory provisions that have affected the IRF PPS over the years. That discussion, along with detailed background information for various other aspects of the IRF PPS, is now available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

I. Executive Summary

A. Purpose

This final rule updates the prospective payment rates for IRFs for FY 2023 (that is, for discharges occurring on or after October 1, 2022, and on or before September 30, 2023) as required under section 1886(j)(3)(C) of the Social Security Act (the Act). As required by section 1886(j)(5) of the Act, this final rule includes the classification and weighting factors for the IRF PPS's case-mix groups (CMGs) and a description of the methodologies and data used in computing the prospective payment rates for FY 2023. This final rule codifies CMS' existing teaching status adjustment policy through amendments to the regulation text and updates and clarifies the IRF teaching policy with respect to IRF hospital closures and displaced residents. We also establish a permanent cap policy to smooth the impact of year-to-year changes in IRF payments related to decreases in the IRF wage index. This rule also requires quality data reporting on all IRF patients beginning with the FY 2026 IRF QRP and amends the regulations consistent with the requirements. This final rule also corrects an error in the regulations text at § 412.614(d)(2).

B. Summary of Major Provisions

In this final rule, we use the methods described in the FY 2022 IRF PPS final rule (86 FR 42362) to update the prospective payment rates for FY 2023 using updated FY 2021 IRF claims and the most recent available IRF cost report data, which is FY 2020 IRF cost report data. This final rule codifies CMS' existing teaching status adjustment policy through amendments to the regulation text and updates and clarifies the IRF teaching status adjustment policy with respect to IRF hospital closures and displaced residents.

We establish a permanent cap policy to smooth the impact of year-to-year changes in IRF payments related to decreases in the IRF wage index. This final rule also requires quality reporting data for all IRF patients beginning with the FY 2026 IRF QRP and revises the regulations accordingly.

C. Summary of Impact

II. Background

A. Statutory Basis and Scope for IRF PPS Provisions

Section 1886(j) of the Act provides for the implementation of a per-discharge PPS for inpatient rehabilitation hospitals and inpatient rehabilitation units of a hospital (collectively, hereinafter referred to as IRFs). Payments under the IRF PPS encompass inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs), but not direct graduate medical education costs, costs of approved nursing and allied health education activities, bad debts, and other services or items outside the scope of the IRF PPS. A complete discussion of the IRF PPS provisions appears in the original FY 2002 IRF PPS final rule (66 FR 41316) and the FY 2006 IRF PPS final rule (70 FR 47880) and we provided a general description of the IRF PPS for FYs 2007 through 2019 in the FY 2020 IRF PPS final rule (84 FR 39055 through 39057). A general description of the IRF PPS for FYs 2020 through 2022, along with detailed background information for various other aspects of the IRF PPS, is now available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

Under the IRF PPS from FY 2002 through FY 2005, the prospective payment rates were computed across 100 distinct CMGs, as described in the FY 2002 IRF PPS final rule (66 FR 41316). We constructed 95 CMGs using rehabilitation impairment categories (RICs), functional status (both motor and cognitive), and age (in some cases, cognitive status and age may not be a factor in defining a CMG). In addition, we constructed five special CMGs to account for very short stays and for patients who expire in the IRF.

For each of the CMGs, we developed relative weighting factors to account for a patient's clinical characteristics and expected resource needs. Thus, the weighting factors accounted for the relative difference in resource use across all CMGs. Within each CMG, we created tiers based on the estimated effects that certain comorbidities would have on resource use.

We established the Federal PPS rates using a standardized payment conversion factor (formerly referred to as the budget-neutral conversion factor). For a detailed discussion of the budget-neutral conversion factor, please refer to our FY 2004 IRF PPS final rule (68 FR 45684 through 45685). In the FY 2006 IRF PPS final rule (70 FR 47880), we discussed in detail the methodology for determining the standard payment conversion factor.

We applied the relative weighting factors to the standard payment conversion factor to compute the unadjusted prospective payment rates under the IRF PPS from FYs 2002 through 2005. Within the structure of the payment system, we then made adjustments to account for interrupted stays, transfers, short stays, and deaths. Finally, we applied the applicable adjustments to account for geographic variations in wages (wage index), the percentage of low-income patients, location in a rural area (if applicable), and outlier payments (if applicable) to the IRFs' unadjusted prospective payment rates.

For cost reporting periods that began on or after January 1, 2002, and before October 1, 2002, we determined the final prospective payment amounts using the transition methodology prescribed in section 1886(j)(1) of the Act. Under this provision, IRFs transitioning into the PPS were paid a blend of the Federal IRF PPS rate and the payment that the IRFs would have received had the IRF PPS not been implemented. This provision also allowed IRFs to elect to bypass this blended payment and immediately be paid 100 percent of the Federal IRF PPS rate. The transition methodology expired as of cost reporting periods beginning on or after October 1, 2002 (FY 2003), and payments for all IRFs now consist of 100 percent of the Federal IRF PPS rate.

Section 1886(j) of the Act confers broad statutory authority upon the Secretary to propose refinements to the IRF PPS. In the FY 2006 IRF PPS final rule (70 FR 47880) and in correcting amendments to the FY 2006 IRF PPS final rule (70 FR 57166), we finalized a number of refinements to the IRF PPS case-mix classification system (the CMGs and the corresponding relative weights) and the case-level and facility-level adjustments. These refinements included the adoption of the Office of Management and Budget's (OMB's) Core-Based Statistical Area (CBSA) market definitions; modifications to the CMGs, tier comorbidities; and CMG relative weights, implementation of a new teaching status adjustment for IRFs; rebasing and revising the market basket index used to update IRF payments, and updates to the rural, low-income percentage (LIP), and high-cost outlier adjustments. Beginning with the FY 2006 IRF PPS final rule (70 FR 47908 through 47917), the market basket index used to update IRF payments was a market basket reflecting the operating and capital cost structures for freestanding IRFs, freestanding inpatient psychiatric facilities (IPFs), and long-term care hospitals (LTCHs) (hereinafter referred to as the rehabilitation, psychiatric, and long-term care (RPL) market basket). Any reference to the FY 2006 IRF PPS final rule in this final rule also includes the provisions effective in the correcting amendments. For a detailed discussion of the final key policy changes for FY 2006, please refer to the FY 2006 IRF PPS final rule.

The regulatory history previously included in each rule or notice issued under the IRF PPS, including a general description of the IRF PPS for FYs 2007 through 2020, is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

In late 2019,^[1] the United States began responding to an outbreak of a virus named “SARS-CoV-2” and the disease it causes, which is named “coronavirus disease 2019” (abbreviated “COVID-19”). Due to our prioritizing efforts in support of containing and combatting the PHE for COVID-19, and devoting significant resources to that end, we published two interim final rules with comment period affecting IRF payment and conditions for participation. The interim final rule with comment period (IFC) entitled, “Medicare and Medicaid Programs; Policy and Regulatory Revisions in Response to the COVID-19 Public Health Emergency”, published on April 6, 2020 (85 FR 19230) (hereinafter referred to as the April 6, 2020 IFC), included certain changes to the IRF PPS medical supervision requirements at 42 CFR 412.622(a)(3)(iv) and 412.29(e) during the PHE for COVID-19. In addition, in the April 6, 2020 IFC, we removed the post-admission physician evaluation requirement at § 412.622(a)(4)(ii) for all IRFs during the PHE for COVID-19. In the FY 2021 IRF PPS final rule, to ease documentation and administrative burden, we also removed the post-admission physician evaluation documentation requirement at 42 CFR 412.622(a)(4)(ii) permanently beginning in FY 2021.

A second IFC entitled, “Medicare and Medicaid Programs, Basic Health Program, and Exchanges; Additional Policy and Regulatory Revisions in Response to the COVID-19 Public Health Emergency and Delay of Certain Reporting Requirements for the Skilled Nursing Facility Quality Reporting Program” was published on May 8, 2020 (85 FR 27550) (hereinafter referred to as the May 8, 2020 IFC). Among other changes, the May 8, 2020 IFC included a waiver of the “3-hour rule” at § 412.622(a)(3)(ii) to reflect the waiver required by section 3711(a) of the Coronavirus Aid, Relief, and Economic Security Act (CARES Act) (Pub. L. 116-136, enacted on March 27, 2020). In the May 8, 2020 IFC, we also modified certain IRF coverage and classification requirements for freestanding IRF hospitals to relieve acute care hospital capacity concerns in States (or regions, as applicable) experiencing a surge during the PHE for COVID-19. In addition to the policies adopted in our IFCs, we responded to the PHE with numerous blanket waivers ^[2] and other flexibilities,^[3] some of which are applicable to the IRF PPS.

B. Provisions of the PPACA and the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) Affecting the IRF PPS in FY 2012 and Beyond

The Patient Protection and Affordable Care Act (PPACA) (Pub. L. 111-148) was enacted on March 23, 2010. The Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152), which amended and revised several provisions of the PPACA, was enacted on March 30, 2010. In this final rule, we refer to the two statutes collectively as the “Patient Protection and Affordable Care Act” or “PPACA”.

The PPACA included several provisions that affect the IRF PPS in FYs 2012 and beyond. In addition to what was previously discussed, section 3401(d) of the PPACA also added section 1886(j)(3)(C)(ii)(I) of the Act (providing for a “productivity adjustment” for FY 2012 and each subsequent FY). The productivity adjustment for FY 2023 is discussed in section VI.B. of this final rule. Section 1886(j)(3)(C)(ii)(II) of the Act provides that the application of the productivity adjustment to the market basket update may result in an update that is less than 0.0 for a FY and in payment rates for a FY being less than such payment rates for the preceding FY.

Sections 3004(b) of the PPACA and section 411(b) of the MACRA (Pub. L. 114-10, enacted on April 16, 2015) also addressed the IRF PPS. Section 3004(b) of PPACA reassigned the previously designated section 1886(j)(7) of the Act to section 1886(j)(8) of the Act and inserted a new section 1886(j)(7) of the Act, which contains requirements for the Secretary to establish a QRP for IRFs. Under that program, data must be submitted in a form and manner and at a time specified by the Secretary. Beginning in FY 2014, section 1886(j)(7)(A)(i) of the Act requires the application of a 2-percentage point reduction to the market basket increase factor otherwise applicable to an IRF (after application of paragraphs (C)(iii) and (D) of section 1886(j)(3) of the Act) for a FY if the IRF does not comply with the requirements of the IRF QRP for that FY. Application of the 2-percentage point reduction may result in an update that is less than 0.0 for a FY and in payment rates for a FY being less than such payment rates for the preceding FY. Reporting-based reductions to the market basket increase factor are not cumulative; they only apply for the FY involved. Section 411(b) of the MACRA amended section 1886(j)(3)(C) of the Act by adding paragraph (iii), which required us to apply for FY 2018, after the application of section 1886(j)(3)(C)(ii) of the Act, an increase factor of 1.0 percent to update the IRF prospective payment rates.

C. Operational Overview of the Current IRF PPS

As described in the FY 2002 IRF PPS final rule (66 FR 41316), upon the admission and discharge of a Medicare Part A fee-for-service (FFS) patient, the IRF is required to complete the appropriate sections of a Patient Assessment Instrument (PAI), designated as the IRF-PAI. In addition, beginning with IRF discharges occurring on or after October 1, 2009, the IRF is also required to complete the appropriate sections of the IRF-PAI upon the admission and discharge of each Medicare Advantage (MA) patient, as described in the FY 2010 IRF PPS final rule (74 FR 39762 and 74 FR 50712). All required data must be electronically encoded into the IRF-PAI software product. Generally, the software product includes patient classification programming called the Grouper software. The Grouper software uses specific IRF-PAI data elements to classify (or group) patients into distinct CMGs and account for the existence of any relevant comorbidities.

The Grouper software produces a five-character CMG number. The first character is an alphabetic character that indicates the comorbidity tier. The last four characters are numeric characters that represent the distinct CMG number. A free download of the Grouper software is available on the CMS website at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​Software.html. The Grouper software is also embedded in the internet Quality Improvement and Evaluation System (iQIES) User tool available in iQIES at https://www.cms.gov/​medicare/​quality-safety-oversight-general-information/​iqies.

Once a Medicare Part A FFS patient is discharged, the IRF submits a Medicare claim as a Health Insurance Portability and Accountability Act of 1996 (HIPAA) (Pub. L. 104-191, enacted on August 21, 1996)-compliant electronic claim or, if the Administrative Simplification Compliance Act of 2002 (ASCA) (Pub. L. 107-105, enacted on December 27, 2002) permits, a paper claim (a UB-04 or a CMS-1450 as appropriate) using the five-character CMG number and sends it to the appropriate Medicare Administrative Contractor (MAC). In addition, once a MA patient is discharged, in accordance with the Medicare Claims Processing Manual, chapter 3, section 20.3 (Pub. 100-04), hospitals (including IRFs) must submit an informational-only bill (type of bill (TOB) 111), which includes Condition Code 04 to their MAC. This will ensure that the MA days are included in the hospital's Supplemental Security Income (SSI) ratio (used in calculating the IRF LIP adjustment) for FY 2007 and beyond. Claims submitted to Medicare must comply with both ASCA and HIPAA.

Section 3 of the ASCA amended section 1862(a) of the Act by adding paragraph (22), which requires the Medicare program, subject to section 1862(h) of the Act, to deny payment under Part A or Part B for any expenses for items or services for which a claim is submitted other than in an electronic form specified by the Secretary. Section 1862(h) of the Act, in turn, provides that the Secretary shall waive such denial in situations in which there is no method available for the submission of claims in an electronic form or the entity submitting the claim is a small provider. In addition, the Secretary also has the authority to waive such denial in such unusual cases as the Secretary finds appropriate. For more information, see the “Medicare Program; Electronic Submission of Medicare Claims” final rule (70 FR 71008). Our instructions for the limited number of Medicare claims submitted on paper are available at http://www.cms.gov/​manuals/​downloads/​clm104c25.pdf.

Section 3 of the ASCA operates in the context of the administrative simplification provisions of HIPAA, which include, among others, the requirements for transaction standards and code sets codified in 45 CFR part 160 and part 162, subparts A and I through R (generally known as the Transactions Rule). The Transactions Rule requires covered entities, including covered healthcare providers, to conduct covered electronic transactions according to the applicable transaction standards. (See the CMS program claim memoranda at http://www.cms.gov/​ElectronicBillingEDITrans/​ and listed in the addenda to the Medicare Intermediary Manual, Part 3, section 3600).

The MAC processes the claim through its software system. This software system includes pricing programming called the “Pricer” software. The Pricer software uses the CMG number, along with other specific claim data elements and provider-specific data, to adjust the IRF's prospective payment for interrupted stays, transfers, short stays, and deaths, and then applies the applicable adjustments to account for the IRF's wage index, percentage of low-income patients, rural location, and outlier payments. For discharges occurring on or after October 1, 2005, the IRF PPS payment also reflects the teaching status adjustment that became effective as of FY 2006, as discussed in the FY 2006 IRF PPS final rule (70 FR 47880).

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 electronic 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 from the industry to develop Fast Healthcare Interoperability Resources® (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.^[4 5] 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.^[6] We encourage PAC provider and health information technology (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).^[7] The DEL furthers CMS' goal of data standardization and interoperability. These interoperable data elements can reduce provider burden by allowing the use and exchange of healthcare data; supporting provider exchange of electronic health information for care coordination, person-centered care; and supporting real-time, data driven, clinical decision-making.^[8 9] Standards in the DEL can be referenced on the CMS website ( https://del.cms.gov/​DELWeb/​pubHome) and in the ONC Interoperability Standards Advisory (ISA). The 2022 ISA is available at https://www.healthit.gov/​isa/​sites/​isa/​files/​inline-files/​2022-ISA-Reference-Edition.pdf.

The 21st Century Cures Act (Cures Act), (Pub L. 114-255, enacted December 13, 2016) requires HHS to take new steps to enable the electronic sharing of health information and to further interoperability for providers and settings across the care continuum. Section 4003 of the Cures Act required HHS 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 incorporated by reference Qualified Health Information Network Technical Framework Version 1 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 Common Agreement follows a network-of-networks structure, which allows for connection at different levels and is inclusive of many different types of entities, such as health information networks, healthcare practices, hospitals, public health agencies, and Individual Access Services (IAS) Providers.^[10] For more information, we refer readers to https://www.healthit.gov/​topic/​interoperability/​trusted-exchange-framework-and-common-agreement.

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

Comment: We received one comment on the information provided in this section. The commenter expressed support for efforts across HHS to advance health information technology exchange and encouraged use of a standard set of data by providers and health IT vendors, including efforts through the PACIO project. The commenter also noted a recent National Academies report ^[11] describing technology barriers for post-acute care settings due to not being eligible for previous incentives to purchase technology certified under the ONC Health IT Certification Program. The commenter supported recommendations in the report for HHS to pursue financial incentives for post-acute care settings to adopt certified health IT in order to enable health information exchange.

Response: We will take this comment into consideration as we coordinate with Federal partners, including ONC, on interoperability initiatives, and to inform future rulemaking.

III. Summary of Provisions of the Proposed Rule

In the FY 2023 IRF PPS proposed rule (the proposed rule), we proposed to update the IRF PPS for FY 2023 and the IRF QRP for FY 2025.

The proposed policy changes and updates to the IRF prospective payment rates for FY 2023 are as follows:

• Update the CMG relative weights and average length of stay values for FY 2023, in a budget neutral manner, as discussed in section IV. of the FY 2023 IRF PPS proposed rule (87 FR 20222 through 20227).
• Update the IRF PPS payment rates for FY 2023 by the market basket increase factor, based upon the most current data available, with a productivity adjustment required by section 1886(j)(3)(C)(ii)(I) of the Act, as described in section V. of the FY 2023 IRF PPS proposed rule (87 FR 20227 through 20228).
• Describe the establishment of a permanent cap policy in order to smooth the impact of year-to-year changes in IRF payments related to certain changes to the IRF wage index, as discussed in section V. of the FY 2023 IRF PPS proposed rule (87 FR 20230 through 20231).
• Update the FY 2023 IRF PPS payment rates by the FY 2023 wage index and the labor-related share in a budget-neutral manner, as discussed in section V. of the FY 2023 IRF PPS proposed rule (87 FR 20228 through 20229).
• Describe the calculation of the IRF standard payment conversion factor for FY 2023, as discussed in section V. of the FY 2023 IRF PPS proposed rule (87 FR 20232).
• Update the outlier threshold amount for FY 2023, as discussed in section VI. of the FY 2023 IRF PPS proposed rule (87 FR 20235 through 20236).
• Update the cost-to-charge ratio (CCR) ceiling and urban/rural average CCRs for FY 2023, as discussed in section VI. of the FY 2023 IRF PPS proposed rule (87 FR 20236).
• Describe the proposed codification of CMS' existing teaching status adjustment policy and proposed clarifications and updates of the IRF teaching status adjustment policy with respect to IRF hospital closures and displaced residents, as discussed in section VII. of the FY 2023 IRF PPS proposed rule (87 FR 20236 through 20239).
• Solicit comments on the methodology used to update the facility-level adjustment factors, as discussed in section VIII. of the FY 2023 IRF PPS proposed rule.
• Solicit comments on the IRF transfer payment policy, as discussed in section IX. of the FY 2023 IRF PPS proposed rule.

We also proposed updates to the IRF QRP and requested information in section VII. of the proposed rule as follows:

• Update data reporting requirements under the IRF QRP beginning with FY 2025.
• Request information on (1) future measure concepts under consideration for the IRF QRP; (2) inclusion of a future dQM for the IRF QRP; and (3) CMS' overarching principles for measuring healthcare disparities across CMS Quality Programs, including the IRF QRP.

IV. Analysis of and Responses to Public Comments

We received 61 timely responses from the public, many of which contained multiple comments on the FY 2023 IRF PPS proposed rule (87 FR 20218). We received comments from various trade associations, inpatient rehabilitation facilities, individual physicians, therapists, clinicians, health care industry organizations, and health care consulting firms. The following sections, arranged by subject area, include a summary of the public comments that we received, and our responses.

A. Miscellaneous Comments

Comment: We received several additional comments that were outside the scope of the FY 2023 IRF PPS proposed rule. Specifically, we received comments regarding Medicare beneficiaries and vaccine status, the inclusion of recreational therapy, and general patient access issues in post-acute care settings.

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

V. Update to the Case-Mix Group (CMG) Relative Weights and Average Length of Stay (ALOS) Values for FY 2023

As specified in § 412.620(b)(1), we calculate a relative weight for each CMG that is proportional to the resources needed by an average inpatient rehabilitation case in that CMG. For example, cases in a CMG with a relative weight of 2, on average, will cost twice as much as cases in a CMG with a relative weight of 1. Relative weights account for the variance in cost per discharge due to the variance in resource utilization among the payment groups, and their use helps to ensure that IRF PPS payments support beneficiary access to care, as well as provider efficiency.

We proposed to update the CMG relative weights and ALOS values for FY 2023. Typically, we use the most recent available data to update the CMG relative weights and average lengths of stay. For FY 2023, we proposed to use the FY 2021 IRF claims and FY 2020 IRF cost report data. These data are the most current and complete data available at this time. Currently, only a small portion of the FY 2021 IRF cost report data are available for analysis, but the majority of the FY 2021 IRF claims data are available for analysis. We also proposed that if more recent data became available after the publication of the proposed rule and before the publication of the final rule, we would use such data to determine the FY 2023 CMG relative weights and ALOS values in the final rule.

We proposed to apply these data using the same methodologies that we have used to update the CMG relative weights and ALOS values each FY since we implemented an update to the methodology. The detailed CCR data from the cost reports of IRF provider units of primary acute care hospitals is used for this methodology, instead of CCR data from the associated primary care hospitals, to calculate IRFs' average costs per case, as discussed in the FY 2009 IRF PPS final rule (73 FR 46372). In calculating the CMG relative weights, we use a hospital-specific relative value method to estimate operating (routine and ancillary services) and capital costs of IRFs. The process to calculate the CMG relative weights for this final rule is as follows:

Step 1. We estimate the effects that comorbidities have on costs.

Step 2. We adjust the cost of each Medicare discharge (case) to reflect the effects found in the first step.

Step 3. We use the adjusted costs from the second step to calculate CMG relative weights, using the hospital-specific relative value method.

Step 4. We normalize the FY 2023 CMG relative weights to the same average CMG relative weight from the CMG relative weights implemented in the FY 2022 IRF PPS final rule (86 FR 42362).

Consistent with the methodology that we have used to update the IRF classification system in each instance in the past, we proposed to update the CMG relative weights for FY 2023 in such a way that total estimated aggregate payments to IRFs for FY 2023 are the same with or without the changes (that is, in a budget-neutral manner) by applying a budget neutrality factor to the standard payment amount. We note that, as we typically do, we updated our data between the FY 2023 IRF PPS proposed and final rules to ensure that we use the most recent available data in calculating IRF PPS payments. This updated data reflects a more complete set of claims for FY 2021 and additional cost report data for FY 2020. To calculate the appropriate budget neutrality factor for use in updating the FY 2023 CMG relative weights, we use the following steps:

Step 1. Calculate the estimated total amount of IRF PPS payments for FY 2023 (with no changes to the CMG relative weights).

Step 2. Calculate the estimated total amount of IRF PPS payments for FY 2023 by applying the changes to the CMG relative weights (as discussed in this final rule).

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2 to determine the budget neutrality factor of 0.9979 that would maintain the same total estimated aggregate payments in FY 2023 with and without the changes to the CMG relative weights.

Step 4. Apply the budget neutrality factor from step 3 to the FY 2023 IRF PPS standard payment amount after the application of the budget-neutral wage adjustment factor.

In section VI.E. of this final rule, we discuss the use of the existing methodology to calculate the standard payment conversion factor for FY 2023.

In Table 2, “Relative Weights and Average Length of Stay Values for Case-Mix Groups,” we present the CMGs, the comorbidity tiers, the corresponding relative weights, and the ALOS values for each CMG and tier for FY 2023. The ALOS for each CMG is used to determine when an IRF discharge meets the definition of a short-stay transfer, which results in a per diem case level adjustment.

Generally, updates to the CMG relative weights result in some increases and some decreases to the CMG relative weight values. Table 2 shows how we estimate that the application of the revisions for FY 2023 would affect particular CMG relative weight values, which would affect the overall distribution of payments within CMGs and tiers. We note that, because we implement the CMG relative weight revisions in a budget-neutral manner (as previously described), total estimated aggregate payments to IRFs for FY 2023 are not affected as a result of the CMG relative weight revisions. However, the revisions affect the distribution of payments within CMGs and tiers.

As shown in Table 3, 98.9 percent of all IRF cases are in CMGs and tiers that would experience less than a 5 percent change (either increase or decrease) in the CMG relative weight value as a result of the revisions for FY 2023. The changes in the ALOS values for FY 2023, compared with the FY 2022 ALOS values, are small and do not show any particular trends in IRF length of stay patterns.

The comments we received on our proposed updates to the CMG relative weights and ALOS values for FY 2023 and our responses are summarized below.

Comment: Some commenters were supportive of our proposed updates to the CMG relative weights and average length of stay values using the most recent data available. A few commenters expressed concern regarding reductions in the relative weight values associated with stroke and traumatic spinal cord injury and suggested that this would inappropriately reduce payments. One commenter requested that CMS not reduce any CMG relative weight values or LOS values until after the COVID-19 PHE has ended and urged CMS to ensure that adequate payment is provided for all cases.

Response: We appreciate these commenters' support for the proposed updates. The CMG relative weights are updated each year in a budget neutral manner, thus leading to increases in some CMG relative weights and corresponding decreases in other CMG relative weights. We note that, as we typically do, we have updated our data between the FY 2023 IRF PPS proposed and this final rule to ensure that we use the most recent available data in calculating IRF PPS payments. We have reviewed the increases and decreases in the CMG relative weights for this final rule and we believe that these changes accurately reflect our best estimates of the relative costs of caring for different types of patients in the IRF setting for FY 2023 and that it would not be appropriate to prevent decreases in these values until after the PHE has ended. The relative weights associated with these CMGs include both increases and decreases, and the variation for FY 2023 is similar to the typical year-to-year variation that we observe. The relative weight values are updated each year to ensure that the IRF case mix system is as reflective as possible of the current IRF population, thereby ensuring that IRF payments appropriately reflect the relative costs of caring for all types of IRF patients.

Comment: A commenter expressed concern that the CMG relative weights do not address patient severity and are not aligned with recent trends in coding practices. This commenter also recommended that CMS revise the CMGs and the underlying data collection to account for new populations of cases.

Response: We believe that these data accurately reflect the severity of the IRF patient population and the associated costs of caring for these patients in the IRF setting. The CMG relative weights are updated each year based on the most recent available data for the full population of IRF Medicare fee-for-service beneficiaries. This ensures that the IRF case mix system is as reflective as possible of changes in the IRF patient populations and the associated coding practices.

After consideration of the comments we received, we are finalizing our proposal to update the CMG relative weights and ALOS values for FY 2023, as shown in Table 2 of this final rule. These updates are effective for FY 2023, that is, for discharges occurring on or after October 1, 2022 and on or before September 30, 2023.

VI. FY 2023 IRF PPS Payment Update

A. Background

Section 1886(j)(3)(C) of the Act requires the Secretary to establish an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services for which payment is made under the IRF PPS. According to section 1886(j)(3)(A)(i) of the Act, the increase factor shall be used to update the IRF prospective payment rates for each FY. Section 1886(j)(3)(C)(ii)(I) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Thus, in the proposed rule, we proposed to update the IRF PPS payments for FY 2023 by a market basket increase factor as required by section 1886(j)(3)(C) of the Act based upon the most current data available, with a productivity adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act.

We have utilized various market baskets through the years in the IRF PPS. For a discussion of these market baskets, we refer readers to the FY 2016 IRF PPS final rule (80 FR 47046).

