2024-06764. Medicare Program; FY 2025 Inpatient Psychiatric Facilities Prospective Payment System-Rate Update

AGENCY:

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

ACTION:

Proposed rule.

SUMMARY:

This rulemaking proposes to update the prospective payment rates, the outlier threshold, and the wage index for Medicare inpatient hospital services provided by Inpatient Psychiatric Facilities (IPF), which include psychiatric hospitals and excluded psychiatric units of an acute care hospital or critical access hospital. This rulemaking also proposes to revise the patient-level adjustment factors, the Emergency Department adjustment, and the payment amount for electroconvulsive therapy. These proposed changes would be effective for IPF discharges occurring during the fiscal year beginning October 1, 2024 through September 30, 2025 (FY 2025). In addition, this proposed rule seeks to adopt a new quality measure and modify reporting requirements under the IPF Quality Reporting Program beginning with the FY 2027 payment determination. Furthermore, this proposed rule solicits comments through Requests for Information (RFIs) regarding potential future revisions to the IPF PPS facility-level adjustments and regarding the development of a standardized IPF Patient Assessment Instrument.

DATES:

To be assured consideration, comments must be received at one of the addresses provided below, by May 28, 2024.

ADDRESSES:

In commenting, please refer to file code CMS-1806-P.

Comments, including mass comment submissions, must be submitted in one of the following three ways (please choose only one of the ways listed):

1. Electronically. You may submit electronic comments on this regulation to http://www.regulations.gov. Follow the “Submit a comment” instructions.

2. By regular mail. You may mail written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-1806-P, P.O. Box 8010, Baltimore, MD 21244-8010.

Please allow sufficient time for mailed comments to be received before the close of the comment period.

3. By express or overnight mail. You may send written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-1806-P, Mail Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.

For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT:

Nick Brock [phone], for information regarding the inpatient psychiatric facilities prospective payment system (IPF PPS).

Kaleigh Emerson [phone], for information regarding the inpatient psychiatric facilities quality reporting program (IPFQR).

SUPPLEMENTARY INFORMATION:

Inspection of Public Comments: All comments received before the close of the comment period are available for viewing by the public, including any personally identifiable or confidential business information that is included in a comment. We post all comments received before the close of the comment period on the following website as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that website to view public comments. CMS will not post on Regulations.gov public comments that make threats to individuals or institutions or suggest that the commenter will take actions to harm an individual. CMS continues to encourage individuals not to submit duplicative comments. We will post acceptable comments from multiple unique commenters even if the content is identical or nearly identical to other comments.

Plain Language Summary: In accordance with 5 U.S.C. 553(b)(4), a plain language summary of this rule may be found at https://www.regulations.gov/​.

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

Addendum A to this proposed rule summarizes the proposed FY 2025 Inpatient Psychiatric Facilities Prospective Payment System (IPF PPS) payment rates, outlier threshold, cost of living adjustment factors for Alaska and Hawaii, national and upper limit cost-to-charge ratios, and adjustment factors. In addition, Addendum B to this proposed rule shows the complete listing of ICD-10 Clinical Modification and Procedure Coding System codes, the FY 2025 IPF PPS comorbidity adjustment, and electroconvulsive therapy procedure codes. The A and B Addenda are available on the CMS website at: https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.

Tables setting forth the FY 2025 Wage Index for Urban Areas Based on Core-Based Statistical Area Labor Market Areas, the FY 2025 Wage Index Based on CBSA Labor Market Areas for Rural Areas, and a county-level crosswalk of the FY 2024 CBSA Labor Market Areas to the FY 2025 CBSA Labor Market Areas are available exclusively through the internet, on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​IPFPPS/​WageIndex.html.