In FY 2016, we finalized the use of a 2012-based IRF market basket, using Medicare cost report data for both freestanding and hospital-based IRFs (80 FR 47049 through 47068). Beginning with FY 2020, we finalized a rebased and revised IRF market basket to reflect a 2016 base year. The FY 2020 IRF PPS final rule (84 FR 39071 through 39086) contains a complete discussion of the development of the 2016-based IRF market basket.

B. FY 2023 Market Basket Update and Productivity Adjustment

For FY 2023 (that is, beginning October 1, 2022 and ending September 30, 2023), we proposed to update the IRF PPS payments by a market basket increase factor as required by section 1886(j)(3)(C) of the Act, with a productivity adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act. For FY 2023, we proposed to use the same methodology described in the FY 2022 IRF PPS final rule (86 FR 42373 through 42376).

Consistent with historical practice, we proposed to estimate the market basket update for the IRF PPS for FY 2023 based on IHS Global Inc.'s (IGI's) forecast using the most recent available data. Based on IGI's fourth quarter 2021 forecast with historical data through the third quarter of 2021, the proposed 2016-based IRF market basket increase factor for FY 2023 was projected to be 3.2 percent. We also proposed that if more recent data became available after the publication of the proposed rule and before the publication of the final rule (for example, a more recent estimate of the market basket update or productivity adjustment), we would use such data, if appropriate, to determine the FY 2023 market basket update in this final rule.

According to section 1886(j)(3)(C)(i) of the Act, the Secretary shall establish an increase factor based on an appropriate percentage increase in a market basket of goods and services. Section 1886(j)(3)(C)(ii) of the Act then requires that, after establishing the increase factor for a FY, the Secretary shall reduce such increase factor for FY 2012 and each subsequent FY, 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 sets forth the definition of this productivity adjustment. The statute defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide, private nonfarm business multifactor productivity (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or other annual period) (the “productivity adjustment”). The U.S. Department of Labor's Bureau of Labor Statistics (BLS) publishes the official measures of productivity for the U.S. economy. We note that previously the productivity measure referenced in 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 multifactor productivity (MFP) with total factor productivity (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) is now published by BLS as private nonfarm business total factor productivity. However, as mentioned above, the data and methods are unchanged. Please see www.bls.gov for the BLS historical published TFP data. A complete description of IGI's TFP projection methodology is available on the CMS website at https://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch. In addition, in the FY 2022 IRF final rule (86 FR 42374), we noted that effective with FY 2022 and forward, CMS changed the name of this adjustment to refer to it as the productivity adjustment rather than the MFP adjustment.

Using IGI's fourth quarter 2021 forecast, the 10-year moving average growth of TFP for FY 2023 was projected to be 0.4 percent. Thus, in accordance with section 1886(j)(3)(C) of the Act, we proposed to base the FY 2023 market basket update, which is used to determine the applicable percentage increase for the IRF payments, on IGI's fourth quarter 2021 forecast of the 2016-based IRF market basket. We proposed to then reduce this percentage increase by the estimated productivity adjustment for FY 2023 of 0.4 percentage point (the 10-year moving average growth of TFP for the period ending FY 2023 based on IGI's fourth quarter 2021 forecast). Therefore, the proposed FY 2023 IRF update was equal to 2.8 percent (3.2 percent market basket update reduced by the 0.4 percentage point productivity adjustment). Furthermore, we proposed that if more recent data became available after the publication of the proposed rule and before the publication of this final rule (for example, a more recent estimate of the market basket and/or productivity adjustment), we would use such data, if appropriate, to determine the FY 2023 market basket update and productivity adjustment in this final rule.

Based on the more recent data available for this FY 2023 IRF final rule (that is, IGI's second quarter 2022 forecast of the 2016-based IRF market basket with historical data through the first quarter of 2022), we estimate that the IRF FY 2023 market basket update is 4.2 percent. Based on the more recent data available from IGI's second quarter 2022 forecast, the current estimate of the productivity adjustment for FY 2023 is 0.3 percentage point. Therefore, the current estimate of the FY 2023 IRF productivity-adjusted market basket increase factor is equal to 3.9 percent (4.2 percent market basket update reduced by 0.3 percentage point productivity adjustment).

For FY 2023, the Medicare Payment Advisory Commission (MedPAC) recommends that we reduce IRF PPS payment rates by 5 percent.^[12] As discussed, and in accordance with sections 1886(j)(3)(C) and 1886(j)(3)(D) of the Act, the Secretary proposed to update the IRF PPS payment rates for FY 2023 by a productivity-adjusted IRF market basket increase factor of 2.8 percent. Based on more recent data, the current estimate of the productivity-adjusted IRF market basket increase factor for FY 2023 is 3.9 percent. Section 1886(j)(3)(C) of the Act does not provide the Secretary with the authority to apply a different update factor to IRF PPS payment rates for FY 2023.

We invited public comment on our proposals for the FY 2023 market basket update and productivity adjustment. The following is a summary of the public comments received on the proposed FY 2023 market basket update and productivity adjustment and our responses:

Comment: Several commenters expressed concern that the proposed market basket update is inadequate relative to input price inflation experienced by IRFs, particularly as a result of COVID-19. These commenters stated the PHE, along with inflation, has significantly driven up operating costs. The commenters expressed concern that these increased costs are not reflected in the market basket update and requested that CMS discuss in the final rule how the agency will account for these increased costs. Specifically, some commenters noted changes to the labor market, such as increased reliance on contract nurses and staff due to shortages. Several commenters also mentioned a report by the American Hospital Association, which stated there has been significant growth in hospital expenses across labor, drugs, and supplies due to recent high inflation.

One commenter had concerns that the proposed market basket forecast is neither accurately nor adequately capturing the unique factors influencing the hospital and health care market today in general, and the market in which IRFs compete specifically. In particular, the commenter was concerned that the methods used to estimate inflation in IRF spending are not capturing the pandemic-initiated shocks to the health care market that are significantly driving up costs, especially labor, across the spectrum of hospital inputs. One commenter noted that other payment systems (such as for Medicare Advantage plans) have higher increases. Several commenters supported and appreciated that CMS would use a more recent projection of the market basket but remained concerned that the impacts of the PHE would not be adequately factored into the payment rate update.

Commenters had several different suggestions for addressing these concerns. One commenter requested that CMS consider an alternative approach that would better align market basket increases with increases in cost to treat patients. A few commenters requested that CMS consider other methods and data sources to calculate the final rule market basket update that would better reflect the rapidly increasing input prices facing IRFs. A few commenters requested that CMS deviate from its typical methodology to update payments in a manner that addresses rising costs and reductions in reimbursement to ensure there are not disruptions to IRF services for Medicare beneficiaries. One commenter urged CMS to consider the pandemic triggers that do not seem to be reflected in the market basket forecast and make a PHE-related exception to further increase IRF rates to better adjust FY 2023 payments to IRFs to account for inflation. Finally, another commenter requested that CMS provide a one-time payment adjustment to supplement the cost of care.

Response: We are required to update IRF PPS payments by the market basket update adjusted for productivity, as directed by section 1886(j)(3)(C) of the Act. Specifically, section 1886(j)(3)(C)(i) states that the increase factor shall be based on an appropriate percentage increase in a market basket of goods and services comprising services for which payment is made. We believe the 2016-based IRF market basket increase adequately reflects the average change in the price of goods and services hospitals purchase in order to provide IRF medical services, and is technically appropriate to use as the IRF payment update factor. As described in the FY 2020 IRF final rule (84 FR 39072 through 39089), the IRF market basket is a fixed-weight, Laspeyres-type index that measures price changes over time and would not reflect increases in costs associated with changes in the volume or intensity of input goods and services. As such, the IRF market basket update would reflect the prospective price pressures described by the commenters as increasing during a high inflation period (such as faster wage growth or higher energy prices), but would inherently not reflect other factors that might increase the level of costs, such as the quantity of labor used or any shifts between contract and staff nurses. We note that cost changes (that is, the product of price and quantities) would only be reflected when a market basket is rebased and the base year weights are updated to a more recent time period.

We agree with the commenters that recent higher inflationary trends have impacted the outlook for price growth over the next several quarters. At the time of the FY 2023 IRF proposed rule, based on the IHS Global Inc. fourth quarter 2021 forecast with historical data through third quarter 2021, IHS Global Inc. forecasted the 2016-based IRF market basket update of 3.2 percent for FY 2023 reflecting forecasted compensation price growth of 3.8 percent (by comparison, compensation price growth in the IRF market basket averaged 2.1 percent from 2012-2021). In the FY 2023 IRF PPS proposed rule, we proposed that if more recent data became available, we would use such data, if appropriate, to derive the final FY 2023 IRF market basket update for the final rule. For this final rule, we now have an updated forecast of the price proxies underlying the market basket that incorporates more recent historical data and reflects a revised outlook regarding the U.S. economy and expected price inflation for FY 2023 for IRFs. Based on IHS Global Inc.'s second quarter 2022 forecast with historical data through the first quarter of 2022, we are projecting a FY 2023 IRF market basket update of 4.2 percent (reflecting forecasted compensation price growth of 4.8 percent) and a productivity adjustment of 0.3 percentage point. Therefore, for FY 2023 a final IRF productivity-adjusted market basket update of 3.9 percent (4.2 percent less 0.3 percentage point) will be applicable, compared to the 2.8 percent that was proposed. We note that the final FY 2023 IRF market basket growth rate of 4.2 percent would be the highest market basket update implemented in a final rule since the beginning of the IRF PPS.

Regarding commenters' request that CMS consider other methods and data sources to calculate the final rule market basket update, including the authority under section 1886(j) of the Act, while we generally agree that the Secretary has broad authority under the statute to establish the methodology for updating the IRF PPS payments, we note that our longstanding policy since the inception of the IRF PPS has been to update IRF PPS payments based on an appropriate market basket. As discussed earlier in this section of this final rule, the market basket used to update IRF PPS payments has been rebased and revised over the history of the IRF PPS to reflect more recent data on IRF cost structures. The IRF market basket was last rebased in the FY 2020 IRF final rule using 2016 Medicare cost reports (84 FR 39072 through 39084), the most recent year of complete data available at the time of the rebasing. We note that we did review the most recent Medicare cost report data available for IRFs submitted as of March 2022, which includes data through 2020. The compensation cost weight (wages and salaries, employee benefits, and contract labor) estimated for 2020 was similar to the cost weight in the 2016-based IRF market basket (59 percent). Data through 2021 are incomplete at this time. Based on this preliminary analysis, the impact on the cost weights through 2020 appear minimal and it is unclear whether any trends through 2020 are reflective of sustained shifts in the cost structure for IRFs or whether they were temporary as a result of the PHE. Therefore, we believe the current 2016-based IRF market basket continues to appropriately reflect IRF cost structures. We will continue to monitor these data and any changes to the IRF market basket will be proposed in future rulemaking. We also note that we did not propose to use other methods or data sources to calculate the final market basket update for FY 2023, and therefore, we are not finalizing such an approach for this final rule.

Finally, consistent with our proposal, we have used more recent data to calculate a final IRF productivity-adjusted market basket update of 3.9 percent for FY 2023.

Lastly, regarding commenters' concerns about payment adequacy under the IRF PPS, MedPAC did a full analysis of payment adequacy for IRF providers in its March 2022 Report to Congress ( https://www.medpac.gov/​document/​march-2022-report-to-the-congress-medicare-payment-policy/​) and determined that, even considering the cost increases that have occurred as a result of the PHE associated with the COVID-19 pandemic, payments to IRFs continue to be more than adequate. Although they acknowledged that providers' costs have increased significantly under the pandemic, they expect these costs to normalize in subsequent years and do not anticipate any long-term effects that warrant inclusion in the annual update to IRF payments in FY 2023. In fact, MedPAC recommended a 5 percent reduction to IRF PPS payments for FY 2023. Given MedPAC's analysis, we believe that payments to IRFs continue to be more than adequate and do not believe that adjustments to the FY 2023 IRF market basket update are needed at this time.

Comment: One commenter stated that the rising labor costs over the last several years mean that IRFs may be particularly undercompensated given that the IHS Global Inc. market basket forecast uses more generalized hospital goods and services, and fails to account for the specialized training and experience IRFs require of their therapists, nurses, and other clinicians, who in turn require a higher salary than those in a more generalized hospital setting. The commenter also stated that services that IRFs provide, such as advanced rehabilitation technologies and specialized drugs, may also be outpacing other hospital-level settings of care and not properly captured in the market basket. The commenter also stated that hospitals have had to increase quantities of materials such as PPE, which the commenter stated is not captured in the market basket forecasts.

Response: As described previously, the IRF market basket measures price changes (including changes in the prices for wages and salaries) over time and would not reflect increases in costs associated with changes in the volume or intensity of input goods and services until the market basket is rebased. As stated previously, we believe the 2016-based IRF market basket continues to appropriately reflect IRF cost structures. To measure price growth for IRF wages and salaries costs, the IRF market basket uses the Employment Cost Index for wages and salaries for civilian hospital workers. We believe that this ECI is the best available price proxy to account for the occupational skill mix within IRFs. We note that we reviewed the Bureau of Labor Statistics Occupational Employment Statistics (OES) data for NAICS 622100 (General Medical and Surgical Hospitals). The OES data are one of the primary data sources used to derive the weights for the ECI. In 2016, the base year of the IRF market basket, a little over 50 percent of total estimated salaries (total employment multiplied by mean annual wage) for NAICS 622100 was attributed to Health Professional and Technical occupations, and approximately 20 percent was attributed to Health Service occupations. Therefore, in the absence of IRF-specific data, we believe that the highly skilled hospital workforce captured by the ECI for hospital workers (inclusive of therapists, nurses, other clinicians, etc.) is a reasonable proxy for the compensation component of the IRF market basket.

With regard to additional costs incurred by IRFs for PPE, we acknowledge the commenters' concern that the market basket update may not reflect certain additional costs incurred during the COVID-19 PHE. As stated previously, due to the fixed-weight nature of the index, any changes to the quantity of inputs purchased (such as increased PPE as stated by the commenter) would not be reflected in the IRF market basket update for FY 2023. However, as stated in the FY 2022 IRF PPS final rule, Medicare providers may have been eligible for additional payments to cover health-care related expenses and lost revenues attributed to COVID-19, which were intended to help healthcare providers respond to the productivity losses and extra expenses caused by the PHE. In accordance with statutory requirements, the Provider Relief Fund and American Rescue Plan Act (ARPA) (Pub. L. 117-2, March 11, 2021) rural payments may not be used to reimburse expenses or losses that have been reimbursed from other sources or that other sources are obligated to reimburse. Likewise, we do not believe that it is appropriate to account for PHE-related costs in our IRF rate setting to the extent that such costs were reimbursed by the Provider Relief Fund or may be reimbursed by the ARPA Rural Distribution program (86 FR 42375).

Comment: Several commenters had concerns with the application of the productivity adjustment to the market basket update. A couple of commenters expressed concern that the continued application of the productivity adjustment further undercuts reimbursement for providers. The commenters stated that with higher rates of inflation, the currently used TFP measure will prove especially harmful to hospitals. A few commenters requested that CMS elaborate on the specific productivity gains that are the basis of this proposed reduction to the market basket as it does not align with actual hospital experience or ongoing losses from the pandemic and a nationwide labor shortage.

One commenter stated that the assumptions underpinning the productivity adjustment are fundamentally flawed and strongly disagrees with the continuation of this policy—particularly during the PHE. Another commenter referenced CMS Office of the Actuary analysis that compares the private non-farm multifactor productivity growth measure and a hospital-specific measure ( https://www.cms.gov/​files/​document/​productivity-memo.pdf). The commenter urged CMS to consider the appropriateness of this reduction in context of payment adequacy for IRFs. One commenter requested that CMS monitor the impact productivity adjustments have on rehabilitation hospitals and requested that CMS provide feedback to Congress (as these were statutorily required under the Affordable Care Act), and reduce the productivity adjustment.

One commenter urged CMS to consider its regulatory authority to modify the productivity adjustment or make a PHE related exception in its application for the FY 2023 update. Another commenter requested that CMS work with Congress to permanently eliminate the reduction to hospital payments from the productivity adjustment and further requested that CMS use its section 1135 waiver authority to remove the productivity adjustment for any fiscal year that was covered under public health emergency determination (for example, 2020, 2021, and 2022) from the calculation of market basket for FY 2023 and any year thereafter that the PHE continues.

Response: Section 1886(j)(3)(C)(ii)(I) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(xi)(II) of the Act to the IRF PPS market basket increase factor. As required by statute, the FY 2023 productivity adjustment is derived based on the 10-year moving average growth in economy-wide productivity for the period ending FY 2023. We recognize the concerns of the commenters regarding the appropriateness of the productivity adjustment; however, we are required pursuant to section 1886(j)(3)(C)(ii)(I) of the Act to apply the specific productivity adjustment described here. In addition, with respect to providing feedback to Congress, we note that MedPAC annually monitors various factors for Medicare providers in terms of profitability and beneficiary access to care and reports the findings to Congress on an annual basis. As stated previously, based on these findings, CMS believes payments to IRFs continue to be more than adequate.

Regarding the suggestion that CMS consider section 1135 waiver authority to remove the productivity adjustment, we do not believe that section 1135 authority is available in this circumstance. Section 1135 of the Act authorizes the Secretary to waive or modify only statutory provisions and regulations that pertain to the specific types of requirements that are enumerated under section 1135(b) of the Act. However, payment requirements, such as the application of the productivity adjustment under the IRF PPS, are not one of the types enumerated under section 1135(b) of the Act. Therefore, we do not believe that section 1135 of the Act would authorize the Secretary to waive the application of the productivity adjustment.

Comment: A commenter stated that given there is no provision to correct for forecast error in the market basket update in the IRF PPS, CMS should do more to account for the unique inflationary challenges currently facing the field. Another commenter stated that the forecast error adjustment proposed in the FY 2023 SNF PPS proposed rule is indicative of the complexity in accurately accounting for the unprecedented challenges driving up costs. The commenter requested CMS make an additional increase to the IRF PPS market basket factor to more closely match payment rates with the cost of IRF operations. One commenter provided a table showing the current estimates of the FY 2021 and FY 2022 IRF market basket increases (2.7 percent and 3.8 percent, respectively) relative to the FY 2021 and FY 2022 IRF market basket increases implemented in the final rules (2.4 percent and 2.6 percent, respectively). The commenter stated that the FY 2021 and the FY 2022 market basket increases were underestimated, which suggests the base rate for IRF PPS payments for FY 2023 is 1.5 percent too low. The commenter stated that this further compounds what the commenter characterized to be an inadequate increase for FY 2023.

Response: Section 1886(j)(3) of the Act requires that the Secretary shall determine a prospective payment rate for IRFs and establish an increase factor based on an appropriate percentage increase in a market basket of goods and services, which means that the update relies on a mix of both historical data for part of the period for which the update is calculated and forecasted data for the remainder. For instance, the FY 2023 market basket update in this final rule reflects historical data through the first quarter of CY 2022 and forecasted data through the third quarter of CY 2023. While there is currently no mechanism to adjust for market basket forecast error in the IRF payment update, the forecast error for a market basket update is calculated as the actual market basket increase for a given year less the forecasted market basket increase. Due to the uncertainty regarding future price trends, forecast errors can be both positive and negative. This was the case for the FY 2020 IRF forecast error, which was -0.8 percentage point, and the FY 2021 IRF forecast error, which was +0.3 percentage point; FY 2022 historical data is not yet available to calculate a forecast error for FY 2022. As noted above, forecast errors reflect both upward and downward adjustments, as appropriate. For this final rule, we have incorporated more recent historical data and forecasts to capture the price and wage pressures facing IRFs and believe it is the best available projection of inflation to determine the applicable percentage increase for the IRF payments in FY 2023. We disagree with the suggestion that the FY 2023 base rates are too low based solely on the calculation of a forecast error over a short period of time (instead of considering forecast errors over longer periods).

After consideration of the comments we received, we are finalizing a FY 2023 IRF productivity-adjusted market basket increase of 3.9 percent based on the most recent data available.

C. Labor-Related Share for FY 2023

Section 1886(j)(6) of the Act specifies that the Secretary is to adjust the proportion (as estimated by the Secretary from time to time) of IRFs' costs that are attributable to wages and wage-related costs, of the prospective payment rates computed under section 1886(j)(3) of the Act, for area differences in wage levels by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for such facilities. The labor-related share is determined by identifying the national average proportion of total costs that are related to, influenced by, or vary with the local labor market. We proposed to continue to classify a cost category as labor-related if the costs are labor-intensive and vary with the local labor market.

Based on our definition of the labor-related share and the cost categories in the 2016-based IRF market basket, we proposed to calculate the labor-related share for FY 2023 as the sum of the FY 2023 relative importance of 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 the Capital-Related relative importance from the 2016-based IRF market basket. For more details regarding the methodology for determining specific cost categories for inclusion in the 2016-based IRF labor-related share, see the FY 2020 IRF PPS final rule (84 FR 39087 through 39089).

The relative importance reflects the different rates of price change for these cost categories between the base year (2016) and FY 2023. Based on IGI's fourth quarter 2021 forecast of the 2016-based IRF market basket, the sum of the FY 2023 relative importance for Wages and Salaries, Employee Benefits, Professional Fees: Labor-related, Administrative and Facilities Support Services, Installation Maintenance & Repair Services, and All Other: Labor-related Services was 69.4 percent. We proposed that the portion of Capital-Related costs that are influenced by the local labor market is 46 percent. Since the relative importance for Capital-Related costs was 8.2 percent of the 2016-based IRF market basket for FY 2023, we proposed to take 46 percent of 8.2 percent to determine the labor- related share of Capital-Related costs for FY 2023 of 3.8 percent. Therefore, we proposed a total labor-related share for FY 2023 of 73.2 percent (the sum of 69.4 percent for the labor-related share of operating costs and 3.8 percent for the labor-related share of Capital-Related costs). We proposed that if more recent data became available after publication of the proposed rule and before the publication of this final rule (for example, a more recent estimate of the labor-related share), we would use such data, if appropriate, to determine the FY 2023 IRF labor-related share in the final rule.

Based on IGI's second quarter 2022 forecast of the 2016-based IRF market basket, the sum of the FY 2023 relative importance for Wages and Salaries, Employee Benefits, Professional Fees: Labor-related, Administrative and Facilities Support Services, Installation Maintenance & Repair Services, and All Other: Labor-related Services is 69.2 percent. Since the relative importance for Capital-Related costs is 8.1 percent of the 2016-based IRF market basket for FY 2023, we take 46 percent of 8.1 percent to determine the labor-related share of Capital-Related costs for FY 2023 of 3.7 percent. Therefore, the current estimate of the total labor-related share for FY 2023 is equal to 72.9 percent (the sum of 69.2 percent for the labor-related share of operating costs and 3.7 percent for the labor-related share of Capital-Related costs).

Table 4 shows the FY 2023 final labor-related share and the FY 2022 final labor-related share using the 2016-based IRF market basket relative importance.

We invited public comments on the proposed labor related share for FY 2023. The following is a summary of the public comments received on the proposed FY 2023 labor-related share and our responses:

Comment: One commenter suggested that CMS should consider excluding the labor portion of capital costs from the calculation of the labor-related share for FY 2023 and going forward. The commenter noted that each increase to the labor related share percentage penalizes any facility that has a wage index less than 1.0 and stated that, across this country there is a growing disparity between high-wage and low-wage States and that limiting the increase in the labor-related share helps mitigate the growing disparity.

Response: We proposed to use the FY 2023 relative importance values for the labor-related cost categories from the 2016-based IRF market basket because it accounts for more recent data regarding price pressures and cost structure of IRFs. This methodology is consistent with the determination of the labor-related share since the implementation of the IRF PPS. The labor-related cost categories reflect IRF costs that are related to, influenced by, or vary with the local labor market, which would include a portion of the capital-related costs. Therefore, we disagree with the commenter's suggestion to exclude the labor portion of capital-related costs for FY 2023 and going forward. As stated in the FY 2023 IRF proposed rule, we also proposed that if more recent data became available, we would use such data, if appropriate, to determine the FY 2023 labor-related share for the final rule. Based on IHS Global Inc.'s second quarter 2022 forecast with historical data through the first quarter of 2022, the FY 2023 labor-related share for the final rule is 72.9 percent, unchanged from the FY 2022 labor-related share.

D. Wage Adjustment for FY 2023

1. Background

Section 1886(j)(6) of the Act requires the Secretary to adjust the proportion of rehabilitation facilities' costs attributable to wages and wage-related costs (as estimated by the Secretary from time to time) by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for those facilities. The Secretary is required to update the IRF PPS wage index on the basis of information available to the Secretary on the wages and wage-related costs to furnish rehabilitation services. Any adjustment or updates made under section 1886(j)(6) of the Act for a FY are made in a budget-neutral manner.

For FY 2023, we proposed to maintain the policies and methodologies described in the FY 2022 IRF PPS final rule (86 FR 42377) related to the labor market area definitions and the wage index methodology for areas with wage data. Thus, we proposed to use the core based statistical areas (CBSAs) labor market area definitions and the FY 2023 pre-reclassification and pre-floor hospital wage index data. In accordance with section 1886(d)(3)(E) of the Act, the FY 2023 pre-reclassification and pre-floor hospital wage index is based on data submitted for hospital cost reporting periods beginning on or after October 1, 2018, and before October 1, 2019 (that is, FY 2019 cost report data).

The labor market designations made by the OMB include some geographic areas where there are no hospitals and, thus, no hospital wage index data on which to base the calculation of the IRF PPS wage index. We proposed to continue to use the same methodology discussed in the FY 2008 IRF PPS final rule (72 FR 44299) to address those geographic areas where there are no hospitals and, thus, no hospital wage index data on which to base the calculation for the FY 2023 IRF PPS wage index.

We invited public comment on our proposals regarding the Wage Adjustment for FY 2023.

The following is a summary of the public comments received on the proposed revisions to Wage Adjustment for FY 2023 and our responses:

Comment: Several commenters suggested that CMS revise the IRF wage index to adopt the same geographic reclassification and rural floor polices that apply to the IPPS wage index. Additionally, commenters stated that the IPPS implemented a policy to address disparities between high and low wage index hospitals beginning in FY 2020 and requested that CMS adopt a similar adjustment to address wage index disparities under the IRF PPS. One commenter also reiterated language from the FY 2021 IRF PPS final rule where we previously responded to similar comments related to the IRF wage index, noting it was unclear. The commenter also requested that CMS release data that would allow IRFs to crosswalk the IPPS wage index values after the application of the low wage index hospital policy to the IRF PPS wage indices.

Response: We appreciate the commenters' suggestion to adopt the IPPS reclassification and rural floor policies for the IRF wage index. As we do not have an IRF-specific wage index, we are unable to determine the degree, if any, to which a geographic reclassification adjustment or a rural floor policy under the IRF PPS would be appropriate. The rationale for our current wage index policies was most recently published in the FY 2022 IRF PPS final rule (86 FR 42377 through 42378) and fully described in the FY 2006 IRF PPS final rule (70 FR 47880, 47926 through 47928).

We appreciate the commenters' suggestion to adopt an adjustment to address wage disparities between high and low wage index areas under the IRF PPS. As most recently discussed in the FY 2021 IRF PPS final rule (85 FR 48424), we would like to note that the IRF wage index is derived from IPPS wage data, that is, the pre-reclassification and pre-floor inpatient PPS (IPPS) wage index discussed above in section D. Thus, to the extent that increasing wage index values under the IPPS for low wage index hospitals results in those hospitals increasing employee compensation, this increase would be reflected in the IPPS wage data that the IRF wage index is derived from and likely would result in higher wage indices for these areas under the IRF PPS. We note that IPPS wage index values are based on historical data and typically lag by four years. The hospital cost report data would reflect any changes in employee compensation, and as this data would become the basis for the IRF wage index in future years, any effects of these changes would be extended to the IRF setting.