I. Executive Summary

A. Purpose

This proposed rule would update the prospective payment rates, the outlier threshold, and the wage index for Medicare inpatient hospital services provided by Inpatient Psychiatric Facilities (IPFs) for discharges occurring during fiscal year (FY) 2025, (beginning October 1, 2024 through September 30, 2025). We are proposing to adopt the Core-Based Statistical Area (CBSA) Labor Market Areas for the IPF PPS wage index as defined in the Office of Management and Budget (OMB) Bulletin 23-01. In addition, this rule includes a proposal to refine the patient-level adjustment factors and increase the payment amount for electroconvulsive therapy (ECT) treatments. We are not proposing changes to the facility-level adjustment factors for FY 2025; however, this proposed rule presents the results of our latest analysis and includes a request for information relating to those results. This rule also includes a clarification of the eligibility criteria for an IPF to be approved to file all-inclusive cost reports. In addition, this proposed rule includes a request for information regarding the creation of a patient assessment instrument (PAI) as mandated by Section 4125 of the Consolidated Appropriations Act (CAA), 2023 (hereafter referred to as CAA, 2023) (Pub. L. 117-328). Lastly, this proposed rule discusses quality measures and reporting requirements under the Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program.

B. Summary of the Major Provisions

1. Inpatient Psychiatric Facilities Prospective Payment System (IPF PPS)

For the IPF PPS, we are:

• Proposing to revise the patient-level IPF PPS adjustment factors and increase the ECT per treatment payment amount.
• Proposing to update the IPF PPS wage index to use the CBSAs defined within OMB Bulletin 23-01.
• Clarifying the eligibility criteria for an IPF to be approved to file all-inclusive cost reports. Only a government-owned or tribally owned facility will be able to satisfy these criteria and will be eligible to file its cost report using an all-inclusive rate or no charge structure.
• Soliciting comments to inform elements to be included in the IPF patient assessment instrument, which the CAA, 2023 requires the Centers for Medicare & Medicaid Services (CMS) to develop for FY 2028.
• Soliciting comments to inform future refinements to the IPF PPS facility-level adjustment factors.
• Making technical rate setting updates: The IPF PPS payment rates are adjusted annually for inflation, as well as statutory and other policy factors. This rule proposes to update:

++ The IPF PPS Federal per diem base rate from $895.63 to $874.93.

++ The IPF PPS Federal per diem base rate for providers who failed to report quality data to $857.89.

++ The ECT payment per treatment from $385.58 to $660.30.

++ The ECT payment per treatment for providers who failed to report quality data to $647.45.

++ The labor-related share from 78.7 percent to 78.8 percent.

++ The wage index budget neutrality factor to 0.9998. This proposed rule would apply a refinement standardization factor of 0.9514.

++ The fixed dollar loss threshold amount from $33,470 to $35,590, to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF PPS payments.

2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

For the IPFQR Program, we are proposing to:

• Adopt the 30-Day Risk-Standardized All-Cause Emergency Department (ED) Visit Following an IPF Discharge measure beginning with the FY 2027 payment determination; and
• Modify reporting requirements to require IPFs to submit patient-level data on a quarterly basis.

We also refer readers to our RFI in which we solicit comments to inform elements to be included in the IPF patient assessment instrument, which the CAA, 2023 requires the Centers for Medicare & Medicaid Services (CMS) to develop and implement for Rate Year (RY) 2028.

C. Summary of Impacts

II. Background

A. Overview of the Legislative Requirements of the IPF PPS

Section 124 of the Medicare, Medicaid, and State Children's Health Insurance Program Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113) required the establishment and implementation of an IPF PPS. Specifically, section 124 of the BBRA mandated that the Secretary of the Department of Health and Human Services (the Secretary) develop a per diem payment perspective system (PPS) for inpatient hospital services furnished in psychiatric hospitals and excluded psychiatric units including an adequate patient classification system that reflects the differences in patient resource use and costs among psychiatric hospitals and excluded psychiatric units. “Excluded psychiatric unit” means a psychiatric unit of an acute care hospital or of a Critical Access Hospital (CAH), which is excluded from payment under the Inpatient Prospective Payment System (IPPS) or CAH payment system, respectively. These excluded psychiatric units will be paid under the IPF PPS.

Section 405(g)(2) of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF PPS to psychiatric distinct part units of CAHs.