Further, we are unable to provide crosswalk tables related to IPPS wage index policies. Data pertaining to the FY 2023 IPPS proposed rule are available at https://www.cms.gov/​medicare/​medicare-fee-for-service-payment/​acuteinpatientpps. We do not have any additional data on this for the IRF PPS.

After consideration of the comments we received, we are finalizing our proposal to continue to use the updated pre-reclassification and pre-floor IPPS wage index data develop the FY 2023 IRF PPS wage index.

2. Core-Based Statistical Areas (CBSAs) for the FY 2023 IRF Wage Index

The wage index used for the IRF PPS is calculated using the pre-reclassification and pre-floor inpatient PPS (IPPS) wage index data and is assigned to the IRF on the basis of the labor market area in which the IRF is geographically located. IRF labor market areas are delineated based on the CBSAs established by the OMB. The CBSA delineations (which were implemented for the IRF PPS beginning with FY 2016) are based on revised OMB delineations issued on February 28, 2013, in OMB Bulletin No. 13-01. 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). We refer readers to the FY 2016 IRF PPS final rule (80 FR 47068 through 47076) for a full discussion of our implementation of the OMB labor market area delineations beginning with the FY 2016 wage index.

Generally, OMB issues major revisions to statistical areas every 10 years, based on the results of the decennial census. Additionally, OMB occasionally issues updates and revisions to the statistical areas in between decennial censuses to reflect the recognition of new areas or the addition of counties to existing areas. In some instances, these updates merge formerly separate areas, transfer components of an area from one area to another, or drop components from an area. On July 15, 2015, OMB issued OMB Bulletin No. 15-01, which provides minor updates to and supersedes OMB Bulletin No. 13-01 that was issued on February 28, 2013. The attachment to OMB Bulletin No. 15-01 provides detailed information on the update to statistical areas since February 28, 2013. The updates provided in OMB Bulletin No. 15-01 are 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.

In the FY 2018 IRF PPS final rule (82 FR 36250 through 36251), we adopted the updates set forth in OMB Bulletin No. 15-01 effective October 1, 2017, beginning with the FY 2018 IRF wage index. For a complete discussion of the adoption of the updates set forth in OMB Bulletin No. 15-01, we refer readers to the FY 2018 IRF PPS final rule. In the FY 2019 IRF PPS final rule (83 FR 38527), we continued to use the OMB delineations that were adopted beginning with FY 2016 to calculate the area wage indexes, with updates set forth in OMB Bulletin No. 15-01 that we adopted beginning with the FY 2018 wage index.

On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which provided updates to and superseded OMB Bulletin No. 15-01 that was issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01 provide detailed information on the update to statistical areas since July 15, 2015, and are based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2014 and July 1, 2015. In the FY 2020 IRF PPS final rule (84 FR 39090 through 39091), we adopted the updates set forth in OMB Bulletin No. 17-01 effective October 1, 2019, beginning with the FY 2020 IRF wage index.

On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which superseded the August 15, 2017 OMB Bulletin No. 17-01, and on September 14, 2018, OMB issued OMB Bulletin No. 18-04, which superseded the April 10, 2018 OMB Bulletin No. 18-03. These bulletins established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas, and provided guidance on the use of the delineations of these statistical areas. A copy of this bulletin may be obtained at https://www.whitehouse.gov/​wp-content/​uploads/​2018/​09/​Bulletin-18-04.pdf.

To this end, as discussed in the FY 2021 IRF PPS proposed (85 FR 22075 through 22079) and final (85 FR 48434 through 48440) 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) beginning October 1, 2020, including a 1-year transition for FY 2021 under which we applied a 5 percent cap on any decrease in an IRF'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 IRF PPS. 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, CMS did not propose to adopt the revised OMB delineations identified in OMB Bulletin No. 20-01 for FY 2022, and for these reasons CMS is likewise not making such a proposal for FY 2023.

3. Permanent Cap on Wage Index Decreases

As discussed previously in this section of the rule, we have proposed and finalized temporary transition policies in the past to mitigate significant changes to payments due to changes to the IRF PPS wage index. Specifically, for FY 2016 (80 FR 47068), we implemented a 50/50 blend for all geographic areas consisting of the wage index values computed using the then-current OMB area delineations and the wage index values computed using new area delineations based on OMB Bulletin No. 13-01. In FY 2021 (85 FR 48434), we implemented a 1-year transition to mitigate any negative effects of wage index changes by applying a 5 percent cap on any decrease in an IRF's wage index from the final wage index from FY 2020. We explained that we believed the 5-percent cap would provide greater transparency and would be administratively less complex than the prior methodology of applying a 50/50 blended wage index. We indicated that no cap would be applied to the reduction in the wage index for FY 2022, and that this transition approach struck an appropriate balance by providing a transition period to mitigate the resulting short-term instability and negative impacts on providers and time for them to adjust to their new labor market area delineations and wage index values.

In the FY 2022 final rule (86 FR 42378), commenters recommended CMS extend the transition period adopted in the FY 2021 IRF PPS final rule so that wage index values do not change by more than 5 percent from year-to-year to protect IRFs from large payment volatility. Although we acknowledged at the time that certain changes to wage index policy may significantly affect Medicare payments, we reiterated that our policy principles with regard to the wage index include generally using the most current data and information available and providing that data and information, as well as any approaches to addressing any significant effects on Medicare payments resulting from these potential scenarios, in notice and comment rulemaking. We did not propose to modify the transition policy that was finalized in the FY 2021 IRF PPS final rule, and therefore did not extend the transition period for FY 2022. With these policy principles in mind, for the FY 2023 proposed rule, we considered how best to address the potential scenarios about which commenters raised concerns in the FY 2022 final rule around IRF payment volatility; that is, scenarios in which changes to wage index policy may significantly affect Medicare payments.

In the past, we have established transition policies of limited duration to phase in significant changes to labor market areas. In taking this approach in the past, we sought to mitigate short-term instability and fluctuations that can negatively impact providers due to wage index changes. In accordance with the requirements of the IRF PPS wage index regulations at § 412.624(a)(2), we use an appropriate wage index based on the best available data, including the best available labor market area delineations, to adjust IRF PPS payments for wage differences. We have previously stated that, because the wage index is a relative measure of the value of labor in prescribed labor market areas, we believe it is important to implement new labor market area delineations with as minimal a transition as is reasonably possible. However, we recognize that changes to the wage index have the potential to create instability and significant negative impacts on certain providers even when labor market areas do not change. In addition, year-to-year fluctuations in an area's wage index can occur due to external factors beyond a provider's control, such as the COVID-19 PHE. For an individual provider, these fluctuations can be difficult to predict. So, we also recognize that predictability in Medicare payments is important to enable providers to budget and plan their operations.

In light of these considerations, we proposed a permanent approach to smooth year-to-year changes in providers' wage indexes. We proposed a policy that we believe increases the predictability of IRF PPS payments for providers, and mitigates instability and significant negative impacts to providers resulting from changes to the wage index.

As previously discussed, we believed applying a 5-percent cap on wage index decreases for FY 2021 provided greater transparency and was administratively less complex than prior transition methodologies. In addition, we believed this methodology mitigated short-term instability and fluctuations that can negatively impact providers due to wage index changes. Lastly, we believed the 5-percent cap applied to all wage index decreases for FY 2021 provided an adequate safeguard against significant payment reductions related to the adoption of the revised CBSAs. However, as discussed in the FY 2023 proposed rule (87 FR 20230), we recognize there are circumstances that a 1-year mitigation policy, like the one adopted for FY 2021, would not effectively address future years in which providers continue to be negatively affected by significant wage index decreases.

Typical year-to-year variation in the IRF PPS wage index has historically been within 5 percent, and we expect this will continue to be the case in future years. Because providers are usually experienced with this level of wage index fluctuation, we believe applying a 5-percent cap on all wage index decreases each year, regardless of the reason for the decrease, would effectively mitigate instability in IRF PPS payments due to any significant wage index decreases that may affect providers in a year. We believe this approach would address concerns about instability that commenters raised in the FY 2022 IRF PPS rule. Additionally, we believe that applying a 5-percent cap on all wage index decreases would support increased predictability about IRF PPS payments for providers, enabling them to more effectively budget and plan their operations. Lastly, because applying a 5-percent cap on all wage index decreases would represent a small overall impact on the labor market area wage index system we believe it would ensure the wage index is a relative measure of the value of labor in prescribed labor market areas. As discussed in further detail in section XIII.C.2. of the proposed rule, we estimate that applying a 5-percent cap on all wage index decreases will have a very small effect on the wage index budget neutrality factor for FY 2023. Because the wage index is a measure of the value of labor (wage and wage-related costs) in a prescribed labor market area relative to the national average, we anticipate that in the absence of proposed policy changes most providers will not experience year-to-year wage index declines greater than 5 percent in any given year. We also believe that when the 5-percent cap would be applied under this proposal, it is likely that it would be applied similarly to all IRFs in the same labor market area, as the hospital average hourly wage data in the CBSA (and any relative decreases compared to the national average hourly wage) would be similar. While this policy may result in IRFs in a CBSA receiving a higher wage index than others in the same area (such as situations when delineations change), we believe the impact would be temporary. Therefore, we anticipate that the impact to the wage index budget neutrality factor in future years would continue to be minimal.

The Secretary has broad authority, pursuant to section 1886(j)(6) of the Act, to establish appropriate payment adjustments under the IRF PPS, including the wage index adjustment. As discussed earlier in this section, the IRF PPS regulations require us to use an appropriate wage index based on the best available data. Further, we believe that it would be appropriate to use a 5-percent cap on wage index decreases for purposes of the IRF PPS wage index adjustment for the reasons discussed in this section and in the proposed rule. Therefore, for FY 2023 and subsequent years, we proposed to apply a 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, regardless of the circumstances causing the decline. That is, we proposed that an IRF's wage index for FY 2023 would not be less than 95 percent of its final wage index for FY 2022, regardless of whether the IRF is part of an updated CBSA, and that for subsequent years, a provider's wage index would not be less than 95 percent of its wage index calculated in the prior FY. This also means that if an IRF's prior FY wage index is calculated with the application of the 5-percent cap, the following year's wage index would not be less than 95 percent of the IRF's capped wage index in the prior FY. For example, if an IRF's wage index for FY 2023 is calculated with the application of the 5-percent cap, then its wage index for FY 2024 would not be less than 95 percent of its capped wage index in FY 2023. Lastly, we proposed that a new IRF 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 IRF would not have a wage index in the prior FY. As we have discussed in the proposed rule, we believe this methodology would maintain the IRF PPS wage index as a relative measure of the value of labor in prescribed labor market areas, increase the predictability of IRF PPS payments for providers, and mitigate instability and significant negative impacts to providers resulting from significant changes to the wage index. In section XIII.C.2. of the proposed rule, we estimated the impact to payments for providers in FY 2023 based on the proposed policy. We also noted that we would examine the effects of this policy on an ongoing basis in the future in order to assess its appropriateness.

Subject to the aforementioned proposal becoming final, we also proposed to revise the regulation text at § 412.624(e)(1) to provide that starting October 1, 2022, CMS would apply a cap on decreases to the wage index such that the wage index applied is not less than 95 percent of the wage index applied to that IRF in the prior year.

We invited public comment on the proposed permanent cap on IRF wage index increase for FY 2023.

The following is a summary of the public comments received on the proposed revisions to the IRF wage index increase for FY 2023 and our responses:

Comment: MedPAC expressed support for the 5-percent permanent cap on wage index decreases, but recommended that the 5-percent cap limit should apply to both increases and decreases in the wage index because they stated that no provider should have its wage index value increase or decrease by more than 5 percent.

Response: We appreciate MedPAC's suggestion that the cap on wage index changes of more than 5 percent should also be applied to increases in the wage index. However, as we discussed in the FY 2023 IRF PPS proposed rule (87 FR 20230), one purpose of the proposed policy is to help mitigate the significant negative impacts of certain wage index changes. Likewise, we explained that we believe that applying a 5-percent cap on all wage index decreases would support increased predictability about IRF PPS payments for providers, enabling them to more effectively budget and plan their operations (87 FR 20231). That is, we proposed to cap decreases because we believe that a provider would be able to more effectively budget and plan when there is predictability about its expected minimum level of IRF PPS payments in the upcoming fiscal year. We did not propose to limit wage index increases because we do not believe such a policy would enable IRFs to more effectively budget and plan their operations. So, we believe it is appropriate for providers that experience an increase in their wage index value to receive the full benefit of their increased wage index value.

Comment: A few commenters requested that CMS retroactively apply the 5-percent cap policy to the FY 2022 wage index.

Response: In the FY 2021 IRF PPS rulemaking cycle, CMS proposed and finalized a one-time, 1-year transition policy to mitigate the effects of adopting OMB delineations updated in OMB Bulletin 18-04 by applying a 5-percent cap on any wage index decreases compared to FY 2020 in a budget neutral manner. In the FY 2023 proposed rule we did not propose to modify the one-time transition policy that was finalized in the FY 2021 final rule, nor did we propose to extend the transition period for FY 2022. We have historically implemented 1-year transitions, as discussed in the FY 2006 (70 FR 47921) and FY 2016 (80 FR 47068) final rules, to address CBSA changes due to substantial updates to OMB delineations. Our policy principles, as noted in the FY 2022 final rule (86 FR 42378), with regard to the wage index are to use the most updated data and information available. Therefore, the FY 2023 IRF PPS wage index policy proposal is prospective and is designed to mitigate any significant decreases beginning in FY 2023, not retroactively.

Comment: A number of commenters suggested the 5-percent cap be applied in a non-budget neutral manner.

Response: We do not believe that the permanent 5-percent cap policy for the IRF wage index should be applied in a non-budget-neutral manner. Any adjustment or updates made under section 1886(j)(6) of the Act for a FY must be made in a manner that assures that the aggregated payments under this subsection in the fiscal year are not greater or less than those that would have been made in the year without such adjustments. In accordance with section 1186(j)(6) of the Act, our longstanding historical practice has been to implement updates to the wage index under the IRF PPS in a budget neutral manner.

After consideration of the comments we received, we are finalizing the proposed permanent 5-percent cap on wage index decreases for the IRF PPS, beginning in FY 2023 and are finalizing revisions to the regulation text at § 412.624(e)(1) to provide that starting October 1, 2022, CMS would apply a cap on decreases to the wage index such that the wage index applied is not less than 95 percent of the wage index applied to that IRF in the prior year.

4. IRF Budget-Neutral Wage Adjustment Factor Methodology

To calculate the wage-adjusted facility payment for the payment rates set forth in this final rule, we multiply the unadjusted Federal payment rate for IRFs by the FY 2023 labor-related share based on the 2016-based IRF market basket relative importance (72.9 percent) to determine the labor-related portion of the standard payment amount. A full discussion of the calculation of the labor-related share is located in section VI.C. of this final rule. We then multiply the labor-related portion by the applicable IRF wage index. The wage index tables are available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​IRF-Rules-and-Related-Files.html.

Adjustments or updates to the IRF wage index made under section 1886(j)(6) of the Act must be made in a budget-neutral manner. We proposed to calculate a budget-neutral wage adjustment factor as established in the FY 2004 IRF PPS final rule (68 FR 45689) and codified at § 412.624(e)(1), as described in the steps below. We proposed to use the listed steps to ensure that the FY 2023 IRF standard payment conversion factor reflects the proposed update to the wage indexes (based on the FY 2019 hospital cost report data) and the proposed update to the labor-related share, in a budget-neutral manner:

Step 1. Calculate the total amount of estimated IRF PPS payments using the labor-related share and the wage indexes from FY 2022 (as published in the FY 2022 IRF PPS final rule (86 FR 42362)).

Step 2. Calculate the total amount of estimated IRF PPS payments using the FY 2023 wage index values (based on updated hospital wage data and considering the permanent cap on wage index decreases policy) and the FY 2023 labor-related share of 72.9 percent.

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2. The resulting quotient is the FY 2023 budget-neutral wage adjustment factor of 1.0002.

Step 4. Apply the budget neutrality factor from step 3 to the FY 2023 IRF PPS standard payment amount after the application of the increase factor to determine the FY 2023 standard payment conversion factor.

We discuss the calculation of the standard payment conversion factor for FY 2023 in section VI.E. of this final rule.

We invited public comments on the proposed IRF wage adjustment for FY 2023 (and the proposed permanent cap on wage index decreases policy).

We did not receive any comments on the proposed IRF budget-neutral wage adjustment factor methodology for FY 2023. Comments related to the proposed budget neutral wage index cap policy are addressed in the Permanent Cap on Wage Index Decreases section (VI.D.3) above. We are finalizing the IRF budget-neutral wage adjustment factor methodology as described in this final rule.

E. Description of the IRF Standard Payment Conversion Factor and Payment Rates for FY 2023

To calculate the standard payment conversion factor for FY 2023, as illustrated in Table 5, we begin by applying the increase factor for FY 2023, as adjusted in accordance with sections 1886(j)(3)(C) of the Act, to the standard payment conversion factor for FY 2022 ($17,240). Applying the 3.9 percent increase factor for FY 2023 to the standard payment conversion factor for FY 2022 of $17,240 yields a standard payment amount of $17,912. Then, we apply the budget neutrality factor for the FY 2023 wage index (taking into account the permanent cap on wage index decreases policy), and labor-related share of 1.0002, which results in a standard payment amount of $17,916. We next apply the budget neutrality factor for the CMG relative weights of 0.9979, which results in the standard payment conversion factor of $17,878 for FY 2023.

We invited public comments on the proposed FY 2023 standard payment conversion factor.

The following is a summary of the public comments received on the proposed revisions to the FY 2023 standard payment conversion factor and our responses:

Comment: One commenter recommended that CMS should increase the standard payment conversion factor to account for increased costs resulting from the implementation of version 4.0 of the IRF-PAI.

Response: We appreciate this commenter's concerns. However, we note that the IRF 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 IRF services, as required by section 1886(j)(3)(C) of the Act. We do not have the statutory authority to make changes to the standard payment conversion factor outside of the annual market basket update and to ensure that any adjustment or update to the IRF wage index made as specified under section 1886(j)(6) of the Act will be made in a budget neutral manner that assures that the estimated aggregated payments under this subsection in the FY year are not greater or less than those that will have been made in the year without such adjustment.

After consideration of the comments we received, we are finalizing the standard payment conversion factor for FY 2023 as proposed.

After the application of the CMG relative weights described in section V. of this final rule to the FY 2023 standard payment conversion factor ($17,878), the resulting unadjusted IRF prospective payment rates for FY 2023 are shown in Table 6.

F. Example of the Methodology for Adjusting the Prospective Payment Rates

Table 7 illustrates the methodology for adjusting the prospective payments (as described in section VI. of this final rule). The following examples are based on two hypothetical Medicare beneficiaries, both classified into CMG 0104 (without comorbidities). The unadjusted prospective payment rate for CMG 0104 (without comorbidities) appears in Table 7.

Example: One beneficiary is in Facility A, an IRF located in rural Spencer County, Indiana, and another beneficiary is in Facility B, an IRF located in urban Harrison County, Indiana. Facility A, a rural non-teaching hospital has a Disproportionate Share Hospital (DSH) percentage of 5 percent (which would result in a LIP adjustment of 1.0156), a wage index of 0.8380, and a rural adjustment of 14.9 percent. Facility B, an urban teaching hospital, has a DSH percentage of 15 percent (which would result in a LIP adjustment of 1.0454 percent), a wage index of 0.8600, and a teaching status adjustment of 0.0784.

To calculate each IRF's labor and non-labor portion of the prospective payment, we begin by taking the unadjusted prospective payment rate for CMG 0104 (without comorbidities) from Table 7. Then, we multiply the labor-related share for FY 2023 (72.9 percent) described in section VI.C. of this final rule by the unadjusted prospective payment rate. To determine the non-labor portion of the prospective payment rate, we subtract the labor portion of the Federal payment from the unadjusted prospective payment.

To compute the wage-adjusted prospective payment, we multiply the labor portion of the Federal payment by the appropriate wage index located in the applicable wage index table. This table is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​IRF-Rules-and-Related-Files.html.

The resulting figure is the wage-adjusted labor amount. Next, we compute the wage-adjusted Federal payment by adding the wage-adjusted labor amount to the non-labor portion of the Federal payment.

Adjusting the wage-adjusted Federal payment by the facility-level adjustments involves several steps. First, we take the wage-adjusted prospective payment and multiply it by the appropriate rural and LIP adjustments (if applicable). Second, to determine the appropriate amount of additional payment for the teaching status adjustment (if applicable), we multiply the teaching status adjustment (0.0784, in this example) by the wage-adjusted and rural-adjusted amount (if applicable). Finally, we add the additional teaching status payments (if applicable) to the wage, rural, and LIP-adjusted prospective payment rates. Table 7 illustrates the components of the adjusted payment calculation.

Thus, the adjusted payment for Facility A would be $28,817.54, and the adjusted payment for Facility B would be $28,257.27.

VII. Update to Payments for High-Cost Outliers Under the IRF PPS for FY 2023

A. Update to the Outlier Threshold Amount for FY 2023

Section 1886(j)(4) of the Act provides the Secretary with the authority to make payments in addition to the basic IRF prospective payments for cases incurring extraordinarily high costs. A case qualifies for an outlier payment if the estimated cost of the case exceeds the adjusted outlier threshold. We calculate the adjusted outlier threshold by adding the IRF PPS payment for the case (that is, the CMG payment adjusted by all of the relevant facility-level adjustments) and the adjusted threshold amount (also adjusted by all of the relevant facility-level adjustments). Then, we calculate the estimated cost of a case by multiplying the IRF's overall CCR by the Medicare allowable covered charge. If the estimated cost of the case is higher than the adjusted outlier threshold, we make an outlier payment for the case equal to 80 percent of the difference between the estimated cost of the case and the outlier threshold.

In the FY 2002 IRF PPS final rule (66 FR 41362 through 41363), we discussed our rationale for setting the outlier threshold amount for the IRF PPS so that estimated outlier payments would equal 3 percent of total estimated payments. For the FY 2002 IRF PPS final rule, we analyzed various outlier policies using 3, 4, and 5 percent of the total estimated payments, and we concluded that an outlier policy set at 3 percent of total estimated payments would optimize the extent to which we could reduce the financial risk to IRFs of caring for high-cost patients, while still providing for adequate payments for all other (non-high cost outlier) cases.

Subsequently, we updated the IRF outlier threshold amount in the FYs 2006 through 2022 IRF PPS final rules and the FY 2011 and FY 2013 notices (70 FR 47880, 71 FR 48354, 72 FR 44284, 73 FR 46370, 74 FR 39762, 75 FR 42836, 76 FR 47836, 76 FR 59256, 77 FR 44618, 78 FR 47860, 79 FR 45872, 80 FR 47036, 81 FR 52056, 82 FR 36238, 83 FR 38514, 84 FR 39054, 85 FR 48444, and 86 FR 42362, respectively) to maintain estimated outlier payments at 3 percent of total estimated payments. We also stated in the FY 2009 final rule (73 FR 46370 at 46385) that we would continue to analyze the estimated outlier payments for subsequent years and adjust the outlier threshold amount as appropriate to maintain the 3 percent target.

To update the IRF outlier threshold amount for FY 2023, we proposed to use FY 2021 claims data and the same methodology that we used to set the initial outlier threshold amount in the FY 2002 IRF PPS final rule (66 FR 41362 through 41363), which is also the same methodology that we used to update the outlier threshold amounts for FYs 2006 through 2022. The outlier threshold is calculated by simulating aggregate payments and using an iterative process to determine a threshold that results in outlier payments being equal to 3 percent of total payments under the simulation. To determine the outlier threshold for FY 2023, we estimated the amount of FY 2023 IRF PPS aggregate and outlier payments using the most recent claims available (FY 2021) and the proposed FY 2023 standard payment conversion factor, labor-related share, and wage indexes, incorporating any applicable budget-neutrality adjustment factors. The outlier threshold is adjusted either up or down in this simulation until the estimated outlier payments equal 3 percent of the estimated aggregate payments. Based on an analysis of the preliminary data used for the proposed rule, we estimated that IRF outlier payments as a percentage of total estimated payments would be approximately 3.8 percent in FY 2022. Therefore, we proposed to update the outlier threshold amount from $9,491 for FY 2022 to $13,038 for FY 2023 to maintain estimated outlier payments at approximately 3 percent of total estimated aggregate IRF payments for FY 2023.

In the proposed rule we stated we believed that updating the outlier threshold for FY 2023 would be appropriate to maintain IRF PPS outlier payments at 3 percent of total estimated payments, and we recognized that the proposed outlier threshold amount for FY 2023 would result in a significant increase from the current outlier threshold amount for FY 2022. As we continue to explore the underlying reasons for the large change in the proposed outlier threshold amount, we welcomed comments from commenters on any observations or information related to the increase in the proposed update to outlier threshold amount for FY 2023.

We note that, as we typically do, we updated our data between the FY 2023 IRF PPS proposed and final rules to ensure that we use the most recent available data in calculating IRF PPS payments. This updated data includes a more complete set of claims for FY 2021. Based on our analysis using this updated data, we estimate that IRF outlier payments as a percentage of total estimated payments are approximately 3.6 percent in FY 2022. Therefore, we will update the outlier threshold amount from $9,491 for FY 2022 to $12,526 for FY 2023 to account for the increases in IRF PPS payments and estimated costs and to maintain estimated outlier payments at approximately 3 percent of total estimated aggregate IRF payments for FY 2023.

The following is a summary of the public comments received on the proposed update to the FY 2023 outlier threshold amount and our responses.

Comment: Some commenters expressed concerns with the proposed outlier threshold amount and suggested that CMS consider making temporary changes to the outlier threshold methodology to account for changes in the data due to the COVID-19 PHE. Commenters suggested using data from FY 2019, adjusting the data to account for changes in IRF utilization associated with the pandemic, blending multiple years of data or averaging the current 2022 threshold with the proposed threshold, using a charge inflation factor from prior years, and adjusting the CCRs used in the outlier calculation.

Response: We thank the commenters for the various suggested revisions to the outlier threshold methodology. We appreciate the suggestions to use FY 2019 data and not FY 2021 claims data in determining the outlier threshold for FY 2023. However, we believe the FY 2021 data reflect changes in IRF utilization related to the PHE and will therefore be more likely to reflect IRF utilization in FY 2023, as COVID-19 will continue to impact IRFs in the future.

We also do not believe the suggestions to blend multiple years of data or determine an average of the current threshold and the proposed threshold would be appropriate, as arbitrarily lowering the outlier threshold would fail to address the fact that for FY 2022 we estimate that we are overpaying by 0.6 percent the established outlier pool of 3 percent for the IRF PPS. Additionally, our simulations assume that cost-to-charge ratios accurately reflect IRF costs and we do not believe using inflation factors from prior years would reflect the best available projection of inflation in FY 2023. We appreciate the commenters' suggestions and will take them into consideration as we continue to consider revisions to our outlier threshold methodology. We will continue to monitor the IRF outlier payments to ensure that they continue to compensate IRFs appropriately for treating unusually high-cost patients.

Comment: Some commenters suggested that CMS should include historical outlier reconciliation dollars in the outlier projections consistent with IPPS to ensure a more accurate calibration of the outlier payment amounts. These commenters requested that CMS conduct further analysis of the increasing concentration of outlier payments and provide that analysis for discussion with the field.

Response: We thank the commenters for their suggestion to include historical outlier reconciliation dollars in the outlier projections. We will continue to explore and analyze the outlier payments and will consider these suggestions for revisions to payment policies in future rulemaking, during which we will solicit public comment.

Comment: Commenters suggested that CMS consider policies that would better target outlier payments, such as placing a 10 percent cap on the amount of outlier payments any IRF could receive or lowering the 3 percent outlier pool. Additionally, commenters recommended that changes in the outlier threshold should be limited to changes in the market basket in a given year.

Response: We thank the commenters for their suggestion to the outlier threshold. Our outlier policy is intended to reimburse IRFs for treating extraordinarily costly cases. As most recently discussed in the FY 2020 IRF PPS Final Rule (84 FR 39054) any future consideration given to imposing a limit on outlier payments would have to carefully analyze and take into consideration the effect on access to IRF care for certain high-cost populations. We continue to believe that maintaining the outlier pool at 3 percent of aggregate IRF payments optimizes the extent to which we can reduce financial risk to IRFs of caring for highest-cost patients, while still providing for adequate payments for all other non-outlier cases as discussed in the FY 2002 IRF PPS final rule (66 FR 41362 through 41363). Additionally, we do not believe it would be appropriate to limit changes in the outlier threshold to changes in the market basket as constraining adjustments to the outlier threshold may result in a threshold that generates outlier payments above or below the 3 percent target.

After consideration of the comments received and considering the most recent available data, we are finalizing the outlier threshold amount of $12,526 to maintain estimated outlier payments at approximately 3 percent of total estimated aggregate IRF payments for FY 2023.

B. Update to the IRF Cost-to-Charge Ratio Ceiling and Urban/Rural Averages for FY 2023

CCRs are used to adjust charges from Medicare claims to costs and are computed annually from facility-specific data obtained from MCRs. IRF specific CCRs are used in the development of the CMG relative weights and the calculation of outlier payments under the IRF PPS. In accordance with the methodology stated in the FY 2004 IRF PPS final rule (68 FR45692 through 45694), we proposed to apply a ceiling to IRFs' CCRs. Using the methodology described in that final rule, we proposed to update the national urban and rural CCRs for IRFs, as well as the national CCR ceiling for FY 2023, based on analysis of the most recent data available. We apply the national urban and rural CCRs in the following situations:

• New IRFs that have not yet submitted their first MCR.
• IRFs whose overall CCR is in excess of the national CCR ceiling for FY 2023, as discussed below in this section.
• Other IRFs for which accurate data to calculate an overall CCR are not available.

Specifically, for FY 2023, we proposed to estimate a national average CCR of 0.463 for rural IRFs, which we calculated by taking an average of the CCRs for all rural IRFs using their most recently submitted cost report data. Similarly, we proposed to estimate a national average CCR of 0.393 for urban IRFs, which we calculated by taking an average of the CCRs for all urban IRFs using their most recently submitted cost report data. We apply weights to both of these averages using the IRFs' estimated costs, meaning that the CCRs of IRFs with higher total costs factor more heavily into the averages than the CCRs of IRFs with lower total costs. For this final rule, we have used the most recent available cost report data (FY 2020). This includes all IRFs whose cost reporting periods begin on or after October 1, 2019, and before October 1, 2020. If, for any IRF, the FY 2020 cost report was missing or had an “as submitted” status, we used data from a previous FY's (that is, FY 2004 through FY 2019) settled cost report for that IRF. We do not use cost report data from before FY 2004 for any IRF because changes in IRF utilization since FY 2004 resulting from the 60 percent rule and IRF medical review activities suggest that these older data do not adequately reflect the current cost of care. Using updated FY 2020 cost report data for this final rule, we estimate a national average CCR of 0.466 for rural IRFs, and a national average CCR of 0.392 for urban IRFs.

In accordance with past practice, we proposed to set the national CCR ceiling at 3 standard deviations above the mean CCR. Using this method, we proposed a national CCR ceiling of 1.40 for FY 2023. This means that, if an individual IRF's CCR were to exceed this ceiling of 1.40 for FY 2023, we will replace the IRF's CCR with the appropriate proposed national average CCR (either rural or urban, depending on the geographic location of the IRF). We calculated the proposed national CCR ceiling by:

Step 1. Taking the national average CCR (weighted by each IRF's total costs, as previously discussed) of all IRFs for which we have sufficient cost report data (both rural and urban IRFs combined).

Step 2. Estimating the standard deviation of the national average CCR computed in step 1.

Step 3. Multiplying the standard deviation of the national average CCR computed in step 2 by a factor of 3 to compute a statistically significant reliable ceiling.

Step 4. Adding the result from step 3 to the national average CCR of all IRFs for which we have sufficient cost report data, from step 1.

We also proposed that if more recent data became available after the publication of the proposed rule and before the publication of this final rule, we would use such data to determine the FY 2023 national average rural and urban CCRs and the national CCR ceiling in the final rule. Using the updated FY 2020 cost report data for this final rule, we estimate a national average CCR ceiling of 1.41, using the same methodology.

We invited public comment on the proposed update to the IRF CCR ceiling and the urban/rural averages for FY 2023.

However, we did not receive any comments on the proposed revisions to the IRF CCR ceiling and the urban/rural averages for FY 2023, and therefore, we are finalizing a national average urban CCR at 0.392, the national average rural CCR at 0.466, and the national average CCR ceiling at 1.41 for FY 2023.

VIII. Codification and Clarifications of IRF Teaching Status Adjustment Policy

In the FY 2006 IRF PPS final rule (70 FR 47928 through 47932), we implemented § 412.624(e)(4) to establish a facility level adjustment for IRFs that are teaching hospitals or units of teaching hospitals. The teaching status adjustment accounts for the higher indirect operating costs experienced by IRFs that participate in training residents in graduate medical education (GME) programs. The teaching status payment adjustment is based on the ratio of the number of full-time equivalent (FTE) interns and residents training in the IRF divided by the IRF's average daily census. Section 1886(j)(3)(A)(v) of the Act requires the Secretary to adjust the prospective payment rates for the IRF PPS by such factors as the Secretary determines are necessary to properly reflect the variations in necessary costs of treatment among rehabilitation facilities.

We established the IRF teaching status adjustment in a manner that limited the incentives for IRFs to add FTE interns and residents for the purpose of increasing their teaching status adjustment, as has been done in the payment systems for Inpatient Psychiatric Facilities (IPF) and acute care hospitals. That is, we imposed a cap on the number of FTE interns and residents that the IRF can count for the purpose of calculating the teaching status adjustment. This cap is similar to the cap established by the Balanced Budget Act of 1997 (Pub. L. 105-33, enacted August 5, 1997) section 4621, that added section 1886(d)(5)(B)(v) of the Act (indirect medical education (IME) FTE cap for IPPS hospitals. The cap limits the number of FTE interns and residents that teaching IRFs may count for the purpose of calculating the IRF PPS teaching status adjustment, not the number of interns and residents that teaching institutions care hire or train. The cap is equal to the number of FTE interns and residents that trained in the IRF during a “base year,” that is based on the most recent final settled cost report for a cost reporting period ending on or before November 15, 2004. A complete discussion of how the IRF teaching status adjustment was calculated appears in the FY 2006 IRF PPS final rule (70 FR 47928 through 47932).

In the FY 2012 IRF PPS final rule (76 FR 47846 through 47848) published on August 5, 2011, we updated the IRF PPS teaching status adjustment policy in order to maintain consistency, to the extent feasible, with the indirect medical education (IME) teaching policies that were finalized in the IPPS FY 1999 final rule (64 FR 41522), the IPPS FY 2001 final rule (66 FR 39900), and the IPF PPS teaching adjustment policies finalized in the 2012 IPF PPS final rule (76 FR 26454 through 26456). In that final rule, we adopted a policy which permits a temporary increase in the FTE intern and resident cap when an IRF increases the number of FTE residents it trains, in order to accept displaced residents because another IRF closes or closes a medical residency training program. We refer to a “displaced” resident or intern as one that is training in an IRF and is unable to complete training in that IRF, either because the IRF closes or closes a medical residency training program.

The cap adjustment for IRFs, adopted in the FY 2012 IRF PPS final rule, is considered temporary because it is resident-specific and will only apply to the residents until they have completed their training in the program in which they were training at the time of the IRF closure or the closure of the program. Similar to the IPPS and IPF policy for displaced residents, the IRF PPS temporary cap adjustment only applies to residents that were still training at the IRF at the time the IRF closed or at the time the IRF ceased training residents in the residency training program(s). Residents who leave the IRF, for whatever reason, before the closure of the IRF or the closure of the medical residency training program are not considered displaced residents for purposes of the IRF temporary cap adjustment policy.

In the FY 2012 IRF PPS final rule, we also adopted the IPPS definition of “closure of a hospital” at § 413.79(h)(1)(i) to refer to circumstances in which the IRF terminates its Medicare provider agreement, as specified in § 489.52. In this instance, we allow a temporary adjustment to an IRF's FTE cap to reflect residents added to their medical residency training program because of an IRF's closure. We allow an adjustment to an accepting IRF's FTE cap if the IRF meets the criteria outlined in the FY 2012 IRF PPS final rule (76 FR 47847). After the displaced residents leave the accepting IRF's training program or complete their medical residency training program, the accepting IRF's cap will revert to its original level. As such, the temporary adjustment to the FTE cap will be available to the IRF only for the period of time necessary for the displaced residents to complete their training.

Additionally, in the FY 2012 IRF PPS final rule, we adopted the IPPS definition of “closure of a hospital residency training program,” as specified in § 413.79(h)(1)(ii), which means that the hospital ceases to offer training for interns and residents in a particular approved medical residency training program. In this instance, if an IRF ceases training residents in a medical residency training program(s) and agrees to temporarily reduce its FTE cap, another IRF may receive a temporary adjustment to its FTE cap to reflect the addition of the displaced residents. For more discussion regarding the methodology for adjusting the caps for the “receiving IRF” and the “IRF that closed its program,” refer to the FY 2012 IRF PPS final rule (76 FR 47847).

A. Codification of Existing Teaching Status Adjustment Policies

In an effort to streamline the IRF PPS teaching status adjustment policies that were finalized in the FY 2006 IRF PPS final rule (70 FR 47928 through 47932) and the FY 2012 IRF PPS final rule (76 FR 47846 through 47848), we are codifying the longstanding policy so that these policies can be easily located by IRF providers and can also align, to the extent feasible, with the IPPS IME and IPF teaching adjustment policy regulations.

First, we are codifying the policy that was finalized in the FY 2006 IRF PPS final rule with respect to how CMS adjusts the Federal prospective payment on a facility basis by a factor to account for indirect teaching costs. When the teaching status adjustment policy was finalized in the FY 2006 IRF PPS final rule (70 FR 47928 through 47932), the definition of this “factor” and explanations of how it is computed were not included in the regulations. Rather, the more detailed definition and the explanation of the teaching status payment adjustment provided in the FY 2006 IRF PPS final rule, were published in the Medicare Claims Processing Manual (100-04, chapter 3, 140.2.5.4). Currently, § 412.624(e)(4) states that for discharges on or after October 1, 2005, CMS adjusts the Federal prospective payment on a facility basis by a factor as specified by CMS for facilities that are teaching institutions or units of teaching institutions. This adjustment is made on a claim basis as an interim payment and the final payment in full for the claim is made during the final settlement of the cost report.

Second, we are codifying the IRF policy that was adopted in the FY 2012 IRF PPS final rule (76 FR 47846 through 47848) allowing an IRF to receive a temporary adjustment to its FTE cap to reflect residents added to its teaching program because of another IRF's closure or an IRF's medical residency training program closure. We believe that codifying these longstanding policies would improve clarity and reduce administrative burden on IRF providers and others trying to locate all relevant information pertaining to the teaching hospital adjustment.

Thus, we are codifying CMS' existing IRF PPS' teaching hospital adjustment policies through amendments to §§ 412.602 and 412.624(e)(4) presented in this final rule; except as specifically noted in this final rule, our intent is to codify the existing IRF PPS teaching status adjustment policy.

We invited public comment on our proposal to amend §§ 412.602 and 412.624(e)(4) to codify our longstanding policies regarding the teaching status adjustment.

The following is a summary of the public comments received on the proposed revisions to codify the existing IRF PPS teaching status adjustment policy and our responses:

Comment: Most commenters were supportive of CMS codifying and consolidating the definition of the teaching status adjustment factor and how the adjustment is calculated in the regulation.

Response: We thank the commenters for their support to codify current regulatory guidelines that were previously located in the Medicare Claims Processing Manual, Chapter 3, Section 140 and were established in the FY 2006 IRF PPS Final Rule (70 FR 47880) and modified in the FY 2012 IRF PPS Final Rule (76 FR 47836). We continue to believe that codifying the requirements will improve clarity and reduce administrative burden for IRFs.

After consideration of the comments we received, we are codifying the IRF PPS teaching status adjustment calculation in §§ 412.602 and 412.624(e)(4), as proposed.

B. Update to the IRF Teaching Policy on IRF Program Closures and Displaced Residents

For FY 2023, we proposed to change the IRF policy pertaining to displaced residents resulting from IRF closures and closures of IRF residency teaching programs. Specifically, we proposed to adopt conforming changes to the IRF PPS teaching status adjustment policy to align with the policy changes that the IPPS finalized in the FY 2021 IPPS final rule (85 FR 58432, 58865 through 58870) and that the IPF finalized in the FY 2022 IPF PPS final rule (86 FR 42608, 42618 through 42621). We believe that the IRF teaching status adjustment policy relating to hospital closure and displaced residents is susceptible to the same vulnerabilities as the IPPS IME policy. Hence, if an IRF with residents training in its residency program announces it is closing, these residents will become displaced and will need to find alternative positions at other IRFs or risk being unable to become board-certified.

We proposed to implement the policy discussed in this section to remain consistent with the IPPS policy for calculating the temporary IME resident cap adjustment in situations where the receiving hospital assumes the training of displaced residents due to another hospital or residency program's closure. We also proposed that, in the future, we would deviate from the IPPS IME policy as it pertains to counting displaced residents for the purposes of the IRF teaching status adjustment only when it is necessary and appropriate for the IRF PPS.

The policy adopted in the FY 2012 IRF PPS final rule (76 FR 47846 through 47848), published August 5, 2011, permits an IRF to temporarily adjust its FTE cap to reflect displaced residents added to their residency program because of another IRF closure or IRF residency program closure. In that final rule, we adopted the IPPS definition of “closure of a hospital” at § 413.79(h)(1)(i) to also apply to IRF, and to mean that the IRF terminates its Medicare provider agreement as specified in § 489.52. We also adopted the IPPS definition of “closure of a hospital residency training program” as it is currently defined at § 413.79(h)(1)(ii) to also apply to IRF residency training program closures, and to mean that the IRF ceases to offer training for residents in a particular approved medical residency training program. In this final rule, we are codifying both of these definitions within the IRF PPS definitions section provided at § 412.602 so that the IRF teaching policies are more centrally located and more easily accessible.

Although not explicitly stated in the regulations, our current policy is that a displaced resident is one that is physically present at the hospital training on the day prior to or the day of hospital or residency program closure. This longstanding policy derived from the fact that there are requirements that the receiving IRF identifies the residents “who have come from the closed IRF” or identifies the residents “who have come from another IRF's closed residency program,” and that the IRF that closed its program identifies “the residents who were in training at the time of the residency program's closure.” We considered the residents who were physically present at the IRF to be those residents who were “training at the time of the program's closure,” thereby granting them the status of “displaced residents.” Although we did not want to limit the “displaced residents” to only those physically present at the time of closure, it becomes much more administratively challenging for the following groups of residents at closing IRFs/residency programs to continue their training:

(1) Residents who leave the program after the closure is publicly announced to continue training at another IRF, but before the actual closure;

(2) Residents assigned to and training at planned rotations at other IRFs who will be unable to return to their rotations at the closing IPF or program; and

(3) Individuals (such as medical students or would-be fellows) who matched into resident programs at the closing IRF or residency program, but have not yet started training at the closing IRF or residency program.

Other groups of residents who, under current policy, are already considered “displaced residents” include—

(1) Residents who are physically training in the IRF on the day prior to or day of residency program or IRF closure; and

(2) Residents who would have been at the closing IRF or IRF residency program on the day prior to or day of closure, but were on approved leave at that time, and are unable to return to their training at the closing IRF or IRF residency training program.

We proposed to amend our IRF policy with regard to closing teaching IRFs and closing IRF medical residency training programs to address the needs of interns and residents attempting to find alternative IRFs in which to complete their training. Additionally, this proposal addresses the incentives of originating and receiving IRFs with regard to ensuring we appropriately account for their indirect teaching costs by way of an appropriate IRF teaching adjustment based on each program's FTE resident count. We proposed to make changes to the current IRF teaching status adjustment policy related to displaced residents as discussed below.

First, rather than link the status of displaced residents for the purpose of the receiving IRF's request to increase their FTE cap to the resident's presence at the closing IRF or program on the day prior to or the day of the residency program or IRF closure, we proposed to link the status of the displaced residents to the day that the closure was publicly announced (for example, via a press release or a formal notice to the Accreditation Council on Graduate Medical Education). This would provide great flexibility for the interns and residents to transfer while the IRF operations or teaching programs are winding down, rather than waiting until the last day of IRF or IRF teaching program operation. This would address the needs of the group of residents who would leave the program after the closure was publicly announced to continue training at another hospital, but before the day of actual closure.

Second, by removing the link between the status of displaced residents and their presence at the closing IRF or residency program on the day prior to or the day of the IRF closure or program closure, we proposed to also allow the residents assigned to and training at planned rotations at other IRFs who will be unable to return to their rotations at the closing IRF or program and individuals (such as medical students or would-be fellows) who matched into resident programs at the closing IRF or residency program, but have not yet started training at the closing IRF or residency program, to be considered a displaced resident.

Thus, we proposed to revise our teaching policy with regard to which residents can be considered “displaced” for the purpose of the receiving IRF's request to increase their IRF cap in the situation where an IRF announces publicly that it is closing, and/or that it is closing an IRF residency program. Specifically, we proposed to adopt the FY 2021 IPPS final rule definition of “displaced resident” as defined at § 413.79(h)(1)(ii), for the purpose of calculating the IRF's teaching status adjustment.

In addition, we proposed to change another detail of the policy specific to the requirements for the receiving IRF. To apply for the temporary increase in the FTE resident cap, the receiving IRF would have to submit a letter to its Medicare Administrative Contractor (MAC) within 60 days after beginning to train the displaced interns and residents. As established in the FY 2012 IRF PPS final rule, this letter must identify the residents who have come from the closed IRF or closed residency program and caused the receiving IRF to exceed its cap, and must specify the length of time that the adjustment is needed. Furthermore, to maintain consistency with the IPPS IME policy, we proposed that the letter must also include:

(1) The name of each displaced resident;

(2) The last four digits of each displaced resident's social security number; this will reduce the amount of personally identifiable information (PII);

(3) The name of the IRF and the name of the residency program or programs in which each resident was training at previously; and

(4) The amount of the cap increase needed for each resident (based on how much the receiving IRF is in excess of its cap and the length of time for which the adjustments are needed).

As we previously discussed in the FY 2012 IRF PPS final rule (76 FR 47846 through 47848), we are also clarifying that the maximum number of FTE resident cap slots that could be transferred to all receiving IRFs is the number of FTE resident cap slots belonging to the IRF that has closed the resident training program, or that is closing. Therefore, if the originating IRF is training residents in excess of its cap, then being a displaced resident does not guarantee that a cap slot will be transferred along with the resident. Therefore, we proposed that if there are more IRF displaced residents than available cap slots, the slots may be apportioned according to the closing IRF's discretion. The decision to transfer a cap slot if one is available would be voluntary and made at the sole discretion of the originating IRF. However, if the originating IRF decides to do so, then it would be the originating IRF's responsibility to determine how much of an available cap slot would go with a particular resident (if any). We also note that, as we previously discussed in the FY 2012 IRF PPS final rule (76 FR 47846 through 47848), only to the extent a receiving IRF would exceed its FTE cap by training displaced residents would it be eligible for a temporary adjustment to its resident FTE cap. As such, displaced residents are factored into the receiving IRF's ratio of resident FTEs to the facility's average daily census.

We invited public comment on the proposed updates to the IRF teaching policy.

The following is a summary of the public comments received on the proposed updates to the IRF teaching policy and our responses:

Comment: Commenters were generally supportive of our proposal to amend §§ 412.602 and 412.624(e)(4) to codify our longstanding policies regarding the teaching status adjustment. These commenters stated that they appreciated us clarifying the definition of a displaced resident for the purpose of reallocating the FTE to a new IRF, mitigating prior delayed transfer issues.

Response: We thank the commenters for their support to codify longstanding policies regarding the teaching status adjustment.

Comment: While expressing support for the proposed codification of the regulations, one commenter stated that the increases in the FTE resident caps for IRFs should be made permanent, similar to what is done for IPPS hospitals in accordance with Section 5506 of the Patient Protection and Affordable Care Act (PPACA) (Pub. L. 111-148).

Response: We appreciate the commenter's concern, but Section 5506 of the PPACA does not apply to IRFs, and we do not believe that it would be appropriate to permanently increase the number of FTE resident cap slots available in the IRF PPS.

After consideration of the comments we received, we are finalizing the proposed updates to the IRF teaching policies in §§ 412.602 and 412.624(e)(4), as proposed.

IX. Solicitation of Comments Regarding the Facility-Level Adjustment Factor Methodology

Section 1886(j)(3)(A)(v) of the Act confers broad authority upon the Secretary to adjust the per unit payment rate “by such other factors as the Secretary determines are necessary to properly reflect variations in necessary costs of treatment among rehabilitation facilities.” Under this authority, we currently adjust the prospective payment amount associated with a CMG to account for facility-level characteristics such as a facility's percentage of low-income patients (LIP), teaching status, and location in a rural area, if applicable, as described in §  412.624(e).

The facility-level adjustment factors are intended to account for differences in costs attributable to the different types of IRF providers and to better align payments with the costs of providing IRF care. The LIP and rural facility-level adjustment factors have been utilized since the inception of the IRF PPS, while the teaching status adjustment factor was finalized in the FY 2006 IRF PPS final rule (70 FR 47880) when our regression analysis indicated that it had become statistically significant in predicting IRF costs. Each of the facility-level adjustment factors were implemented using the same statistical approach, that is, utilizing coefficients determined from regression analysis.

Historically, we have observed relatively large fluctuations in these factors from year-to-year which led us to explore a number of options to provide greater stability and predictability between years and increase the accuracy of Medicare payments for IRFs. In addition to holding these factors constant over multiple years to mitigate fluctuations in payments, we also implemented a number of refinements to the methodology used to calculate the adjustment factors in efforts to better align payments with the costs of care. For example, in FY 2010 (74 FR 39762) we implemented a 3-year moving average approach to updating the facility-level adjustment factors to promote more consistency in the adjustment factors over time. Additionally, in FY 2014 (78 FR 47859) we added an indicator variable for a facility's freestanding or hospital-based status to the payment regression to improve the accuracy of the IRF payment adjustments. This variable was added to control for differences in cost structure between hospital-based and freestanding IRFs in the regression analysis, so that these differences would not inappropriately influence the adjustment factor estimates. We refer readers to the FY 2015 IRF PPS final rule (79 FR 45882 through 45883) for a full discussion of the refinements that have been made to the methodology used to determine the facility-level adjustment factors and other analysis that has been considered over time. Due to the revisions to the regression analysis and the substantive changes to the facility-level adjustment factors that were adopted in the FY 2014 IRF PPS final rule, we finalized a proposal in the FY 2015 IRF PPS final rule (79 FR 45871) to freeze the facility-level adjustment factors for FY 2015 and all subsequent years at the FY 2014 levels while we continued to monitor changes in the adjustment factors over time. Table 8 shows how the IRF facility-level adjustment factors have changed over time since the start of the IRF PPS:

We have continued monitoring the adjustment factors using the same methodology described in the FY 2014 IRF PPS final rule (78 FR 47869). That is, we have continued to calculate the facility-level adjustment factors using the following the steps:

(Steps 1 and 2 are performed independently for each of three years of IRF claims data)

Step 1. Calculate the average cost per case for each IRF in the available IRF claims data.

Step 2. Perform a logarithmic regression analysis on the average cost per case to compute the coefficients for the rural, LIP, and teaching status adjustments. This regression analysis incorporates an indicator variable to account for whether a facility is a freestanding IRF hospital or a unit of an acute care hospital (or a CAH).

Step 3. Calculate a mean for each of the coefficients across the 3 years of data (using logarithms for the LIP and teaching status adjustment coefficients (because they are continuous variables), but not for the rural adjustment coefficient (because the rural variable is either zero (if not rural) or 1 (if rural)). To compute the LIP and teaching status adjustment factors, we convert these factors back out of the logarithmic form.

Additional information on the regression analysis used to calculate the facility-level adjustment factors can be found on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​Research. We have continued to monitor changes in the facility-level adjustment factors for each FY since they were frozen in FY 2015 at the FY 2014 levels. Table 9, contains the rural, LIP, and teaching status adjustment factors for each FY since they were frozen at their 2014 levels.

Table 10 shows the potential estimated impacts of updating the facility-level adjustments for FY 2023.

Table 10 shows how we estimated that the application of the FY 2023 facility-level adjustment factors would affect particular groups if we were to implement updates to these factors for FY 2023. Table 10 categorizes IRFs by geographic location, including urban or rural location, and location for CMS' 9 Census divisions of the country. In addition, Table 10 divides IRFs into those that are separate rehabilitation hospitals (otherwise called freestanding hospitals in this section), those that are rehabilitation units of a hospital (otherwise called hospital units in this section), rural or urban facilities, ownership (otherwise called for-profit, non-profit, and government), by teaching status, and by disproportionate share patient percentage (DSH PP).

Note that, because the facility-level adjustment factors are implemented in a budget-neutral manner, total estimated aggregate payments to IRFs would not be affected. However, these updates would affect the distribution of payments across providers.

Typically, the facility-level adjustment factors have been updated on an intermittent basis to reflect changes in the costs of caring for patients. However, given the magnitude of the increases we are consistently seeing in the teaching status adjustment we do not believe that they are true reflections of the higher costs of teaching IRFs. In addition, we are concerned with the negative effects that the inordinately high teaching status adjustments would have on rural IRFs, given that the updates would be implemented in a budget neutral manner.

Given the changes in the teaching status adjustment and the rural adjustment from their 2014 levels and the potential payment impacts associated with these adjustments, we solicited comments from interested parties on the methodology used to determine the facility-level adjustment factors and suggestions for possible updates and refinements to this methodology. Additionally, we welcomed ideas and suggestions as to what could be driving the changes observed in these adjustment factors from year-to-year.

While we will not be responding to specific comments submitted in response to the solicitation of comments regarding the facility-level adjustment factor methodology in this final rule, we appreciate all of the comments we received. We will take these comments and suggestions into account in future development of payment policies.

X. Solicitation of Comments Regarding the IRF Transfer Payment Policy

In the Medicare Program; Prospective Payment System for Inpatient Rehabilitation Facilities final rule that appeared in the August 7, 2001 Federal Register (66 FR 41353 through 41355), we finalized a transfer payment policy under § 412.624(f) to provide for payments that more accurately reflect facility resources used and services delivered. This reflected our belief that it is important to minimize the inherent incentives specifically associated with the early transfer of patients in a discharge-based payment system. Specifically, we were concerned that incentives might exist for IRFs to discharge patients prematurely, as well as to admit patients that may not be able to endure intense inpatient therapy services. Even if patients were transferred before receiving the typical, full course of inpatient rehabilitation, the IRF could still be paid the full CMG payment rate in the absence of a transfer payment policy. Length of stay has been shown to be a good proxy measure of costs. Thus, in general, reducing lengths of stay would be profitable under the IRF prospective payment system. To address these concerns, we therefore implemented a transfer payment policy, which took effect beginning January 1, 2002, that, under certain circumstances, reduced the full CMG payment rate when a Medicare beneficiary is transferred.

The IRF transfer payment policy applies to IRF stays that are less than the average length of stay for the applicable CMG and tier and are transferred directly to another institutional site, including another IRF, an inpatient hospital, a nursing home that accepts payment under Medicare and Medicaid, or a long-term care hospital. However, the IRF transfer payment policy currently does not apply to IRF stays that are less than the average length of stay for the applicable CMG and tier and are transferred to home health care.

In the August 7, 2001 final rule (66 FR 41353 through 41355), we stated that we did not propose to include early discharges to home health care as part of the transfer payment policy because there were analytical challenges as a result of the recent implementation of the new home health prospective payment system. However, to date, the analytical challenges would not present an issue as we believe the home health payment system is well established with an adequate supply of claims data.

A recent Office of Inspector General (OIG) report, “Early Discharges From Inpatient Rehabilitation Facilities to Home Health Services” ^[13] recommends that CMS expand the IRF transfer payment policy to apply to early discharges to home health. The OIG recommends that the IRF PPS should update its transfer payment policy, similar to the IPPS transfer payment policy, to include home health. The OIG conducted an audit of calendar year 2017 and 2018 Medicare claims data and determined that if CMS had expanded its IRF transfer payment policy to include early discharges to home health it could have realized a significant savings of approximately $993 million over the 2-year period to Medicare.

Initially, home health was not added to the IRF transfer policy due to a lack of home health claims data under the newly-established prospective payment system that we could analyze to determine the impact of this policy change. However, given the findings from the recent OIG report mentioned above, we plan to analyze home health claims data to determine the appropriateness of including home health in the IRF transfer policy:

• Beyond the existing Medicare claims data, under what circumstances, and for what types of patients (in terms of clinical, demographic, and geographic characteristics) do IRFs currently transfer patients to home health?
• Should we consider a policy similar to the IPPS transfer payment policy (see § 412.4(a), (b) and (c))—such as including as part of the IRF transfer payment policy a discharge from an IRF to home health under a written plan for the provision of home health services from a home health agency and those services to begin within 48 hours of referral, or within 48 hours of the patient's return home (see § 484.55(a)(1)), or on the provider's start of care date?
• What impact, if any, do interested parties believe this proposed policy change could have on patient access to appropriate post-acute care services?

While we will not be responding to specific comments submitted in response to the solicitation of comments regarding the IRF transfer payment policy in this final rule, we appreciate all of the comments we received. We will use this information from public commenters in conjunction with our future analysis for potential rulemaking.

XI. Inpatient Rehabilitation Facility (IRF) Quality Reporting Program (QRP)

A. Background and Statutory Authority

The Inpatient Rehabilitation Facility Quality Reporting Program (IRF QRP) is authorized by section 1886(j)(7) of the Act, and it applies to freestanding IRFs, as well as inpatient rehabilitation units of hospitals or Critical Access Hospitals (CAHs) paid by Medicare under the IRF PPS. Under the IRF QRP, the Secretary must reduce by 2 percentage points the annual increase factor for discharges occurring during a fiscal year for any IRF that does not submit data in accordance with the IRF QRP requirements established by the Secretary. For more information on the background and statutory authority for the IRF QRP, we refer readers to the FY 2012 IRF PPS final rule (76 FR 47873 through 47874), the CY 2013 Hospital Outpatient Prospective Payment System/Ambulatory Surgical Center (OPPS/ASC) Payment Systems and Quality Reporting Programs final rule (77 FR 68500 through 68503), the FY 2014 IRF PPS final rule (78 FR 47902), the FY 2015 IRF PPS final rule (79 FR 45908), the FY 2016 IRF PPS final rule (80 FR 47080 through 47083), the FY 2017 IRF PPS final rule (81 FR 52080 through 52081), the FY 2018 IRF PPS final rule (82 FR 36269 through 36270), the FY 2019 IRF PPS final rule (83 FR 38555 through 38556), the FY 2020 IRF PPS final rule (84 FR 39054 through 39165), and the FY 2022 IRF PPS final rule (86 FR 42384 through 42408).

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

For a detailed discussion of the considerations we use for the selection of IRF QRP quality, resource use, or other measures, we refer readers to the FY 2016 IRF PPS final rule (80 FR 47083 through 47084).

1. Quality Measures Currently Adopted for the FY 2023 IRF QRP

The IRF QRP currently has 18 measures for the FY 2023 program year, which are set out in Table 11.

There were no proposals in the proposed rule for new measures for the IRF QRP.

C. IRF QRP Quality Measure Concepts for Future Years: Request for Information (RFI)

We sought input on the importance, relevance, and applicability of each of the concepts under consideration listed in Table 12 for future years in the IRF QRP. More specifically, we sought input on a cross-setting functional measure that would incorporate the domains of self-care and mobility. Our measure development contractor for the cross-setting functional outcome measure convened a Technical Expert Panel (TEP) on June 15 and June 16, 2021 to obtain expert input on the development of a functional outcome measure for PAC. During this meeting, the possibility of creating one measure to capture both self-care and mobility was discussed. We also sought input on measures of health equity, such as structural measures that assess an organization's leadership in advancing equity goals or assess progress toward achieving equity priorities. Finally, we sought input on the value of a COVID-19 Vaccination Coverage measure that would assess whether IRF patients were up to date on their COVID-19 vaccine.

We received several comments on this RFI, which are summarized below:

Comment: A majority of commenters generally supported the inclusion of a cross-setting function measure in the IRF QRP, while many commenters requested additional information pertaining to data collection and measure specifications. Several commenters urged CMS to ensure the measure is meaningful and appropriately implemented for all settings. One commenter stated they preferred separate quality measures for self-care and mobility, but would support the initial use of a composite measure reflecting both self-care and mobility function.

Commenters did not address the concept of a health equity measure but cautioned CMS on additional provider burden for new measures and encouraged CMS to leverage existing data elements.

Several commenters were generally supportive of the inclusion of the PAC—COVID-19 Vaccination Coverage among Patients measure in the IRF QRP. However, some caveated their support and requested further details regarding measure specifications and NQF endorsement. Several commenters raised concerns about the guidance around boosters, as well as whether an IRF length of stay allows for meaningful distinctions among facilities.

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.

D. Inclusion of the National Healthcare Safety Network (NHSN) Healthcare-Associated Clostridioides difficile Infection Outcome Measure in the IRF QRP—Request for Information

1. Solicitation of Public Comment

In section XI.D. of the proposed rule, we requested stakeholder input on the potential electronic submission of quality data from IRFs via their electronic health records (EHRs) under the IRF QRP. We specifically sought comment on the future inclusion of the NHSN Healthcare-Associated Clostridioides difficile Infection Outcome measure (HA-CDI) (MUC2021-098) as a digital quality measure in the IRF QRP.

Specifically, we sought comment on the following:

• Would you support utilizing IRF EHRs as the mechanism of data collection and submission for IRF QRP measures?
• Would your EHR support exposing data via HL7 FHIR to a locally installed Measure Calculation Tool (MCT)? For IRFs using certified health IT systems, how can existing certification criteria under the Office of the National Coordinator (ONC) Health Information Technology (IT) Certification Program support reporting of this data? What updates, if any, to the Certification Program would be needed to better support capture and submission of this data?
• Is a transition period between the current method of data submission and an electronic submission method necessary? If so, how long of a transition would be necessary and what specific factors are relevant in determining the length of any transition?
• Would vendors, including those that service IRFs, be interested in or willing to participate in pilots or voluntary electronic submission of quality data?
• Do IRFs anticipate challenges, other than the adoption of EHR to adopting the HA-CDI, and if so, what are potential solutions for those challenges?

We received several comments on this RFI, which are summarized below:

Comment: In response to the question of whether IRFs would support utilizing EHRs as the mechanism of data collection and submission for IRF QRP measures, we received several supportive comments, citing the increased accuracy by relying “on both microbiologic evidence of C. diff in stool and evidence of antimicrobial treatment using data derived from the electronic health record (EHR)” and decreased provider burden associated with a digital measure. One of these commenters recommended CMS adopt the measure in larger acute care hospitals where use of EHRs is already more prevalent, prior to adopting it in IRFs.

However, commenters raised concerns about the cost associated with IRFs adopting EHR systems that are equipped to collect and exchange digital quality measure (dQM) data. They stated EHR adoption has been slower and less uniform than it was in acute care hospitals, due to the lack of incentive payments available to IRFs. They urged CMS to provide incentive payments to IRFs as they did for acute care hospitals through the Health Information Technology for Economic and Clinical Health (HITECH) Act prior to requiring IRFs' transition to dQMs. One of these commenters noted that IRFs could use those incentive payments to offset implementation costs, such as additional staff, licensing fees and new software and systems.

Commenters also supported the idea of a transition period between the current method of data submission and an electronic submission, and several commenters suggested a 2-year transition period. One commenter stated that some IRFs would need time to implement an EHR system while IRFs that already use EHRs would still need to make refinements to their system. Another commenter recommended that CMS launch a pilot for this measure and/or establish a process for manual data submission as a backup for a specified time before the digital measure is fully implemented.

One commenter indicated their interest in participating in a pilot or voluntary electronic submission of quality data. Other commenters stated they would be willing to participate in a pilot prior to implementation of a digital quality measure (dQM).

In response to the solicitation of comments about challenges IRFs anticipate in the adoption of the NHSN HA-CDI measure, we received one comment about the challenges posed by the adoption of new terminology to end users as well as the challenges associated with implementing new technology into IRF workflows. This commenters also pointed out that the RFI in the proposed rule noted that the Centers for Disease Control and Prevention (CDC) plans to enable reporting using the existing HL7 Clinical Document Architecture and potentially other formats, while continuing to support the current CDI measure until sufficient experience is achieved with the new measure, and while they appreciate CDC's flexibility, they questioned the data integrity across all facilities when so many technology options are in use. Another commenter raised concerns about cyber security, and noted the potential security risk might not outweigh the time involved in manual submission.

Finally, several commenters did not support the idea of the NHSN HA-CDI measure for the IRF QRP, citing a low incidence rate in IRFs, and the lack of meaningful differences in provider performance.

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. One commenter questioned whether it would be worth the cost to IRFs to make the necessary changes to the EHR when incidence is low in IRF patients.

E. Overarching Principles for Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs—Request for Information

1. Solicitation of Public Comment

The goal of the request for information in section XI.E. of the proposed rule was to describe key principles and approaches that we would consider when advancing the use of quality measure development and stratification to address healthcare disparities and advance health equity across our programs.

We invited general comments on the principles and approaches described previously in this section of the rule, as well as additional thoughts about disparity measurement or stratification guidelines suitable for overarching consideration across CMS' QRP programs. Specifically, we invited comment on:

• Identification of Goals and Approaches for Measuring Healthcare Disparities and Using Measure Stratification Across CMS Quality Reporting Programs

++ The use of the within- and between-provider disparity methods in IRFs to present stratified measure results.

++ The use of decomposition approaches to explain possible causes of measure performance disparities.

++ Alternative methods to identify disparities and the drivers of disparities.

• Guiding Principles for Selecting and Prioritizing Measures for Disparity Reporting

++ Principles to consider for prioritization of health equity measures and measures for disparity reporting, including prioritizing stratification for validated clinical quality measures, those measures with established disparities in care, measures that have adequate sample size and representation among healthcare providers and outcomes, and measures of appropriate access and care.

• Principles for Social Risk Factor and Demographic Data Selection and Use

++ Principles to be considered for the selection of social risk factors and demographic data for use in collecting disparity data including the importance of expanding variables used in measure stratification to consider a wide range of social risk factors, demographic variables, and other markers of historic disadvantage. In the absence of patient-reported data we will consider use of administrative data, area-based indicators, and imputed variables as appropriate.

• Identification of Meaningful Performance Differences

++ Ways that meaningful difference in disparity results should be considered.

• Guiding Principles for Reporting Disparity Measures

++ Guiding principles for the use and application of the results of disparity measurement.

• Measures Related to Health Equity

++ The usefulness of a Health Equity Summary Score (HESS) for IRFs, both in terms of provider actionability to improve health equity, and in terms of whether this information would support Care Compare website users in making informed healthcare decisions.

++ The potential for a structural measure assessing an IRF's commitment to health equity, the specific domains that should be captured, and options for reporting this data in a manner that would minimize burden.

++ Options to collect facility-level information that could be used to support the calculation of a structural measure of health equity.

++ Other options for measures that address health equity.

We received several comments on the RFI for Overarching Principles for Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs. While we will not be responding to specific comments submitted in response to this RFI, the following is a summary of some comments received:

Comment: We received several comments on the structural measure for health equity. One commenter supported the concept of a structural quality measure of health equity and believed it would be a step that could lead to more complex measures, and noted that the Leapfrog Hospital Safety Grade program has an established framework that can be used for this measure, including a standardized set of questions for hospitals that capture demographic data elements. Other commenters opposed the measure and expressed that it may not provide useful or actionable data to differentiate IRFs on quality and equity for IRFs or consumers. One commenter noted that larger facilities may have more resources to invest in this area, and as such, perform better than smaller facilities on this type of measure. Another commenter did not support the measure, citing the Measure Application Partnership's Hospital Workgroup observation that “evidence for a linkage between the measure and improved health outcomes had not been established” and that “a performance gap among hospitals for the measure's five structural elements ( i.e., to which attestation would be required) had not been demonstrated.” Furthermore, they shared that many of the priorities in this structural measure are often already addressed by IRFs through initiatives to provide culturally competent and inclusive care and to meet existing accreditation requirements. Finally, two commenters did not support or oppose the measure and requested additional information on the measure definition and how it can be used to advance health equity.

We received three comments on performance disparity decomposition. Two commenters supported the idea of performance disparity decomposition and believed that it would provide valuable data for IRFs while minimizing burden. However, one commenter added a caveat stating that not all IRFs would have the statistical expertise or resources to implement this approach. One commenter opposed the idea, specifically the potential application of the Blinder-Oaxaca methodology.

We received several comments on the concept of the HESS. Some commenters supported the concept of the HESS and noted it would provide a comprehensive view of a patient's clinical, social, and behavioral risks. Despite expressing their support, one commenter noted that the development of the HESS presents several technical challenges, such as the need for a comprehensive standardized set of demographic data elements for each patient, an imputation method for missing data elements, and a method for accounting for small sample sizes within an IRF. A few commenters opposed the development of a HESS and stated that an aggregated quality score would not provide actionable insights for IRFs and confuse consumers. Commenters favored more transparent and accessible methods to collect and measure health equity. Finally, a few commenters requested additional information before proceeding with the development of the HESS score, since the current HESS metric in Medicare Advantage needs to be modified significantly before being applicable to the IRF setting.

Commenters generally supported the combination of within- and between-hospital disparity methods and believed that these complementary approaches could provide comprehensive information to facilities. Commenters in support of the provision requested that the data remain confidential while IRFs become familiar with the data and that CMS consider risk adjustment for IRF characteristics for between-hospital results. One commenter recommended CMS evaluate whether this approach is appropriate for all measures, and especially cautioned against using between-hospital disparity methods for any potential patient experience measures. The commenter stated that “by benchmarking subgroups and making comparisons of those subgroups in patient experience data, it can lead to the expectation that it is `normal' for certain subgroups to report less favorable patient experiences.” The commenter instead encouraged CMS to compute benchmarks for the entire patient population and to introduce incentives for reducing the gap in performance between groups.

Commenters generally supported the addition of data elements like race, ethnicity, language preference, sexual orientation, gender, stable housing, food insecurity, socioeconomic status, veteran status, and other social determinants of health. One commenter encouraged CMS to improve measures of patient social risk and prioritize identifying social risk factors that should be accounted for in a quality payment program using an evidence-based approach. A few commenters emphasized the importance of disability status and recommended CMS define, collect standardized data for, and measure disability status, particularly for IRF care access and outcomes.

Commenters generally suggested prioritizing the development of disparity analysis and reporting before determining the best approach to identify meaningful differences in IRF performance. One commenter suggested grouping IRFs with similar patients to determine rewards and penalties based on comparison with an IRF's peers. Commenters generally opposed a ranked ordering and percentile approach to order IRFs based on their performance because they believed variations in patient populations and IRFs would create challenges in accurately comparing IRFs against each other.

Several commenters encouraged CMS to share stratified results of existing measures in confidential feedback reports. Furthermore, one commenter encouraged CMS to share these results for topped-out measures that were previously removed from programs to determine if these data reveal meaningful disparities in performance when stratified. Commenters also encouraged CMS to establish high standards for stratification and reliability. Relatedly, some suggested strategies include establishing a minimum case count for IRFs or pooling data across years. Other commenters proposed the inclusion of confidence intervals, cut points based on standard deviations, or clustering algorithms to help IRFs contextualize their performance.

Response: Public input is very valuable to the continuing development of CMS' health equity quality measurement efforts and broader commitment to health equity; a key pillar of our strategic vision, as well as a core agency function. Thus, we will continue to take all concerns, comments, and suggestions into account for future development and expansion of policies to advance health equity across the IRF QRP, including by supporting IRFs in their efforts to ensure equity for all of their patients, and to identify opportunities for improvements in health outcomes.

F. Proposals Relating to the Form, Manner, and Timing of Data Submission Under the IRF QRP

1. Background

We refer readers to the regulatory text at § 412.634(b) for information regarding the current policies for reporting IRF QRP data.

2. Proposal To Require Quality Data Reporting on all IRF Patients Beginning With the FY 2025 IRF QRP

a. Background

We have received public input for the past 10 years on the need to standardize measurement data collection across all payers in the PAC settings. For example, as part of their recommendations on Coordination Strategy for Post-Acute Care and Long-term Care Performance Measurement,^[14] the National Quality Forum (NQF)-convened Measures Application Partnership (MAP) defined priorities and core measure concepts for PAC, including IRFs, in order to improve care coordination for patients. The MAP concluded that standardized measurement data collection is needed to support the flow of information and data among PAC providers and recommended CMS collect data across all payers. Since the implementation of the Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT Act) and the development of the statutorily required quality measures, we have also received public input suggesting that the quality measures used in the IRF QRP should be calculated using data collected from all IRF patients, regardless of the patients' payer. This input has been provided to us through different mechanisms, including comments requested about quality measure development. Specifically, in response to the call for public comment on quality measures to satisfy the IMPACT Act domain of Transfer of Health Information and Care Preferences When an Individual Transitions,^[15] the majority of comments expressed concern over the non-standardized populations across the PAC setting and urged CMS to standardize the patient populations. One commenter stated having an all-payer policy in place in some, but not all PAC settings, limits the ability of providers and consumers to interpret the information. In the FY 2018 IRF PPS proposed rule (82 FR 20740), we sought input on expanding the quality measures to include all patients regardless of payer status. In response to the Request for Information (RFI), several commenters supported expanding the IRF QRP to include all patients regardless of payer. The Medicare Payment Advisory Commission (MedPAC) was supportive of the effort to ensure quality care for all patients, but sensitive to the issue of additional burden, while another commenter questioned whether the use of additional data would outweigh the burden of additional reporting. Other commenters were also supportive, noting that it would not be overly burdensome since most of their organizations' members already complete the IRF-PAI on all patients, regardless of payer status. One commenter supported the idea since collecting information on only a subset of patients could be interpreted as having provided different levels of care based on the payer.

In the FY 2020 IRF PPS proposed rule (84 FR 17326 to 17327), CMS proposed to expand IRF quality data reporting on all patients regardless of payer for purposes of the IRF QRP. In the FY 2020 IRF PPS final rule (84 FR 39161 through 39163), we decided not to finalize the proposal at the time, but rather use the comments to help inform a future all-payer proposal.

b. Support for Expanding Quality Reporting Data on all IRF Patients

Currently, IRF-PAI assessment data are collected on patients admitted under the Medicare Part A fee-for-service (FFS) and Medicare Part C benefits.^[16]

The concept of requiring quality data reporting on all patients regardless of payer is not new; as part of the Long-Term Care Hospital (LTCH) quality reporting program, CMS currently collects quality data on all patients regardless of payer. CMS also collects quality data on all Hospice patients for the Hospice Quality Reporting Program (HQRP) regardless of payer. Eligible clinicians participating in the Merit-based Incentive Payment System (MIPS) who submit quality measure data on Qualified Clinical Data Registry (QCDR) measures, MIPS clinical quality measures (CQMs) or electronic clinical quality measures (eCQMs) must submit such data on a specified percentage of patients regardless of payer. Collecting such quality data on all patients in the IRF setting would provide the most robust and accurate representation of quality in the IRFs since CMS does not have access to other payer claims. Additionally, the data would promote higher quality and more efficient healthcare for Medicare beneficiaries and all patients through the exchange of information and longitudinal analysis of that data.

We believe that data reporting on standardized patient assessment data elements using the IRF-PAI should include all IRF patients for the same reasons we believe that collecting data on Medicare beneficiaries for the IRF QRP's quality measures is important: to achieve equity in healthcare outcomes for our beneficiaries by supporting providers in quality improvement activities, enabling them to make more informed decisions, and promoting provider accountability for healthcare disparities.^[17 18] We believe that we have authority to collect all-payer data for the IRF QRP under section 1886(j)(7) of the Act. We believe it is necessary to obtain admission and discharge assessment information on all patients admitted to IRFs in order to obtain full and complete data regarding the quality of care provided by the IRF to the Medicare patients receiving care in that facility. We note, however, that these data would not be used by CMS for purposes of updating the IRF PPS payment rates annually. In addition, we note that section 1886(j)(7) of the Act does not limit the Secretary to collecting data only on individuals with Medicare, and therefore this proposal is not inconsistent with CMS' statutory obligations.

We take the appropriate access to care in IRFs very seriously, and routinely monitor the QRP measures' performance, including performance gaps across IRFs. We intend to monitor closely whether any proposed change to the IRF QRP has unintended consequences on access to care for high risk patients. Should we find any unintended consequences, we will take appropriate steps to address these issues in future rulemaking. We wish to clarify that although CMS stated as part of the proposed rule that we believed that expanding the reporting of quality measures to include all patients, regardless of payer, would ensure that the IRF QRP makes publicly available information regarding the quality of services furnished to the IRF population as a whole CMS did not make any proposals for policies related to publicly reporting IRF QRP data collected on non-Medicare patients as part of the proposed rule, and therefore is not finalizing any such policies as part of this rule.

We also take the privacy and security of protected health information (PHI) very seriously. Our systems conform to all applicable Federal laws and regulations as well as Federal government, Department of Health & Human Services (HHS), and CMS policies and standards as they relate to information security and data privacy. The system limits data access to authorized users and monitors such users to ensure against unauthorized data access or disclosures.

While we appreciate that collecting quality data on all patients regardless of payer may create additional burden, we also note that this burden may be partially offset by eliminating the effort to separate out Medicare beneficiaries from other patients, which is also burdensome. We also acknowledge the concerns raised by some stakeholders in the past with respect to the administrative challenges of implementing all payer data collection and the need to account for the burden related to the proposal. In section XII.B. of the proposed rule, we provided an estimate of additional burden related to the proposal.

c. Proposal To Require Quality Data Reporting on all IRF Patients

In order to facilitate and ensure that high-quality care is delivered to all patients, including Medicare beneficiaries, in the IRF setting, we proposed to require that the IRF-PAI assessment be collected on each patient receiving care in an IRF, regardless of payer, beginning with the FY 2025 IRF QRP. If finalized as proposed, IRFs would be required to report these data with respect to admission and discharge for all patients, regardless of payer, discharged between October 1, 2023 and December 31, 2023. These data would be used (in addition to the data collected January 1, 2023 through September 30, 2023) to calculate an IRF's data completion threshold for the FY 2025 IRF QRP.

In the proposed rule we noted that if finalized as proposed, we would revise the IRF-PAI in order for IRFs to submit data pursuant to the finalized policy. A new item would replace the current item identifying payment source on the IRF-PAI admission assessment to collect additional payer(s) information. The collection of this item would align with the LTCH setting. A draft IRF PAI containing this new item would be available at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​IRF-Quality-Reporting. We would notify stakeholders when the draft IRF PAI is available.

We invited public comments on this proposal.

The following is a summary of the public comments received on the proposal to collect IRF quality data on all patients regardless of payer and our responses:

Comment: We received support from several commenters on our proposal to require quality data reporting on all IRF patients, regardless of payer, beginning with the FY 2025 IRF QRP. Commenters expressed support for CMS's intention to standardize data collection for all patients. Relatedly, one commenter noted that collecting assessment data on subsets of populations could be interpreted as providing different levels of care. Other commenters appreciated that collecting all-payer data will allow IRF QRP measures to include all patients regardless of payer status to ensure representation of the quality of services provided on the population as a whole, rather than a subset limited to Medicare, and one commenter agreed with CMS that the inclusion of all-payer data will more accurately reflect the quality of care provided to IRF patients. Another commenter highlighted that by aligning data collection across payer types, it will allow health equity issues to be examined consistently for all patients, regardless of payer. Regarding burden, MedPAC noted that “since it has long been common practice for providers to collect IRF-PAI data on all patients, expanding IRF quality measures to include all patients should not be particularly onerous and may even relieve burden, to the extent that providers must now separate out assessment data for Medicare patients from that of all patients.”

Response: We thank the commenters for their support. We take the appropriate access to care in IRFs seriously, and routinely monitor the QRP measures' performance, including performance gaps across IRFs. Expanding the reporting of quality measures to include all patients, regardless of payer, will further inform our quality work at CMS, allowing for the continued improvement in quality of care.

In addition, there were many providers who expressed their understanding of CMS' rationale and supported the concept of collecting quality data on all IRF patients regardless of payer, but raised various concerns about the implementation of the proposal. We will address each of these comments here.

Comment: Several commenters stated that CMS did not provide enough information on how the data collection for all IRF patients, regardless of payer, would be implemented and operationalized. Commenters questioned how the IRF-PAI data would be validated for determining reporting compliance when CMS does not have access to claims from other payers. Given the financial penalty IRFs face for non-compliance with the QRP, they requested more detail on how this would be handled.

Response: IRFs would be required to collect and submit the QRP data for all patients in the same manner and method they are accustomed to for patients with Medicare and Medicare Advantage. IRFs will use the IRF-PAI assessment instrument and submit the data through iQIES. The IRF QRP requires that the data be submitted and accepted by CMS according to the established submission timelines. An IRF-PAI for each patient discharged from the IRF must be submitted no later than 11:59 p.m. the day of the quarterly submission deadline. IRFs have generally 4.5 months after the end of a quarter to submit their data. More information about the data submission deadlines can be found on the IRF Data Submission Deadlines web page at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​IRF-Quality-Reporting/​IRF-Quality-Reporting-Data-Submission-Deadlines. For the purposes of calculating compliance, IRF-PAI data submissions for the calendar year are reviewed against the requirements of the IRF QRP. Of the assessments received, 95 percent must contain 100 percent of the data required to calculate the IRF QRP quality measures. The IRF-PAI compliance percentage is calculated by dividing the numerator (the number of IRF-PAI assessments with 100 percent of the required IRF-PAI data elements) by the denominator (the number of assessments submitted successfully before the submission deadlines). Each year, CMS issues notices to providers found non-compliant. This methodology is not dependent on Medicare claims to determine AIF compliance.

We would remind providers that IRFs are currently required to meet the IRF QRP requirements as authorized by section 1886(j)(7) of the Act, and it applies to freestanding IRFs, as well as inpatient rehabilitation units of hospitals or Critical Access Hospitals (CAHs) paid by Medicare under the IRF PPS. Under the IRF QRP, the Secretary must reduce by 2 percentage points the annual increase factor for discharges occurring during a fiscal year for any IRF that does not submit data in accordance with the IRF QRP requirements established by the Secretary.

Comment: Several commenters questioned how CMS would align rules between stays covered by private insurers and stays covered by Medicare given that private insurers may not recognize interrupted stays.

Response: CMS does not expect to align rules with private insurers, since the completion of the IRF-PAI is for purposes of meeting the IRF QRP data collection requirements. An interrupted stay is defined as a stay by a patient who is discharged from the IRF and returns to the same IRF within 3 consecutive calendar days. CMS treats this situation as one combined IRF stay, and the IRF would not need to complete another IRF-PAI when the patient returns to the IRF after the interruption. However, it is expected that the IRF would update the information in the patient's medical record ^[19] to make sure that it is current (that is, update the patient's condition, comorbidities, rehabilitation goals, plan of care, etc.). If the patient returns to the IRF in 4 or more consecutive days (that is, it is not considered an interrupted stay), then all of the required documentation must be completed as with any “new” IRF patient. Therefore, IRFs would follow this same guidance for interrupted stays, regardless of the patient's payer.

Comment: A few commenters stated that CMS did not provide enough detail in the proposed rule about how they would account for “certain patient populations.” They used the example of IRFs that treat pediatric patients, and do not believe the IRF-PAI is appropriate for pediatric patients. The commenters expressed concern that these IRFs would be “faced with conducting an inappropriate IRF-PAI on the patient or running the risk of not meeting the data completion threshold.”

Response: We interpret the commenters' concerns to be directed at the standardized patient assessment data elements and Transfer of Health items that will be collected on/after October 1, 2022. Specifically, we interpret the commenters to be concerned that they will not be able to complete these new items because they do not believe the IRF-PAI is appropriate for pediatric patients, and as a result, they will not be able to meet the 95 percent data completion threshold.

We disagree with the commenters who believe the IRF-PAI is inappropriate for persons treated in an IRF who are younger than the usual Medicare FFS or Medicare Advantage patients. CMS believes these items are clinically relevant for younger patients. They were selected based on their overall clinical relevance to PAC providers, including IRFs, their ability to facilitate care coordination during transitions, their ability to capture medical complexity and risk factors, and their scientific reliability and validity. Specific examples include the hearing, speech, and vision items; the Brief Interview for Mental Status (BIMS); the Confusion Assessment Method (CAM) and Patient Health Questionnaires; the Pain interference items; special services, treatments, and interventions; and SDOH. The remainder of this response discusses the appropriateness of each of these item categories in the pediatric populations in more detail.

The intent of the hearing, speech, and vision items is to document the patient's ability to hear (with assistive devices, if they are used), understand, and communicate with others, and the patient's ability to see objects nearby in their environment. Early detection and prompt management are essential for the development of normal language and psychosocial functioning, as well as to identify potentially reversible causes or other underlying problems.^[20] Sensory limitations can lead to confusion in new settings, increase isolation, contribute to mood disorders, and impede accurate assessment of other medical conditions. Failure to appropriately assess, accommodate, and treat these conditions increases the likelihood that younger patients will require more intensive and prolonged treatment. Individualized assessment with accurate screening tools and follow-up evaluations are essential to determining which patients need hearing- or vision-specific medical attention or assistive devices and accommodations, including auxiliary aids and/or services, and to ensure that person-directed care plans are developed to accommodate a patient's needs.

The BIMS was developed to be a brief, objective screening tool, with a focus on learning and memory. As a brief screener, the BIMS is intended to be a relatively quick and easy-to-score assessment that could identify cognitively impaired patients, as well as those who may be at risk for cognitive decline and require further assessment. A number of underlying chronic conditions,^[21] including traumatic brain injury, side effects of medication, metabolic and/or endocrine imbalances,^[22] delirium, and depression,^[23] can affect cognitive function and mental status in pediatric and adolescent IRF patient populations. In alignment with our Meaningful Measures Initiative, accurate assessment of cognitive function and mental status of patients and in PAC is expected to make care safer by reducing harm caused in the delivery of care; promote effective prevention and treatment of disease; strengthen person and family engagement as partners in their care; and promote effective communication and coordination of care.^[24] For example, standardized assessment of cognitive function and mental status of younger patients in PAC will support establishing a baseline for identifying changes in cognitive function and mental status (for example, an adverse drug reaction), anticipating the patient's ability to understand and participate in treatments during a PAC stay, ensuring patient safety (for example, risk of falls), and identifying appropriate support needs at the time of discharge or transfer. We also acknowledge that further cognitive tests may be required based on a patient's age and conditions.

Likewise, the CAM and Patient Health Questionnaire-2 to 9 (PHQ-2 to 9) have value as universal assessments to identify patients in need of further clinical evaluation. The prevalence of depression is increasing among youth in the United States. The 2005 to 2014 National Surveys on Drug Use and Health, which included 172,495 adolescents 12 to 17 years of age, found that the percentage of adolescents who experienced one or more major depressive episodes in the previous 12 months increased from 9 percent in 2005 to 11 percent in 2014.^[25] In 2020, an estimated 4.1 million or 17.0 percent of the U.S. population aged 12 to 17 had at least one major depressive episode, and 2.9 million of these had at least one major depressive episode with severe impairment. The prevalence was highest among adolescents reporting two or more races (29.9%). However, among adolescents with a major depressive episode with severe impairment, only about 46.9 percent received treatment.^[26] Treatment rates have changed little since 2005, raising concern that adolescents are not receiving needed care for depression.^[27] The PHQ-2 mood interview focuses on the two cardinal symptoms of depression, and the longer PHQ-9 mood interview assesses presence and frequency of nine signs and symptoms of depression. A study of the PHQ-9 for detecting major depression among adolescents found it to be an effective choice for providers.^[28] Assessments of depression help PAC providers better understand the needs of their pediatric and adolescent patients by: prompting further evaluation after establishing a diagnosis of depression; elucidating the patient's readiness and/or ability to participate in therapies for conditions other than depression during their stay; and identifying appropriate ongoing treatment and support needs at the time of discharge.

Pain interference items (Pain Effect on Sleep, Pain Interference with Therapy Activities, and Pain Interference with Day-to-Day Activities) are also appropriate for younger patients. Pain is not a surprising symptom in PAC patients and residents, where healing, recovery, and rehabilitation often require regaining mobility and other functions after an acute event. However, in the pediatric population, pain is frequently under-recognized and inadequately treated.^[29 30] In acknowledgement of the opioid crisis, these items were carefully considered, and stakeholder comment was specifically sought prior to adopting these items in light of those concerns. Opioids are frequently prescribed to children and adolescents after surgery or major injury. Children are not immune to opioid use disorders,^[31] and prescription opioid misuse is associated with high-risk behavior in youth, so it is important for healthcare personnel caring for children to recognize these risks and maximize nonopioid regimens, in addition to educating families.^[32] In pain management, a critical part of providing comprehensive care is performance of a thorough initial evaluation, including assessment of both the medical and any biopsychosocial factors causing or contributing to the pain, with a treatment plan to address the causes of pain and to manage pain that persists over time. Using a standardized assessment of pain interference with sleep, function, and activities of daily living (ADLs) is an important first step toward appropriate pain management in PAC settings for patients of all ages.

Other items collected on the IRF-PAI version 4.0 include special services, treatments, and interventions performed in the IRF. Individually or collectively, these items can have a major effect on an individual's health status, self-image, and quality of life. The assessment of these special services, treatments, and interventions in IRFs is important to ensure the continuing appropriateness of care for the pediatric or adolescent patients receiving them, and to support care transitions from one PAC provider to another, to an acute care hospital, or to discharge. For example, standardized assessment of special services, treatments, and interventions used in the IRF can promote the pediatric or adolescent patient's safety through appropriate care planning (for example, mitigating risks such as infection or pulmonary embolism associated with central intravenous access), and identifying life-sustaining treatments that must be continued, such as mechanical ventilation, dialysis, suctioning, and chemotherapy, at the time of discharge or transfer.

Social determinants of health affect nearly everyone in one way or another, and have a major impact on people's health, well-being, and quality of life.^[33] These seven items (race, ethnicity, preferred language, interpreter services, health literacy, transportation, and social isolation) were finalized for collection under our authority under section 2(d)(2)(B) of the IMPACT Act, as well as section 1899B(b)(1)(B)(vi) of the Act. We maintain that these data elements will inform provider understanding of individual patient risk factors and treatment preferences, facilitate coordinated care and care planning, and improve patient outcomes. Adolescents and young adults are not immune to health disparities.^[34 35] As stated in section X.F.2.b. of the proposed rule, we believe that data reporting on standardized patient assessment data elements using the IRF-PAI should include all IRF patients (including pediatric and adolescent patients) for the same reasons we believe that collecting data on Medicare beneficiaries for the IRF QRP's quality measures is important: To achieve equity in healthcare outcomes for our beneficiaries by supporting providers in quality improvement activities, enabling them to make more informed decisions, and promoting provider accountability for healthcare disparities.^[36 37]

For each of the items, the IRF-PAI guidance manual provides instructions for how to code the items if the item does not apply to the patient or the patient 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.

Comment: Several commenters noted that CMS did not provide information on how the data collected under this policy would be used. They stated CMS would need to carefully consider how any data from non-Medicare sources is publicly reported on Care Compare, since commercial coverage policies are different and may limit patient access to IRF services. The commenters stressed the importance of appropriately risk-adjusting for those differences. These commenters urged CMS to engage stakeholders in developing these risk adjustment methods. One commenter supported having more aggregate representative data for the Care Compare website, since they believe it will more accurately reflect the work IRFs provide. One commenter provided several suggestions such as providing confidential results to IRFs and stratifying results by payer class.

Response: We interpret the commenters to be referring to how the data collected would be used for public reporting and specifically those activities associated with public reporting, such as risk adjustment for publicly reported measures and the confidential facility-level quality measure reports IRFs receive prior to publishing results on Care Compare. We clarify for commenters that CMS did not make any proposals for policies related to publicly reporting IRF QRP data collected on non-Medicare patients. To the extent that CMS is interested in such policies in the future, these policies would be proposed as part of future notice and comment rulemaking.

Comment: Two commenters disagreed with our estimated cost of implementing a policy to collect IRF QRP data on all patients regardless of payer. One commenter said that the expected additional 237 IRF-PAI assessments per year was a significant underestimation for larger urban IRFs. Another commenter believes CMS excluded several healthcare personnel who are contributors to the IRF-PAI collection in addition to disregarding crucial administrative complexities associated with IRF-PAI submission, which in turn underestimated the overall cost and burden. This commenter questioned how CMS arrived at its estimate and concluded that CMS may have based its estimate on the current version of the IRF-PAI since the personnel types we included in the burden estimate were Registered Nurses, Licensed Vocational Nurses, Respiratory Therapists, Speech and Language Pathologists, Occupational Therapists, Physical Therapists, and Psychologists. This commenter stated that they believe CMS should have included pharmacists and physicians in its cost estimate in addition to increasing the percentage of time physical therapists (PTs) and occupational therapists (OTs) are involved in the process. They state that PTs and OTs are substantially more involved in both the clinical process and as PPS coordinators than is reflected in CMS' burden estimate. This commenter described a two-stage process to completing the IRF-PAI that includes: (1) clinicians providing services and documenting the relevant data; and (2) the PPS coordinator compiling, verifying, and clarifying the data in preparation for submission. They point out that the PPS coordinator may spend the entire 1.8 hours completing the IRF-PAI, but that does not take into account the assessment of the patient and the interdisciplinary communication that goes on in the weekly interdisciplinary team conferences.

Response: We disagree with the commenters about our burden estimate. We acknowledge that some IRFs will incur a higher cost than was estimated due to their size and volume of admissions. We also acknowledge that some IRFs will incur a lower cost. We do agree that the additional cost will be dependent on the IRF's current volume of non-Medicare and non-Medicare Advantage patients.

We also want to point out that the estimated burden included in section XI.B. of the FY 2023 IRF PPS proposed rule reflects the estimated burden associated with collecting the IRF-PAI data on patients associated with this proposal: that is, expanding data collection from Medicare FFS and Medicare Advantage patients to all patients receiving IRF services, regardless of payer. It was not an estimate of burden associated with the transition from the IRF-PAI version 3.0 to the IRF-PAI version 4.0 (that is, the collection of new data elements) since this burden was accounted for in the FY 2020 IRF PPS proposed and final rules (84 FR 17333 and 84 FR 39166).

The 1.8 hours per IRF-PAI is based on past IRF burden calculations and represents the time it takes to encode the IRF-PAI. As the commenter pointed out in their example, after the patient assessment is completed, the IRF-PAI is coded with the information and submitted to iQIES, and it is these steps (after the patient assessment) that the estimated burden and cost captures. Finally, as we stated in section XI.B. of the proposed rule, our assumptions for staff type were based on the categories generally necessary to perform an assessment, and subsequently encode it, which is consistent with past collection of information estimates.^[38] While we acknowledge that some IRFs may use PTs and OTs more than others, our estimates are based on the categories of personnel necessary to complete the IRF-PAI.

Comment: A few commenters opposed the proposal because they stated that CMS did not provide information in the proposal to address their concerns raised in previous years. Specifically, they stated it was not reasonable to compare IRFs and LTCHs since expanding data collection for non-Medicare patients is a significantly larger undertaking for IRFs due to the fact that the volume of assessments is much higher in IRFs than LTCHs. Commenters also disagreed with the comparison to Hospices since their assessment is smaller than the current version of the IRF-PAI. One commenter called the proposal an “unfunded mandate” while another referred to it as “regulatory overreach.”

Response: We clarify that when CMS referred to the LTCH and Hospice QRP programs in the proposed rule, we were not implying that the volume of assessments would be similar. We acknowledge that there are more IRFs than LTCHs in the U.S. and that an IRF generally has a higher number of patients than an LTCH. It is also true that Hospices have a higher number of patient stays annually than IRFs (in 2020, more than 1.7 million Medicare beneficiaries received hospice services compared to 379,000 IRF stays).^[39] The intent in referring to the LTCH QRP was to provide an example of a CMS program that currently collects QRP data on all patients, regardless of payer.

As we have stated before, we appreciate that collecting quality data on all patients regardless of payer may create additional burden. We also note that this burden may be partially offset by eliminating the effort to separate out Medicare beneficiaries from other patients, which is also burdensome. Moreover, section 2(d)(2)(B) of the IMPACT Act requires the Secretary to collect or otherwise obtain access to the data necessary to carry out the provisions of paragraph (2) of section 2(d) of the IMPACT Act through both new and existing data sources. Accessing standardized data relating to the standardized data elements on a national level is necessary to permit CMS to conduct periodic analyses; to assess appropriate adjustments to quality measures, resource use measures, and other measures; and to assess and implement appropriate adjustments to Medicare payments based on those measures. Collecting the data as proposed will provide the basis for our periodic analyses of the relationship between an individual's health status and other factors and quality, resource use, and other measures, as required by section 2(d)(2) of the IMPACT Act, and to assess appropriate adjustments.

Comment: Two commenters raised concerns that if finalized, the proposal to collect IRF QRP data on all patients, regardless of payer, would take time away from the patient care process. One of these commenters opposes the collection of patient data from patients who have no connection to the Medicare program.

Response: We disagree that this policy, if finalized, would take time away from patient care. The items collected on the IRF-PAI, including vision, hearing, cognition, pain interference, functional status, and special services, are all important pieces of information to developing and administering a comprehensive plan of care. Rather than taking time away from patient care, providers will be documenting information they are likely already collecting through the course of providing care to the patients. We received support from IRFs to our RFI in the FY 2018 IRF PPS proposed rule, as well as our proposal in the FY 2020 IRF PPS proposed rule (the FY 2020 proposal was not subsequently finalized). Many commenters at that time and in response to this proposal indicated they are already collecting IRF-PAI data on all patients, regardless of payer. Other commenters have told us that they already collect many of the SDOH items included within the IRF-PAI version 4.0. The Transfer of Health Information items represent processes IRFs are likely already doing, since freestanding IRFs or IRF units within larger hospitals that participate in Medicare must arrange for a patient's discharge plan which likely includes providing a legible, complete, reconciled medication list in order to be in compliance with hospital Conditions of Participation at § 482.43.

We also disagree that the data collected under this proposal would have no connection to the Medicare program. As we stated in the proposed rule, expanding the collection of data to all patients, regardless of payer, would ensure that CMS has full and complete data in order to assess the relative quality of care provided by IRFs to all patients, and to better evaluate the quality of care received by Medicare patients, including whether disparities appear to exist. We believe collecting such quality data on all patients in the IRF setting would provide the most robust and accurate representation of quality in the IRFs.

Comment: One commenter stated that the proposal provides no benefit to patient care and instead would create different patient populations for claims-based measures and assessment-based measures, creating more confusion in the data publicly reported.

Response: We acknowledge that claims-based measures and assessment-based measures would have different patient populations represented by the measure denominators. However, currently that issue exists because IRF claims-based measures only reflect Medicare FFS patients while IRF assessment-based measures reflect Medicare FFS and Medicare Advantage patients. We believe that if this proposal is finalized, it will make the assessment-based measures more robust and represent the IRF population as a whole, rather than limiting it to only those patients with Medicare FFS or Medicare Advantage benefits. CMS did not make any proposals for policies related to publicly reporting IRF QRP data collected on non-Medicare patients. To the extent that CMS is interested in such policies in the future, these policies would be proposed as a part of future notice and comment rulemaking.

Comment: One commenter opposes the collection of data on all patients, regardless of payer, because not all the information required by CMS is utilized for the IRF QRP quality measures and/or public reporting. Another commenter referred to a MedPAC report that indicated Medicare FFS patients represent 54 percent of IRF discharges. This commenter stated that if you factor in Medicare Advantage patients, it would increase the total percentage of their patient population and mean that “many IRFs are already submitting IRF-PAIs on most of their patients.” They also point out that in IRFs that have very similar section GG functional assessment average numeric change from admission to discharge in their Medicare and non-Medicare patients, there is no value in submitting non-Medicare patients' IRF-PAIs to Medicare. Instead, they suggest requiring only the items on the IRF-PAI that are required to generate a case mix group (CMG), length of stay, discharge destination, and GG change to be calculated.

Response: The IRF QRP requires the collection of certain standardized patient assessment data elements. These items have gone through extensive research, technical expert review, and public comment. The proposal for collecting the IRF-PAI data on all patients, regardless of payer, is specific to the data elements specified for the QRP and can be found on the IRF QRP Measures Information web page at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​IRF-Quality-Reporting/​IRF-Quality-Reporting-Program-Measures-Information.

With regard to the comment about how most IRFs are already submitting IRF-PAI assessments on most of their patients or that if an IRF has similar section GG functional assessment average numeric change scores in their Medicare and non-Medicare patients, then there is no value in the proposal, CMS disagrees. The functional outcome measures calculated using section GG are not the only IRF QRP assessment-based measures. There are 10 measures in total, and they reflect a number of quality-of-care areas, such as skin integrity, major falls, medication reconciliation, and Transfer of Health information.

Additionally, MedPAC is tasked with reporting to Congress on the payment adequacy of Medicare's FFS payment system, the Medicare Advantage program, and the Medicare prescription drug program. While their numbers reflect average IRF payer penetration, they do not represent all IRFs' payer penetration.

Comment: Some commenters were concerned about CMS' timeline for collecting data on all IRF patients. Two commenters noted that starting in FY 2025 is too soon because collection would begin one year following the implementation of the IRF-PAI version 4.0, which increases data collection by over 100 data points and begins October 1, 2022. While other commenters noted that their members already complete an IRF-PAI on all their patients, and will likely continue to do so, they point to the increased length and number of items in the IRF-PAI version 4.0. As such, these commenters requested that CMS delay expanding reporting requirements for the IRF-PAI to all patients to October 1, 2024 so that IRFs would have time to develop a clearer understanding of the time commitment for collecting the new items. These commenters noted it would give them additional time for training and development of operational policies and procedures in order to ensure compliance with QRP reporting.

Response: We interpret the comments referring to “over 100 data points” to be referring to the number of possible response options available for the 21 new data elements that have been added to the IRF-PAI version 4.0. While it is true that there are approximately 106 response options for these 21 new data elements, we want to note that three of the new items have a response option (“None of the above”) IRFs can select for patients 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 IRFs do not have to complete them. Additionally, we do not believe the vast majority of IRFs would have an issue meeting the reporting requirements. For example, in FY 2016, CMS added 58 new data elements with a possible 109 data points for the FY 2018 QRP, and for the FY 2018 program year, less than 2 percent of IRFs did not meet the compliance threshold for the annual increase factor (AIF).

IRFs have had exposure to many of these items since CMS first introduced them in the FY 2018 IRF proposed rule. At that time, CMS did not finalize the majority of the standardized patient assessment data element proposals in recognition of the concern raised by many commenters that we were moving too fast to adopt the data elements. Since then, 4 additional years have passed and CMS has provided a number of educational resources and training materials for IRFs to take advantage of, reducing the burden to IRFs in creating their own training resources. Additionally, CMS recognizes that the effort of having to separate out Medicare beneficiaries from other patients has clinical and work flow implications that introduce burden, and collecting data on all patients admitted would remove the burden of having to verify the patient's payer's requirements before beginning IRF-PAI collection. Data collection could begin immediately upon admission without delay. The IRF QRP Helpdesk is also available to providers and has been fielding questions about these new items since November 2021 when the revised compliance date for the IRF-PAI version 4.0 was finalized.

Additionally, CMS has several reports available to providers to monitor their compliance with the QRP reporting requirements during the year. These reports are available within iQIES to providers, including the IRF-Final Validation Report (FVR) and the Provider Threshold Report (PTR). The IRF FVR is automatically generated in iQIES within 24 hours of the submission of a file and placed in the provider's My Reports folder. The FVR provides detailed information about the status of submission files, including warnings and fatal errors encountered. The PTR allows providers to monitor their compliance status regarding the required data submission for the IRF QRP measures for the current Annual Increase Factor (AIF). It is a user-requested and on-demand report, meaning that it can be pulled anytime by the IRF.

Although we disagree with the specific concerns raised by these commenters pertaining the implementation of the IRF-PAI version 4.0, we note that as part of this final rule, CMS is updating the proposed requirement for the collection of IRF-PAI assessment data on each patient receiving care in an IRF, regardless of payer, to begin with the FY 2026 IRF QRP, in order to provide additional time for IRFs to prepare for the new requirement. Consequently, IRFs will be required to collect and report IRF-PAI assessment data with respect to admission and discharge for all patients, regardless of payer, discharged on or after October 1, 2024.

Comment: Several commenters disagreed with implementing the proposal for FY 2025 because they noted the landscape for IRF providers is vastly different than in 2020 when the proposal was last made. The commenters were not specific about what is meant by a “changing landscape,” but we interpret this as being in reference to their later comments about how the lingering impacts of the COVID-19 pandemic, particularly with respect to nurse staffing, and they noted that they do not believe these issues will be resolved by October 1, 2023. A few commenters cited a report by the HHS Assistant Secretary for Planning and Evaluation (ASPE) finding that “healthcare workforce shortages will continue to persist and significantly worsen by 2030.”

Response: We believe the commenters are referring to the ASPE Issue Brief (HP-2022-13, May 3, 2022), titled Impact of the COVID-19 Pandemic on the Hospital and Outpatient Clinician Workforce .^[40] This report describes the workforce shortages tied to COVID-19 surges. However, the report also details how the pandemic-related disruptions and workforce shortages have taken place within the context of significant pre-pandemic shortages in some geographic areas, many of which have been exacerbated by the uneven and extended duration of the pandemic. The report goes on to say that shortages and maldistribution of healthcare workers were a major concern even before the pandemic. The analysis we believe the commenters are referring to was done in 2016, 4 years prior to the start of the COVID-19 pandemic.^[41] While relevant, we understand that healthcare staffing has been a longstanding challenge, and may take time to resolve.

Although CMS believes it will help IRFs, physicians, and other practitioners caring for patients in IRFs better prepare for the complex and resource-intensive care needs of patients, which is an important consideration in preparing for emerging infectious diseases, we note that as part of this final rule CMS is updating the proposed requirement for the collection of IRF-PAI assessment on each patient receiving care in an IRF, regardless of payer to begin with the FY 2026 IRF QRP, in order to provide additional time for IRFs to prepare for the new requirement.

Comment: A few commenters stated that IRFs are facing increased costs to procure supplies and retain staff, and yet the data would not be included in payment updates for IRFs despite the increased resource use IRFs will have in conducting the additional data collection. One commenter stated the increased cost would be easier to absorb once the pandemic is truly endemic.

Response: We acknowledge that IRFs may continue to be impacted by the PHE and that collecting quality data on all patients regardless of payer may create additional burden for some IRFs. As noted earlier, we received several comments from providers and provider organizations stating that they are currently collecting IRF-PAI data on all patients, regardless of payer. As we described in section XI.F.2.b. of the proposed rule, reporting standardized patient assessment data elements using the IRF-PAI on all IRF patients is important now in order to better understand the impact of the PHE on our healthcare system. It will give IRFs the opportunity to analyze their quality of care across and between patient populations so that opportunities to achieve equity in healthcare outcomes might be more easily recognized, promoting provider accountability.^{[42]  [43]} The significance of the information (including, but not limited to health literacy, transportation, race, ethnicity, social isolation, high-risk medications) will assist IRFs in supporting patients as they make health decisions. Although we believe the benefit of having this information available in a standardized format outweighs the potential burden of collecting this data, we acknowledge the commenters' concerns. We note that as part of this final rule CMS is updating the proposed requirement for the collection of IRF-PAI assessment on each patient receiving care in an IRF, regardless of payer to begin with the FY 2026 IRF QRP, in order to provide additional time for IRFs to prepare for the new requirement.

Comment: One commenter opposes the proposal to collect IRF QRP information on all patients regardless of payer because they are concerned that Medicare Administrative Contractors (MACs) may inappropriately access PAI information without authority to do so. They state MACs are only allowed to access the IRF-PAI data submitted for Medicare and Medicare Advantage patients for purposes of Medicare claim reviews and IRF 60 percent rule compliance determinations. They stated that MACs have at times incorrectly reviewed IRF-PAI data for non-Medicare patients when conducting these reviews. They are concerned that even though CMS says it takes the privacy and security of PHI seriously, and that CMS systems conform to applicable Federal laws and standards to ensure information security, it does not change the fact that “thousands” of non-Medicare IRF patients will not be notified or able to provide consent for transmission of their sensitive personal health information to CMS. They also raise concerns about the security of that information when accessed by other agencies or researchers.

Response: CMS has not been made aware of inappropriate use of IRF-PAI data by the MACs. If an IRF is aware of inappropriate use of IRF-PAI data by MACs, we urge them to contact CMS' Privacy Office at [e-mail].

We also want to point providers to the IRF-PAI guidance manual, specifically Appendix E, which includes a Privacy Act Statement and a Data Collection Information Summary available in both English and Spanish. As explained in these documents,^[44] the authority for data collection is given under section 1886(j)(2)(D) of the Act, which authorizes the Secretary to collect the data necessary to establish and administer the IRF PPS, and to help evaluate whether the IRF meets quality standards and gives appropriate healthcare to its patients. Also, as noted in these documents, the IRF-PAI must be used to assess every Medicare Part A FFS and Part C (Medicare Advantage) inpatient, and it may be used to assess other types of inpatients. These documents are intended to give patients notice of a data collection as required by section 552a(e)(3) of the Privacy Act of 1974, and serve as resources for IRF providers to provide to all patients upon admission to the IRF to notify them of their privacy rights as well as the authority for the data collection under the statute.

In response to the concern about the security of the information when accessed by other agencies or researchers, CMS has stringent policies and safeguards in place for the use of any data CMS has collected. CMS safeguards the IRF-PAI data in a data system. The system limits data access to authorized users and monitors such users to ensure against unauthorized data access or disclosures. This system conforms to all applicable Federal laws and regulations as well as Federal government, HHS, and CMS policies and standards as they relate to information security and data privacy. The applicable laws and regulations include, but are not limited to: the Privacy Act of 1974; the Federal Information Security Management Act of 2002; the Computer Fraud and Abuse Act of 1986; the Health Insurance Portability and Accountability Act of 1996; the E-Government Act of 2002; the Clinger-Cohen Act of 1996; the Medicare Modernization Act of 2003; and the corresponding implementing regulations. Prior to receiving data under one of the routine uses specified in the System of Records Notice (SORN) (09-70-0521), each prospective recipient must agree in writing to ensure the continuing confidentiality and security of the information. Furthermore, disclosures of PHI authorized by these routine uses may be made only if, and as, permitted or required by the “Standards for Privacy of Individually Identifiable Health Information” (45 CFR parts 160 and 164, which are commonly referred to as the “HIPAA Privacy Rule”). These same policies and safeguards would exist for information collected under this proposal. Additionally, we would also remind stakeholders that the CDC NHSN data are already collected on all patients regardless of payer and these data are currently safeguarded under the privacy standards previously noted.

Comment: Two commenters opposed the proposal because they believe that patients who are not on government-sponsored healthcare plans should not be required to report these data and IRFs should not be required to collect and submit them. One commenter questioned whether non-government patients will have the opportunity to opt out of reporting and if they did, what implications it would have on penalties for non-compliance. Another commenter challenged CMS statutory authority to require IRFs to submit the data, stating they believe CMS' proposal violates the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, the Privacy Act of 1974 (5 U.S.C. 552a), the privacy provisions of the E-Government Act of 2002, and potentially 35 State privacy laws that are more stringent than HIPAA and other Federal laws and which may prohibit IRFs from disclosing non-Medicare patient health information via the IRF-PAI to CMS.

Response: We appreciate the commenters' concerns but disagree that this proposal is a violation of HIPAA, the Privacy Act of 1974, and the E-Government Act of 2002. IRF-PAI data are collected under an existing SORN, 09-70-0521 (66 FR 56682). Any disclosure of the data will be made in accordance with the Privacy Act and those routine uses outlined in the SORN. Medicare patients are currently given a Privacy Act Statement and therefore one would be given to every patient under the IRF QRP. Section 208 of the E-Government Act of 2002 requires Federal agencies to perform Privacy Impact Assessments when acquiring or developing new information technology or making substantial changes to existing information technology that involves the collection, maintenance, or dissemination of information in identifiable form. Because we are not acquiring or developing new information technology, or making substantial changes to existing information technology under this proposal, we disagree that this policy violates the E-Government Act. Additionally, the IRF final rule is required for the implementation of a Federal program within CMS' authority. As such, CMS attests to compliance with all Federal laws, but is not held to State law requirements regarding this collection.

With regard to questions about how CMS would keep non-Medicare data secure, we safeguard the IRF-PAI data in a secure data system. The system limits data access to authorized users and monitors such users to ensure against unauthorized data access or disclosures. This system conforms to all applicable Federal laws and regulations, as well as Federal government, HHS, and CMS policies and standards as they relate to information security and data privacy. The applicable laws and regulations include, but are not limited to: the Privacy Act of 1974; the Federal Information Security Management Act of 2002; the Computer Fraud and Abuse Act of 1986; the Health Insurance Portability and Accountability Act of 1996; the E-Government Act of 2002; the Clinger-Cohen Act of 1996; the Medicare Modernization Act of 2003; and the corresponding implementing regulations. With regard to the scope of data collection, IRFs would be required to submit quality measure and standardized patient assessment data elements required by the IRF QRP.

We believe that the maturation of the IRF QRP and the modernized use of the IRF-PAI instrument by IRFs argue for the collection of IRF-PAI data on all patients, regardless of payer. Specifically, we believe there is a rationale and agency precedent (in the other reporting programs, such as LTCH, Hospice, and MIPS) for moving forward with the collection of assessment data for the purposes of the IRF QRP. It will improve the IRF QRP's ability to assess IRF quality and allow the IRF to foster better-quality care for patients regardless of the payer source. It will also support CMS' ability to compare standardized outcome measures across PAC settings.

Final Decision: After considering the public comments received, for the reasons discussed above and in the FY 2023 IRF PPS proposed rule (87 FR 20254), we are finalizing our proposal to begin collection of IRF-PAI assessment on each patient receiving care in an IRF, regardless of payer. In the proposed rule, we proposed that this collection would begin with the FY 2025 IRF QRP, meaning that IRFs would be required to report these data with respect to admission and discharge of all patients, regardless of payer, discharged between October 1, 2023 and December 31, 2023. However, upon consideration of the public comments received on this issue, and for the reasons discussed above, CMS is finalizing this policy in this final rule to begin with the FY 2026 IRF QRP in order to give IRFs more time to prepare for the new data collection. IRFs will be required to report these data with respect to admission and discharge for all patients, regardless of payer, discharged between October 1, 2024 and December 31, 2024. These data will be used (in addition to the data collected January 1, 2024 through September 30, 2024) to calculate an IRF's data completion threshold for the FY 2026 IRF QRP.

As noted in the proposed rule, we will revise the IRF-PAI in order for IRFs to submit data pursuant to the finalized policy. A new item will replace the current item identifying payment source on the IRF-PAI admission assessment to collect additional payer(s) information. The collection of this item will align with the LTCH setting. A draft IRF PAI containing this new item will be available at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​IRF-Quality-Reporting. We will notify stakeholders when the draft IRF PAI is available.

3. Revisions to the Regulation Text To Require IRFs To Submit Patient Assessments on All Patients Beginning With the FY 2026 IRF QRP

As discussed in section XI.F.2. of the proposed rule, we proposed to require that the IRF-PAI assessment be collected on each patient receiving care in an IRF, regardless of payer. Therefore, we also proposed, subject to the aforementioned proposal becoming final, to revise the regulation text in §§ 412.604, 412.606, 412.610, 412.614, and 412.618 so that the requirements that IRFs must currently satisfy with respect to collection and submission of IRF-PAI data for Medicare Part A and Medicare Part C patients would also apply to data on all other IRF patients, regardless of payer.

In addition, we note that CMS' regulations at § 412.610(f) currently require IRFs to maintain all PAIs completed on Medicare Part A FFS patients within the previous 5 years and Medicare Part C (Medicare Advantage) patients within the previous 10 years either in a paper format in the patient's clinical record or in an electronic computer file format that the IRF can easily obtain and produce upon request to CMS or its contractors. Subject to the aforementioned all-payer proposal becoming final, we also proposed to revise the regulation text at § 410.610(f) to require that IRFs maintain PAIs completed on patients receiving care under all other payer sources (that is, other than Medicare Part A and Medicare Part C) for 5 years. We proposed a 5-year period for the same reasons we proposed a 5-year requirement for Medicare Part A patients in the original Medicare Program; Prospective Payment System for Inpatient Rehabilitation Facilities final rule that appeared in the August 7, 2001 Federal Register (66 FR 41329). Specifically, the assessments may be needed as part of a retrospective review conducted at the IRF for various purposes, including the fact that the completed patient assessments could be beneficial to other entities that appropriately have access to these records (for example, a State or Federal agency conducting an investigation due to a complaint of patient abuse).

The proposed revisions are outlined in §§ 412.604, 412.606, 412.610, 412.614, and 412.618 in the regulation text of the proposed rule. We invited public comments on this proposal.

We did not receive any comments on the proposed revisions to the regulation text in §§ 412.604, 412.606, 412.610, 412.614, and 412.618 so that the requirements that IRFs must currently satisfy with respect to collection and submission of IRF-PAI data for Medicare Part A and Medicare Part C patients would also apply to data on all other IRF patients, regardless of payer. Therefore, we are finalizing these revisions as proposed, with three exceptions. Specifically, we are updating the proposed regulation text at §§ 412.604(c), 412.606(a)(1), and 412.606(b)(1) to reflect that the facilities will need to start collecting the IRF-PAI assessment data for each patient receiving care in an IRF, regardless of payer, beginning on October 1, 2024, rather than October 1, 2023 as originally proposed.

4. Revisions to § 412.614(d)(2) To Correct an Error to the Regulatory Text

In accordance with the Administrative Procedure Act, 5 U.S.C. 553, it is the Secretary's practice to offer interested parties the opportunity to comment on proposed regulations.

However, the regulatory changes in this proposal are necessary to correct an error and do not establish any new substantive rules.

We proposed to revise the regulatory text at § 412.614(d)(2) to correct a reference to another part of the regulations. Specifically, we proposed to replace a reference to § 412.23(b)(2) with the correct reference to § 412.29(b)(1). The proposed revisions were outlined in the regulation text of the proposed rule.

We invited public comments on this proposal.

We did not receive any comments on the proposed revision to the regulatory text at § 412.614(d)(2) to correct a reference to another part of the regulations and therefore, we are finalizing the revisions as proposed. These changes will be effective with the FY 2026 IRF QRP.

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

We did not propose any new policies regarding the public display of measure data.

XII. Provisions of the Final Regulations

In this final rule, we are adopting the provisions set forth in the FY 2023 IRF PPS proposed rule (87 FR 20218), specifically:

• We will update the CMG relative weights and average length of stay values for FY 2022, in a budget neutral manner, as discussed in section V. of this final rule.
• We will update the IRF PPS payment rates for FY 2023 by the market basket increase factor, based upon the most current data available, with a productivity adjustment required by section 1886(j)(3)(C)(ii)(I) of the Act, as described in section VI. of this final rule.
• We will adopt a permanent cap policy in order to smooth the impact of year-to-year changes in IRF payments related to certain changes to the IRF wage index, as discussed in section VI. of this final rule.
• We will update the FY 2023 IRF PPS payment rates by the FY 2023 wage index and the labor-related share in a budget-neutral manner, as discussed in section VI. of this final rule.
• We will calculate the calculation of the IRF standard payment conversion factor for FY 2023, as discussed in section VI. of this final rule.
• We will update the outlier threshold amount for FY 2023, as discussed in section VII. of this final rule.
• We will update the cost-to-charge ratio (CCR) ceiling and urban/rural average CCRs for FY 2023, as discussed in section VII. of this final rule.
• We will codify CMS' existing teaching status adjustment policy and clarify and update the IRF teaching status adjustment policy with respect to IRF hospital closures and displaced residents, as discussed in section VIII. of this final rule.

We are also adopting updates to the IRF QRP in section XI. of this final rule as follows:

• Update data reporting requirements under the IRF QRP beginning with FY 2026.

XIII. Collection of Information Requirements

A. Statutory Requirement for Solicitation of Comments

Under the Paperwork Reduction Act of 1995, 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. In order to fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the Paperwork Reduction Act of 1995 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.

This final rule refers to associated information collections that are not discussed in the regulation text contained in this document.

B. Collection of Information Requirements for Updates Related to the IRF QRP Beginning With the FY 2026 IRF QRP

An IRF that does not meet the requirements of the IRF QRP for a fiscal year will receive a 2-percentage point reduction to its otherwise applicable annual increase factor for that fiscal year.

We believe that the burden associated with the IRF QRP is the time and effort associated with complying with the requirements of the IRF QRP. In section X.F.2. of the proposed rule, we proposed to update the data reporting requirements for the IRF QRP beginning with the FY 2025 IRF QRP. We proposed to require IRFs to collect IRF-PAI assessment information on each patient receiving care in an IRF, regardless of payer. We believe the IRF-PAI items are completed by Registered Nurses (RN), Licensed Practical and Licensed Vocational Nurses (LVN), Respiratory Therapists (RT), Speech-Language Pathologists (SLP), Occupational Therapists (OT), Physical Therapists (PT), and/or Psychologists (Psy), depending on the item. We identified the staff type per item based on past IRF burden calculations in conjunction with expert opinion. Our assumptions for staff type were based on the categories generally necessary to perform an assessment. Individual providers determine the staffing resources necessary; therefore, we averaged the national average for these labor types and established a composite cost estimate. This composite estimate was calculated by weighting each salary based on the following breakdown regarding provider types most likely to collect this data: RN 50 percent; LVN 31.7 percent; RT 7 percent; SLP 6 percent; PT 2.5 percent; OT 2.5 percent; Psy 2 percent. For the purposes of calculating the costs associated with the collection of information requirements, we obtained mean hourly wages for these staff from the U.S. Bureau of Labor Statistics' May 2020 National Occupational Employment and Wage Estimates.^[45] To account for overhead and fringe benefits, we have doubled the hourly wage. These amounts are detailed in Table 13.

As a result of the proposal, the estimated burden and cost for IRFs for complying with requirements of the FY 2026 IRF QRP will increase. Specifically, we believe that there will be a 1.8 hours addition in clinical staff time to report data for each additional IRF-PAI completed. We estimated the collection of an additional 263,988 IRF-PAIs from 1,115 IRFs annually. This equated to an increase of 475,178 hours in burden for all IRFs (1.8 hours × 263,988 discharges). Given the clinician times estimated in the previous paragraph and the wages in Table 13, we calculated a blended hourly rate of $66.82. We estimated that each IRF will complete an average of 237 additional IRF-PAIs per year, the total cost related to the additional reporting requirements is estimated at $28,505.41 per IRF annually [(237 assessment × 1.8 hours) × $66.82], or $31,783,532.15 for all IRFs annually ($28.505.41 × 1,115). The increase in burden will be accounted for in a revised information collection request under OMB control number (0938-0842). The required 60-day and 30-day notices will publish in the Federal Register and the comment periods will be separate from those associated with this rulemaking. A 60-day Federal Register notice was published on February 3, 2022 (87 FR 6175) to extend the information collection request (ICR). The 60-day comment period for the extension ended April 4, 2022. The 30-day Federal Register notices published on April 12, 2022 (87 FR 21661) and the ICR is pending at OMB. The revision ICR will be submitted at the conclusion of the extension process.

As described in section X.F.2.c. of the proposed rule, a new item would replace Item 20 on the IRF-PAI V4.0. However, since this item is replacing another item already accounted for in the PRA, we do not believe this would add any additional burden to the estimate described above.

We invited public comments on these potential information collection requirements. We responded to these comments in section XI.F.2. of this final rule. However, for the reasons discussed in section XI.F.2., CMS is finalizing this policy to begin with the FY 2026 IRF QRP in order to give IRFs more time to prepare for the new data collection. IRFs will be required to report these data with respect to admission and discharge for all patients, regardless of payer, discharged between October 1, 2024 and December 31, 2024. These data will be used (in addition to the data collected January 1, 2024 through September 30, 2024) to calculate an IRF's data completion threshold for the FY 2026 IRF QRP.

XIV. Regulatory Impact Analysis

A. Statement of Need

This final rule updates the IRF prospective payment rates for FY 2023 as required under section 1886(j)(3)(C) of the Act and in accordance with section 1886(j)(5) of the Act, which requires the Secretary to publish in the Federal Register on or before August 1 before each FY, the classification and weighting factors for CMGs used under the IRF PPS for such FY and a description of the methodology and data used in computing the prospective payment rates under the IRF PPS for that FY. This final rule also implements section 1886(j)(3)(C) of the Act, which requires the Secretary to apply a productivity adjustment to the market basket increase factor for FY 2012 and subsequent years.

Furthermore, this final rule also adopts policy changes under the statutory discretion afforded to the Secretary under section 1886(j) of the Act. We are also finalizing updates to the data reporting requirements for the IRF QRP and corresponding amendments to the regulations consistent with these requirements. In addition, we are also finalizing an amendment to correct an error in the regulations text at § 412.614(d)(2).

B. Overall Impact

We have examined the impacts of this 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), the Regulatory Flexibility Act (RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, section 202 of the Unfunded Mandates Reform Act of 1995 (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). 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 $100 million or more in any 1 year, or adversely and materially affecting a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local or tribal governments or communities (also referred to as “economically significant”); (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) raising novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866.

Section (6)(a) of Executive Order 12866 provides that a regulatory impact analysis (RIA) must be prepared for major rules with economically significant effects ($100 million or more in any 1 year). We estimate the total impact of the policy updates described in this final rule by comparing the estimated payments in FY 2023 with those in FY 2022. This analysis results in an estimated $275 million increase for FY 2023 IRF PPS payments. Additionally, we estimate that costs associated with updating the reporting requirements under the IRF QRP result in an estimated $31,783,532.15 additional cost in FY 2026 for IRFs. Based on our estimates OMB's Office of Information and Regulatory Affairs has determined that this rulemaking is “economically significant” as measured by the $100 million threshold. Also, the rule has been reviewed by OMB. Accordingly, we have prepared an RIA that, to the best of our ability, presents the costs and benefits of the rulemaking.

C. Anticipated Effects

1. Effects on IRFs

The RFA requires agencies to analyze options for regulatory relief of small entities, if a rule has a significant impact on a substantial number of small entities. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and small governmental jurisdictions. Most IRFs and most other providers and suppliers are small entities, either by having revenues of $8.0 million to $41.5 million or less in any 1 year depending on industry classification, or by being nonprofit organizations that are not dominant in their markets. (For details, see the Small Business Administration's final rule that set forth size standards for health care industries, at 65 FR 69432 at https://www.sba.gov/​sites/​default/​files/​2019-08/​SBA%20Table%20of%20Size%20Standards_​Effective%20Aug%2019%2C%202019_​Rev.pdf, effective January 1, 2017 and updated on August 19, 2019.) Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IRFs or the proportion of IRFs' revenue that is derived from Medicare payments. Therefore, we assume that all IRFs (an approximate total of 1,118 IRFs, of which approximately 52 percent are nonprofit facilities) are considered small entities and that Medicare payment constitutes the majority of their revenues. HHS generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA. As shown in Table 14, we estimate that the net revenue impact of the final rule on all IRFs is to increase estimated payments by approximately 3.2 percent. The rates and policies set forth in this final rule will not have a significant impact (not greater than 4 percent) on a substantial number of small entities. The estimated impact on small entities is shown in Table 14. MACs are not considered to be small entities. Individuals and States are not included in the definition of a small entity.

In addition, section 1102(b) of the Act requires us to prepare an RIA if a rule may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 604 of the RFA. For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is located outside of a Metropolitan Statistical Area and has fewer than 100 beds. As shown in Table 14, we estimate that the net revenue impact of this final rule on rural IRFs is to increase estimated payments by approximately 3.1 percent based on the data of the 134 rural units and 12 rural hospitals in our database of 1,118 IRFs for which data were available. We estimate an overall impact for rural IRFs in all areas between 0.5 percent and 4.0 percent. As a result, we anticipate that this final rule will not have a significant impact on a substantial number of small entities.

Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-04, enacted on March 22, 1995) (UMRA) also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. In 2022, that threshold is approximately $165 million. This final rule does not mandate any requirements for State, local, or tribal governments, or for the private sector.

Executive Order 13132 establishes certain requirements that an agency must meet when it issues a proposed rule (and subsequent final rule) that imposes substantial direct requirement costs on State and local governments, preempts State law, or otherwise has federalism implications. As stated, this final rule will not have a substantial effect on State and local governments, preempt State law, or otherwise have a federalism implication.

2. Detailed Economic Analysis

This final rule will update the IRF PPS rates contained in the FY 2022 IRF PPS final rule (86 FR 42362). Specifically, this final rule will update the CMG relative weights and ALOS values, the wage index, and the outlier threshold for high-cost cases. This final rule will apply a productivity adjustment to the FY 2023 IRF market basket increase factor in accordance with section 1886(j)(3)(C)(ii)(I) of the Act. Further, this final rule codifies CMS' existing teaching status adjustment policy through proposed amendments to the regulation text and updates and clarifies the IRF teaching policy with respect to IRF hospital closures and displaced residents. Additionally, this final rule will establish a permanent cap policy to smooth the impact of year-to-year changes in IRF payments related to decreases in the IRF wage index.

We estimate that the impact of the changes and updates described in this final rule would be a net estimated increase of $275 million in payments to IRF providers. The impact analysis in Table 14 of this final rule represents the projected effects of the updates to IRF PPS payments for FY 2023 compared with the estimated IRF PPS payments in FY 2022. We determine the effects by estimating payments while holding all other payment variables constant. We use the best data available, but we do not attempt to predict behavioral responses to these changes, and we do not make adjustments for future changes in such variables as number of discharges or case-mix.

We note that certain events may combine to limit the scope or accuracy of our impact analysis, because such an analysis is future-oriented and, thus, susceptible to forecasting errors because of other changes in the forecasted impact time period. Some examples could be legislative changes made by the Congress to the Medicare program that would impact program funding, or changes specifically related to IRFs. Although some of these changes may not necessarily be specific to the IRF PPS, the nature of the Medicare program is such that the changes may interact, and the complexity of the interaction of these changes could make it difficult to predict accurately the full scope of the impact upon IRFs.

In updating the rates for FY 2023, we are implementing the standard annual revisions described in this final rule (for example, the update to the wage index and market basket increase factor used to adjust the Federal rates). We are also reducing the FY 2023 IRF market basket increase factor by a productivity adjustment in accordance with section 1886(j)(3)(C)(ii)(I) of the Act. We estimate the total increase in payments to IRFs in FY 2023, relative to FY 2022, would be approximately $275 million.

This estimate is derived from the application of the FY 2023 IRF market basket increase factor, as reduced by a productivity adjustment in accordance with section 1886(j)(3)(C)(ii)(I) of the Act, which yields an estimated increase in aggregate payments to IRFs of $330 million. However, there is an estimated $55 million decrease in aggregate payments to IRFs due to the proposed update to the outlier threshold amount. Therefore, we estimate that these updates would result in a net increase in estimated payments of $275 million from FY 2022 to FY 2023.

The effects of the updates that impact IRF PPS payment rates are shown in Table 14. The following updates that affect the IRF PPS payment rates are discussed separately below:

• The effects of the update to the outlier threshold amount, from approximately 3.6 percent to 3.0 percent of total estimated payments for FY 2023, consistent with section 1886(j)(4) of the Act.
• The effects of the annual market basket update (using the IRF market basket) to IRF PPS payment rates, as required by sections 1886(j)(3)(A)(i) and (j)(3)(C) of the Act, including a productivity adjustment in accordance with section 1886(j)(3)(C)(ii)(I) of the Act.
• The effects of applying the budget-neutral labor-related share and wage index adjustment, as required under section 1886(j)(6) of the Act.
• The effects of applying the budget-neutral permanent cap on wage index decreases policy.
• The effects of the budget-neutral changes to the CMG relative weights and ALOS values under the authority of section 1886(j)(2)(C)(i) of the Act.
• The total change in estimated payments based on the FY 2023 payment changes relative to the estimated FY 2022 payments.

3. Description of Table 14

Table 14 shows the overall impact on the 1,118 IRFs included in the analysis.

The next 12 rows of Table 14 contain IRFs categorized according to their geographic location, designation as either a freestanding hospital or a unit of a hospital, and by type of ownership; all urban, which is further divided into urban units of a hospital, urban freestanding hospitals, and by type of ownership; and all rural, which is further divided into rural units of a hospital, rural freestanding hospitals, and by type of ownership. There are 972 IRFs located in urban areas included in our analysis. Among these, there are 654 IRF units of hospitals located in urban areas and 318 freestanding IRF hospitals located in urban areas. There are 146 IRFs located in rural areas included in our analysis. Among these, there are 134 IRF units of hospitals located in rural areas and 12 freestanding IRF hospitals located in rural areas. There are 434 for-profit IRFs. Among these, there are 399 IRFs in urban areas and 35 IRFs in rural areas. There are 577 non-profit IRFs. Among these, there are 487 urban IRFs and 90 rural IRFs. There are 107 government-owned IRFs. Among these, there are 86 urban IRFs and 21 rural IRFs.

The remaining four parts of Table 14 show IRFs grouped by their geographic location within a region, by teaching status, and by DSH patient percentage (PP). First, IRFs located in urban areas are categorized for their location within a particular one of the nine Census geographic regions. Second, IRFs located in rural areas are categorized for their location within a particular one of the nine Census geographic regions. In some cases, especially for rural IRFs located in the New England, Mountain, and Pacific regions, the number of IRFs represented is small. IRFs are then grouped by teaching status, including non-teaching IRFs, IRFs with an intern and resident to average daily census (ADC) ratio less than 10 percent, IRFs with an intern and resident to ADC ratio greater than or equal to 10 percent and less than or equal to 19 percent, and IRFs with an intern and resident to ADC ratio greater than 19 percent. Finally, IRFs are grouped by DSH PP, including IRFs with zero DSH PP, IRFs with a DSH PP less than 5 percent, IRFs with a DSH PP between 5 and less than 10 percent, IRFs with a DSH PP between 10 and 20 percent, and IRFs with a DSH PP greater than 20 percent.

The estimated impacts of each policy described in this rule to the facility categories listed are shown in the columns of Table 14. The description of each column is as follows:

• Column (1) shows the facility classification categories.
• Column (2) shows the number of IRFs in each category in our FY 2023 analysis file.
• Column (3) shows the number of cases in each category in our FY 2023 analysis file.
• Column (4) shows the estimated effect of the adjustment to the outlier threshold amount.
• Column (5) shows the estimated effect of the update to the IRF labor-related share and wage index, in a budget-neutral manner.
• Column (6) shows the estimated effect of the permanent cap on wage index decreases policy, in a budget-neutral manner.
• Column (7) shows the estimated effect of the update to the CMG relative weights and ALOS values, in a budget-neutral manner.
• Column (8) compares our estimates of the payments per discharge, incorporating all of the policies reflected in this final rule for FY 2023 to our estimates of payments per discharge in FY 2022.

The average estimated increase for all IRFs is approximately 3.2 percent. This estimated net increase includes the effects of the IRF market basket increase factor for FY 2023 of 3.9 percent, which is based on a IRF market basket update of 4.2 percent, less a 0.3 percentage point productivity adjustment, as required by section 1886(j)(3)(C)(ii)(I) of the Act. It also includes the approximate 0.6 percent overall decrease in estimated IRF outlier payments from the update to the outlier threshold amount. Since we are making the updates to the IRF wage index, labor-related share and the CMG relative weights in a budget-neutral manner, they will not be expected to affect total estimated IRF payments in the aggregate. However, as described in more detail in each section, they will be expected to affect the estimated distribution of payments among providers.

4. Impact of the Update to the Outlier Threshold Amount

The estimated effects of the update to the outlier threshold adjustment are presented in column 4 of Table 14.

For the FY 2023 proposed rule, we used preliminary FY 2021 IRF claims data and, based on that preliminary analysis, we estimated that IRF outlier payments as a percentage of total estimated IRF payments would be 3.8 percent in FY 2022. As we typically do between the proposed and final rules each year, we updated our FY 2021 IRF claims data to ensure that we are using the most recent available data in setting IRF payments. Therefore, based on an updated analysis of the most recent IRF claims data for this final rule, we estimate that IRF outlier payments as a percentage of total estimated IRF payments are 3.6 percent in FY 2022. Thus, we are adjusting the outlier threshold amount in this final rule to maintain total estimated outlier payments equal to 3 percent of total estimated payments in FY 2023. The estimated change in total IRF payments for FY 2023, therefore, includes an approximate 0.6 percentage point decrease in payments because the estimated outlier portion of total payments is estimated to decrease from approximately 3.6 percent to 3.0 percent.

The impact of this outlier adjustment update (as shown in column 4 of Table 14) is to decrease estimated overall payments to IRFs by 0.6 percentage point.

5. Impact of the Wage Index and Labor-Related Share

In column 5 of Table 14, we present the effects of the budget-neutral update of the wage index and labor-related share. The changes to the wage index and the labor-related share are discussed together because the wage index is applied to the labor-related share portion of payments, so the changes in the two have a combined effect on payments to providers. As discussed in section VI.C. of this final rule, the FY 2023 labor-related share is 72.9 percent, which is the same as the labor-related share for FY 2022. In aggregate, we do not estimate that these updates will affect overall estimated payments to IRFs. However, we do expect these updates to have small distributional effects. We estimate the largest decrease in payment from the update to the CBSA wage index and labor-related share to be a 1.1 percent decrease for IRFs in the Urban New England region and the largest increase in payment to be a 1.1 percent increase for IRFs in the Rural New England Region.

6. Impact of the Wage Index Policy

In column 6 of Table 14, we present the effects of the budget-neutral permanent cap on wage index decreases policy. As discussed in section VI.D.3 of this final rule, we are applying a permanent 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year to smooth the impact of year-to-year changes in IRF payments related to changes in the IRF wage index. We are required by section 1886(j)(6) of the Act to implement changes to the wage index in a budget-neutral manner. Thus, there will not be an impact on aggregate Medicare payments to IRFs.

7. Impact of the Update to the CMG Relative Weights and ALOS Values.

In column 7 of Table 14, we present the effects of the budget-neutral update of the CMG relative weights and ALOS values. In the aggregate, we do not estimate that these updates will affect overall estimated payments of IRFs. However, we do expect these updates to have small distributional effects, with the largest effect begin a decrease in payments of 0.3 percent to IRFs in the Rural Pacific region.

8. Effects of Codification and Clarifications of IRF Teaching Status Adjustment Policy

As discussed in section VIII. of this final rule, we are codifying the longstanding teaching status adjustment policy through the amendments to the regulation text at § 412.602 and § 412.624(e)(4) provided in this final rule.

We do not anticipate a financial impact associated with the codification of the IRF teaching status adjustment policies. However, the clarification of certain teaching status adjustment policies and codification of these policies will enable us to align the IRF policies with recent updates to the IPPS and IPF teaching status adjustment policies. Aligning the policy guidance with other post-acute care setting regulations will also assist stakeholders in providing care for Medicare beneficiaries.

9. Effects of Requirements for the IRF QRP for FY 2026

In accordance with section1886(j)(7)(A) of the Act, the Secretary must reduce by 2 percentage points the annual market basket increase factor otherwise applicable to an IRF for a fiscal year if the IRF does not comply with the requirements of the IRF QRP for that fiscal year. In section X.A. of the proposed rule, we discuss the method for applying the 2 percentage point reduction to IRFs that fail to meet the IRF QRP requirements.

As discussed in section XI.F.2. of this final rule, we are finalizing the proposal to require the reporting of quality data on all patients discharged from the IRF beginning with the FY 2026 IRF QRP. We describe the estimated burden for the proposal in section XI.B. of the proposed rule. In summary, the changes to the IRF QRP will result in a burden addition of $28,505.41 per IRF annually, or $31,783,532.15 for all IRFs annually beginning with the FY 2026 IRF QRP. We note, however, that this estimate may be partially offset by eliminating the effort that IRFs currently undertake to separate out Medicare beneficiaries from other patients, which is also burdensome.

D. Alternatives Considered

The following is a discussion of the alternatives considered for the IRF PPS updates contained in this final rule.

Section 1886(j)(3)(C) of the Act requires the Secretary to update the IRF PPS payment rates by an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services.

As noted previously in this final rule, section 1886(j)(3)(C) of the Act requires the Secretary to update the IRF PPS payment rates by an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services and section 1886(j)(3)(C)(ii)(I) of the Act requires the Secretary to apply a productivity adjustment to the market basket increase factor for FY 2023. There is currently no mechanism to adjust for market basket forecast error in the IRF payment update and any change to the productivity adjusted-market basket update would need to be made by a change to the statute at section 1886(j)(3)(C)(ii)(I) of the Act. Thus, in accordance with sections 1886(j)(3)(C) of the Act, we are updating the IRF prospective payments in this final rule by 3.9 percent (which equals the 4.2 percent estimated IRF market basket increase factor for FY 2023 reduced by a 0.3 percentage point productivity adjustment as determined under section 1886(b)(3)(B)(xi)(II) of the Act (as required by section 1886(j)(3)(C)(ii)(I) of the Act)).

We considered maintaining the existing CMG relative weights and average length of stay values for FY 2023. However, in light of recently available data and our desire to ensure that the CMG relative weights and average length of stay values are as reflective as possible of recent changes in IRF utilization and case mix, we believe that it is appropriate to update the CMG relative weights and average length of stay values at this time to ensure that IRF PPS payments continue to reflect as accurately as possible the current costs of care in IRFs.

We considered maintaining the existing outlier threshold amount for FY 2023. However, analysis of updated FY 2021 data indicates that estimated outlier payments would be more than 3 percent of total estimated payments for FY 2022, by approximately 0.6 percent, unless we updated the outlier threshold amount. Consequently, we are adjusting the outlier threshold amount in this final rule to reflect a 0.6 percent decrease thereby setting the total outlier payments equal to 3 percent, instead of 3.6 percent, of aggregate estimated payments in FY 2023.

We considered not amending § 412.602 and § 412.624(e)(4) to codify our longstanding guidance on the teaching status adjustment policies and update the IRF teaching policy on IRF program closures and displaced residents. However, we believe that codifying these longstanding policies into regulation text would improve clarity and reduce administrative burden on IRF providers trying to locate all relevant information regarding the teaching status adjustment. Additionally, we believe that we should streamline all teaching status adjustment policy information in the same place for ease of reference.

E. Regulatory Review Costs

If regulations impose administrative costs on private entities, such as the time needed to read and interpret this final rule, we should estimate the cost associated with regulatory review. Due to the uncertainty involved with accurately quantifying the number of entities that will review the rule, we assume that the total number of unique commenters on the FY 2023 IRF PPS proposed rule will be the number of reviewers of this year's final rule. We acknowledge that this assumption may understate or overstate the costs of reviewing this final rule. It is possible that not all commenters reviewed the FY 2023 IRF PPS proposed rule in detail, and it is also possible that some reviewers chose not to comment on the FY 2023 proposed rule. For these reasons, we thought that the number of commenters would be a fair estimate of the number of reviewers of this final rule.

We also recognize that different types of entities are in many cases affected by mutually exclusive sections of this final rule, and therefore, for the purposes of our estimate we assume that each reviewer reads approximately 50 percent of the rule.

Using the national mean hourly wage data from the May 2021 BLS for Occupational Employment Statistics (OES) for medical and health service managers (SOC 11-9111), we estimate that the cost of reviewing this rule is $115.22 per hour, including overhead and fringe benefits ( https://www.bls.gov/​oes/​current/​oes_​nat.htm). Assuming an average reading speed, we estimate that it would take approximately 3 hours for the staff to review half of this final rule. For each reviewer of the rule, the estimated cost is $345.66 (3 hours x $115.22). Therefore, we estimate that the total cost of reviewing this regulation is $21,085.26 ($345.66 x 61 reviewers).

F. Accounting Statement and Table

As required by OMB Circular A-4 (available at https://www.whitehouse.gov/​wp-content/​uploads/​legacy_​drupal_​files/​omb/​circulars/​A4/​a-4.pdf), in Table 15 we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this final rule. Table 15 provides our best estimate of the increase in Medicare payments under the IRF PPS as a result of the updates presented in this final rule based on the data for 1,118 IRFs in our database.

G. Conclusion

Overall, the estimated payments per discharge for IRFs in FY 2023 are projected to increase by 3.2 percent, compared with the estimated payments in FY 2022, as reflected in column 8 of Table 14.

IRF payments per discharge are estimated to increase by 3.2 percent in urban areas and 3.1 percent in rural areas, compared with estimated FY 2022 payments. Payments per discharge to rehabilitation units are estimated to increase 2.6 percent in urban areas and 2.9 percent in rural areas. Payments per discharge to freestanding rehabilitation hospitals are estimated to increase 3.7 percent in urban areas and increase 3.7 percent in rural areas.

Overall, IRFs are estimated to experience a net increase in payments as a result of the policies in this final rule. The largest payment increase is estimated to be a 4.1 percent increase for IRFs located in the Urban West South Central region. The analysis above, together with the remainder of this preamble, provides an RIA.

In accordance with the provisions of Executive Order 12866, this regulation was reviewed by OMB.

Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & Medicaid Services, approved this document July 19, 2022.

List of Subjects in 42 CFR Part 412

• Administrative practice and procedure
• Health facilities
• Medicare
• Puerto Rico
• Reporting and recordkeeping requirements

For the reasons set forth in the preamble, the Centers for Medicare & Medicaid Services amends 42 CFR chapter IV as set forth below:

PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES

1. The authority citation for part 412 continues to read as follows:

Authority: 42 U.S.C. 1302 and 1395hh.

2. Amend § 412.602 by adding the definitions of “Closure of an IRF”, “Closure of an IRF's residency training program”, and “Displaced resident” in alphabetical order to read as follows:

§ 412.602

Definitions.

* * * * *

Closure of an IRF has the same meaning as “closure of a hospital” as defined in § 413.79(h)(1)(i) as applied to an IRF meeting the requirements of § 412.604(b) for the purposes of accounting for indirect teaching costs.

Closure of an IRF's residency training program has the same meaning as “closure of a hospital residency training program” as defined in § 413.79(h)(1)(ii) as applied to an IRF meeting the requirements of § 412.604(b) for the purposes of accounting for indirect teaching costs.

* * * * *

Displaced resident has the same meaning as a “displaced resident” as defined in § 413.79(h)(1)(iii) as applied to an IRF, for purposes of accounting for indirect teaching costs.

* * * * *

3. Amend § 412.604 by revising paragraph (c) to read as follows:

§ 412.604

Conditions for payment under the prospective payment system for inpatient rehabilitation facilities.

* * * * *

(c) Completion of patient assessment instrument. For each Medicare part A fee-for-service patient admitted to or discharged from an IRF on or after January 1, 2002, the inpatient rehabilitation facility must complete a patient assessment instrument in accordance with § 412.606. IRFs must also complete a patient assessment instrument in accordance with § 412.606 for each Medicare Part C (Medicare Advantage) patient admitted to or discharged from an IRF on or after October 1, 2009. In addition, IRFs must complete a patient assessment instrument in accordance with § 412.606 for all other patients, regardless of payer, admitted to or discharged from an IRF on or after October 1, 2024.

* * * * *

4. Amend § 412.606 by revising paragraphs (a) and (b)(1) to read as follows:

§ 412.606

Patient assessments.

(a) Patient assessment instrument. An inpatient rehabilitation facility must use the CMS inpatient rehabilitation facility patient assessment instrument to assess Medicare Part A fee-for-service and Medicare Part C (Medicare Advantage) inpatients who are admitted on or after January 1, 2002, or were admitted before January 1, 2002, and are still inpatients as of January 1, 2002.

(1) Starting on October 1, 2024, inpatient rehabilitation facilities must use the CMS inpatient rehabilitation facility patient assessment instrument to assess all inpatients, regardless of payer, who are admitted on or after October 1, 2024, or who were admitted before October 1, 2024 and are still inpatients as of October 1, 2024.

(2) [Reserved]

(b) * * * (1) A clinician of the inpatient rehabilitation facility must perform a comprehensive, accurate, standardized, and reproducible assessment of each Medicare Part A fee-for-service inpatient using the inpatient rehabilitation facility patient assessment instrument specified in paragraph (b) of this section as part of his or her patient assessment in accordance with the schedule described in § 412.610. IRFs must also complete a patient assessment instrument in accordance with § 412.606 for each Medicare Part C (Medicare Advantage) patient admitted to or discharged from an IRF on or after October 1, 2009. In addition, IRFs must complete a patient assessment instrument in accordance with § 412.606 for all other patients, regardless of payer, admitted to or discharged from an IRF on or after October 1, 2024.

* * * * *

5. Amend § 412.610 by revising paragraphs (a), (b), (c) introductory text, (c)(1)(i)(A), (c)(2)(ii)(B) and (f) to read as follows:

§ 412.610

Assessment schedule

(a) General. For each inpatient, an inpatient rehabilitation facility must complete a patient assessment instrument as specified in § 412.606 that covers a time period that is in accordance with the assessment schedule specified in paragraph (c) of this section.

(b) Starting the assessment schedule day count. The first day that the inpatient is furnished services during his or her current inpatient rehabilitation facility hospital stay is counted as day one of the patient assessment schedule.

(c) Assessment schedules and references dates. The inpatient rehabilitation facility must complete a patient assessment instrument upon the patient's admission and discharge as specified in paragraphs (c)(1) and (2) of this section.

(1) * * *

(i) * * *

(A) General. Time period is a span of time that covers calendar days 1 through 3 of the patient's current hospitalization.

* * * * *

(2) * * *

(ii) * * *

(B) The patient stops being furnished inpatient rehabilitation services.

* * * * *

(f) Patient assessment instrument record retention. An inpatient rehabilitation facility must maintain all patient assessment data sets completed on all Medicare Part A fee-for-service patients within the previous 5 years, on Medicare Part C (Medicare Advantage) patients within the previous 10 years, and all other patients within the previous 5 years either in a paper format in the patient's clinical record or in an electronic computer file format that the inpatient rehabilitation facility can easily obtain and produce upon request to CMS or its contractors.

6. Amend § 412.614 by—

a. Revising paragraphs (a) introductory text, (b)(1) and (d)(2);

b. Adding paragraph (d)(3); and

d. Revising paragraph (e).

The revisions and additions read as follows:

§ 412.614

Transmission of patient assessment data.

(a) Data format—General rule. The inpatient rehabilitation facility must encode and transmit data for each inpatient—

* * * * *

(b) * * *

(1) Electronically transmit complete, accurate, and encoded data from the patient assessment instrument for each inpatient to our patient data system in accordance with the data format specified in paragraph (a) of this section; and

* * * * *

(d) * * *

(2) Medicare Part C (Medicare Advantage) data. Failure of the inpatient rehabilitation facility to transmit all of the required patient assessment instrument data for its Medicare Part C (Medicare Advantage) patients to our patient data system in accordance with the transmission timeline in paragraph (c) of this section will result in a forfeiture of the facility's ability to have any of its Medicare Part C (Medicare Advantage) data used in the calculations for determining the facility's compliance with the regulations in § 412.29(b)(1).

(3) All other payer data. Failure of the inpatient rehabilitation facility to transmit all of the required patient assessment instrument data for all other patients, regardless of payer, to our patient data system in accordance with the transmission timeline in paragraph (c) of this section will result in a forfeiture of the facility's ability to have any of its other payer data used in the calculations for determining the facility's compliance with the regulations in § 412.29(b)(1).

(e) Exemption to the consequences for transmitting the IRF-PAI data late for Medicare Part C (Medicare Advantage) patients and all other patients, regardless of payer. CMS may waive the consequences of failure to submit complete and timely IRF-PAI data specified in paragraph (d) of this section when, due to an extraordinary situation that is beyond the control of an inpatient rehabilitation facility, the inpatient rehabilitation facility is unable to transmit the patient assessment data in accordance with paragraph (c) of this section. Only CMS can determine if a situation encountered by an inpatient rehabilitation facility is extraordinary and qualifies as a situation for waiver of the forfeiture specified in paragraphs (d)(2) or (3) of this section. An extraordinary situation may be due to, but is not limited to, fires, floods, earthquakes, or similar unusual events that inflect extensive damage to an inpatient facility. An extraordinary situation may be one that produces a data transmission problem that is beyond the control of the inpatient rehabilitation facility, as well as other situations determined by CMS to be beyond the control of the inpatient rehabilitation facility. An extraordinary situation must be fully documented by the inpatient rehabilitation facility.

7. Amend § 412.618 by revising the introductory text to read as follows:

§ 412.618

Assessment process for interrupted stays.

For purposes of the patient assessment process, if any patient has an interrupted stay, as defined under § 412.602, the following applies:

* * * * *

8. Amend § 412.624 by revising paragraphs (e)(1) and (4) to read as follows:

§ 412.624

Methodology for calculating the Federal prospective payment rates.

* * * * *

(e) * * *

(1) Adjustment for area wage levels. The labor portion of a facility's Federal prospective payment is adjusted to account for geographical differences in the area wage levels using an appropriate wage index.

(i) The application of the wage index is made on the basis of the location of the facility in an urban or rural area as defined in § 412.602.

(ii) Starting on October 1, 2022, CMS applies a cap on decreases to the wage index such that the wage index applied to an IRF is not less than 95 percent of the wage index applied to that IRF in the prior FY.

(iii) Adjustments or updates to the wage data used to adjust a facility's Federal prospective payment rate under paragraph (e)(1) of this section will be made in a budget neutral manner. CMS determines a budget neutral wage adjustment factor, based on any adjustment or update to the wage data, to apply to the standard payment conversion factor.

* * * * *

(4) Adjustments for teaching hospitals. (i) General. For discharges on or after October 1, 2005, CMS adjusts the Federal prospective payment on a facility basis by a factor as specified by CMS for facilities that are teaching institutions or units of teaching institutions.

(A) An IRF's teaching adjustment is based on the ratio of the number of full-time equivalent residents training in the IRF divided by the facility's average daily census.

(B) As described in § 412.105(f)(1)(iii)(A), residents with less than full-time status are counted as partial full time equivalent based on the proportion of time assigned to the inpatient rehabilitation facility compared to the total time necessary to fill a residency slot. Residents rotating to more than one hospital or non-hospital setting will be counted in proportion to the time they are assigned to inpatient rehabilitation facility compared to the total time worked in all locations. An inpatient rehabilitation facility cannot claim time spent by the resident at another inpatient rehabilitation facility or hospital.

(C) Except as described in paragraph (e)(4)(i)(D) of this section, the actual number of current year full-time equivalent residents used in calculating the teaching adjustment is limited to the number of full-time equivalent residents in the IRF's final settled cost report for the most recent cost reporting period ending on or before November 15, 2004 (base year).

(D) If the inpatient rehabilitation facility first begins training residents in a new approved graduate medical education program after November 15, 2004, the number of full-time equivalent residents determined under paragraph (e)(4)(i)(C) of this section may be adjusted using the method described in § 413.79(e)(1)(i).

(E) The teaching adjustment is made on a claim basis as an interim payment, and the final payment in full for the claim is made during the final settlement of the cost report.

(ii) Closure of an IRF or IRF residency training program. (A) Closure of an IRF. For cost reporting periods beginning on or after October 1, 2011, an IRF may receive a temporary adjustment to its FTE cap to reflect displaced residents added because of another IRFs closure if the IRF meets the following criteria:

( 1) The IRF is training additional displaced residents from an IRF that closed on or after October 1, 2011.

( 2) No later than 60 days after the IRF begins to train the displaced residents, the IRF submits a request to its Medicare contractor for a temporary adjustment by identifying the displaced residents who have come from the closed IRF and have caused the IRF to exceed its cap, and specifies the length of time the adjustment is needed.

(B) Closure of an IRF's residency training program. If an IRF that closes its residency training program on or after October 1, 2011, agrees to temporarily reduce its FTE cap according to the criteria specified in paragraph (e)(4)(ii)(A)( 2) of this section, another IRF(s) may receive a temporary adjustment to its FTE cap to reflect displaced residents added because of the closure of the residency training program if the criteria specified in paragraph (e)(4)(ii)(A)( 1) of this section are met.

( 1) Receiving IRF(s). For cost reporting periods beginning on or after October 1, 2011, an IRF may receive a temporary adjustment to its FTE cap to reflect displaced residents added because of the closure of another IRF's residency training program if the IRF is training additional displaced residents from the residency training program of an IRF that closed a program; and if no later than 60 days after the IRF begins to train the displaced residents the IRF submits to its Medicare Contractor a request for a temporary adjustment to its FTE cap, documents that it is eligible for this temporary adjustment by identifying the displaced residents who have come from another IRF's closed program and have caused the IRF to exceed its cap, specifies the length of time the adjustment is needed, and submits to its Medicare Contractor a copy of the FTE reduction statement by the hospital that closed its program, as specified in paragraph (e)(4)(ii)(A)( 2) of this section.

( 2) IRF that closed its program. An IRF that agrees to train displaced residents who have been displaced by the closure of another IRF's program may receive a temporary FTE cap adjustment only if the hospital with the closed program temporarily reduces its FTE cap based on the FTE of displaced residents in each program year training in the program at the time of the programs closure. This yearly reduction in the FTE cap will be determined based on the number of those displaced residents who would have been training in the program during that year had the program not closed. No later than 60 days after the displaced residents who were in the hospital that closed its program(s) begin training at another hospital must submit to its Medicare Contractor a statement signed and dated by its representative that specifies that it agrees to the temporary reduction in its FTE cap to allow the IRF training the displaced residents to obtain a temporary adjustment to its cap; identifies the displaced residents who were in the training at the time of the program's closure; identifies the IRFs to which the displaced residents are transferring once the program closes; and specifies the reduction for the applicable program years.

* * * * *

Dated: July 25, 2022.

Xavier Becerra,

Secretary, Department of Health and Human Services.

Footnotes

1.  Patel A., Jernigan D.B. Initial Public Health Response and Interim Clinical Guidance for the 2019 Novel Coronavirus Outbreak—United States, December 31, 2019-February 4, 2020. MMWR Morb Mortal Wkly Rep 2020;69:140-146. DOI http://dx.doi.org/​10.15585/​mmwr.mm6905e1.

2.  CMS, “COVID-19 Emergency Declaration Blanket Waivers for Health Care Providers,” (updated Feb. 19 2021) (available at https://www.cms.gov/​files/​document/​summary-covid-19-emergency-declaration-waivers.pdf).

3.  CMS, “COVID-19 Frequently Asked Questions (FAQs) on Medicare Fee-for-Service (FFS) Billing,” (updated March 5, 2021) (available at https://www.cms.gov/​files/​document/​03092020-covid-19-faqs-508.pdf).

4.  HL7 FHIR Release 4. Available at https://www.hl7.org/​fhir/​.

5.  HL7 FHIR. PACIO Functional Status Implementation Guide. Available at https://paciowg.github.io/​functional-status-ig/​.

6.  The IMPACT Act (Pub. L. 113-185) requires the reporting of standardized patient assessment data with regard to quality measures and standardized patient assessment data elements. The Act also requires the submission of data pertaining to measure domains of resource use, and other domains. In addition, the IMPACT Act requires assessment data to be standardized and interoperable to allow for exchange of the data among post-acute providers and other providers. The Act intends for standardized post-acute care data to improve Medicare beneficiary outcomes through shared-decision making, care coordination, and enhanced discharge planning.

7.  Centers for Medicare & Medicaid Services. Newsroom. Fact sheet: CMS Data Element Library Fact Sheet. June 21, 2018. Available at https://www.cms.gov/​newsroom/​fact-sheets/​cms-data-element-library-fact-sheet.

8.  Centers for Medicare & Medicaid Services. Health Informatics and Interoperability Group. Policies and Technology for Interoperability and Burden Reduction. Available at https://www.cms.gov/​Regulations-and-Guidance/​Guidance/​Interoperability/​index.

9.  Bates, David W, and Lipika Samal. “Interoperability: What Is It, How Can We Make It Work for Clinicians, and How Should We Measure It in the Future?.” Health services research vol. 53,5 (2018): 3270-3277. doi:10.1111/1475-6773.12852.

10.  The Common Agreement defines Individual Access Services (IAS) as “with respect to the Exchange Purposes definition, the services provided utilizing the Connectivity Services, to the extent consistent with Applicable Law, to an Individual with whom the QHIN, Participant, or Subparticipant has a Direct Relationship to satisfy that Individual's ability to access, inspect, or obtain a copy of that Individual's Required Information that is then maintained by or for any QHIN, Participant, or Subparticipant.” The Common Agreement defines “IAS Provider” as: “Each QHIN, Participant, and Subparticipant that offers Individual Access Services.” See Common Agreement for Nationwide Health Information Interoperability Version 1, at 7 (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Common_​Agreement_​for_​Nationwide_​Health_​Information_​Interoperability_​Version_​1.pdf.

11.  The National Imperative to Improve Nursing Home Quality: Honoring Our Commitment to Residents, Families & Staff, see https://nap.nationalacademies.org/​catalog/​26526/​the-national-imperative-to-improve-nursing-home-quality-honoring-our.

12.   https://www.medpac.gov/​wp-content/​uploads/​2022/​03/​Mar22_​MedPAC_​ReportToCongress_​SEC.pdf.

13.  Office of the Inspector General. December 7, 2021 Early Discharges From Inpatient Rehabilitation Facilities to Home Health Services [Report No. A-01-20-00501] https://oig.hhs.gov.

14.  National Quality Forum. MAP Coordination Strategy for Post-Acute Care and Long-Term Care Performance Measurement. February 2012. Available at https://www.qualityforum.org/​Publications/​2012/​02/​MAP_​Coordination_​Strategy_​for_​Post-Acute_​Care_​and_​Long-Term_​Care_​Performance_​Measurement.aspx. Accessed January 31, 2022.

15.   https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​MMS/​MMS-Blueprint. Accessed January 31, 2022.

16.  In the FY 2010 IRF PPS final rule (74 FR 39798 through 39800), CMS revised the regulation text in §§ 412.604, 412.606, 412.610, 412.614, and 412.618 to require that all IRFs submit IRF-PAI data on all of their Medicare Part C patients.

17.   https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​Downloads/​CMS-Quality-Strategy.pdf.

18.  Report to Congress: Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/​About-CMS/​Agency-Information/​OMH/​Downloads/​Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.

19.  § 482.24 Condition of Participation: Medical Record Services.

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27.  Selph, S.S., & McDonagh, M.S. (2019). Depression in Children and Adolescents: Evaluation and Treatment. American Family Physician, 100(10), 609-617. https://www.aafp.org/​dam/​brand/​aafp/​pubs/​afp/​issues/​2019/​1115/​p609.pdf. Accessed 6/2/2022.

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30.  Hauer, J., Houtrow, A.J.; & Section on Hospice and Palliative Medicine, Council on Children with Disabilities. (2017). Pain Assessment and Treatment in Children With Significant Impairment of the Central Nervous System. Pediatrics, 139(6), e20171002. https://doi.org/​10.1542/​peds.2017-1002. https://pubmed.ncbi.nlm.nih.gov/​28562301/​. Accessed 6/3/2022.

31.  Groenewald, C.B. Opioid-prescribing Patterns for Pediatric Patients in the United States. (2019). Clinical Journal of Pain, 35(6), 515-520. https://doi.org/​10.1097/​AJP.0000000000000707. https://www.ncbi.nlm.nih.gov/​pmc/​articles/​PMC6782052/​#:~:text=​Opioid%20misuse%20is%20also%20a,having%20opioid%20use%20disorder19. Accessed 6/3/2022.

32.  Kelley-Quon, L.I., Kirkpatrick, M.G., Ricca, R.L., et al. (2021). Guidelines for Opioid Prescribing in Children and Adolescents After Surgery: An Expert Panel Opinion. JAMA Surgery, 156(1), 76-90. https://doi.org/​10.1001/​jamasurg.2020.5045. https://jamanetwork.com/​journals/​jamasurgery/​article-abstract/​2772855. Accessed 6/3/2022.

33.  US Department of Health and Human Services. Office of Disease Prevention and Health Promotion. Healthy People 2030. Available at https://health.gov/​healthypeople/​priority-areas/​social-determinants-health.

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35.  Viner, R.M., Ozer, E.M., Denny, S., Marmot, M., Resnick, M., Fatusi, A., & Currie, C. (2012). Adolescence and the social determinants of health. Lancet, 379(9826), 1641-1652. https://doi.org/​10.1016/​S0140-6736(12)60149-4.

36.   https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​Downloads/​CMS-Quality-Strategy.pdf.

37.  Report to Congress: Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/​About-CMS/​Agency-Information/​OMH/​Downloads/​Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.

38.  FY 2016 IRF PPS proposed rule (80 FR 23390).

39.  MedPAC Report to the Congress: Medicare Payment Policy. March 2022. Available at https://www.medpac.gov/​document/​march-2022-report-to-the-congress-medicare-payment-policy/​. Accessed June 6, 2022.

40.  Office of the Assistant Secretary for Planning and Evaluation (ASPE). Impact of the COVID-19 Pandemic on the Hospital and Outpatient Clinician Workforce: Challenges and Policy Responses. Available at https://aspe.hhs.gov/​index.php/​reports/​covid-19-health-care-workforce.

41.  Zhang X., Tai D., Pforsich H., Lin V.W. United States registered nurses workforce report card and shortage forecast: A revisit.

42.   https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​Downloads/​CMS-Quality-Strategy.pdf.

43.  Report to Congress: Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/​About-CMS/​Agency-Information/​OMH/​Downloads/​Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.

44.  The CMS IRF-PAI Manual Version 4.0 Effective 10-1-2022 can be found on the IRF-PAI and IRF QRP Manual website and downloaded here: https://www.cms.gov/​files/​zip/​cms-irf-pai-manual-version-40-effective-october-1-2022.zip.

45.   https://www.bls.gov/​oes/​current/​oes_​nat.htm.