Sections 3401(f) and 10322 of the Patient Protection and Affordable Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act and by section 1105(d) of the Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152) (hereafter referred to jointly as “the Affordable Care Act”) added subsection (s) to section 1886 of the Act.

Section 1886(s)(1) of the Act titled “Reference to Establishment and Implementation of System,” refers to section 124 of the BBRA, which relates to the establishment of the IPF PPS.

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the rate year (RY) beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY.

Section 1886(s)(2)(A)(ii) of the Act required the application of an “other adjustment” that reduced any update to an IPF PPS base rate by a percentage point amount specified in section 1886(s)(3) of the Act for the RY beginning in 2010 through the RY beginning in 2019. As noted in the FY 2020 Inpatient Psychiatric Facilities Prospective Payment System and Quality Reporting Updates for fiscal year Beginning October 1, 2019 final rule, for the RY beginning in 2019, section 1886(s)(3)(E) of the Act required that the other adjustment reduction be equal to 0.75 percentage point; that was the final year the statute required the application of this adjustment. Because FY 2021 was a RY beginning in 2020, FY 2021 was the first year section 1886(s)(2)(A)(ii) of the Act did not apply since its enactment.

Sections 1886(s)(4)(A) through (D) of the Act require that for RY 2014 and each subsequent RY, IPFs that fail to report required quality data with respect to such a RY will have their annual update to a standard Federal rate for discharges reduced by 2.0 percentage points. This may result in an annual update being less than 0.0 for a RY, and may result in payment rates for the upcoming RY being less than such payment rates for the preceding RY. Any reduction for failure to report required quality data will apply only to the RY involved, and the Secretary will not consider such reduction in computing the payment amount for a subsequent RY. Additional information about the specifics of the current IPFQR Program is available in the FY 2020 Inpatient Psychiatric Facilities Prospective Payment System and Quality Reporting Updates for fiscal year Beginning October 1, 2019 (FY 2020) final rule (84 FR 38459 through 38468).

Section 4125 of the Consolidated Appropriations Act, 2023 (CAA, 2023) (Pub. L. 117-328), which amended section 1886(s) of the Act, requires CMS to revise the Medicare prospective payment system for psychiatric hospitals and psychiatric units. Specifically, section 4125(a) of the CAA, 2023 added section 1886(s)(5)(A) of the Act to require the Secretary to collect data and information, as the Secretary determines appropriate, to revise payments under the IPF PPS. CMS discussed this data collection last year in the FY 2024 IPF PPS final rule, as CMS was required to begin collecting this data and information not later than October 1, 2024. As discussed in that rule, the Agency has already been collecting data and information consistent with the types set forth in the CAA, 2023 as part of our extensive and years-long analyses and consideration of potential payment system refinements. We refer readers to the FY 2024 Inpatient Psychiatric Facilities Prospective Payment System—Rate Update (FY 2024 IPF PPS) final rule (88 FR 51095 through 51098) where we discussed existing data collection and requested information to inform future IPF PPS revisions.

In addition, section 1886(s)(5)(D) of the Act, as added by section 4125(a) of the CAA, 2023 requires that the Secretary implement revisions to the methodology for determining the payment rates under the IPF PPS for psychiatric hospitals and psychiatric units, effective for RY 2025 (FY 2025). The revisions may be based on a review of the data and information collected under section 1886(s)(5)(A) of the Act. As discussed in section III.C of this FY 2025 IPF PPS proposed rule, we are proposing revisions to the IPF PPS patient-level adjustment factors based on a review of cost and claims data.

Section 4125(b) of the CAA, 2023 amended section 1886(s)(4) of the Act by inserting a new subparagraph (E), which requires IPFs participating in the IPFQR Program to collect and submit to the Secretary standardized patient assessment data, using a standardized patient assessment instrument, for RY 2028 (FY 2028) and each subsequent rate year. IPFs must submit such data with respect to at least the admission and discharge of an individual, or more frequently as the Secretary determines appropriate. For IPFs to meet this new data collection and reporting requirement for RY 2028 and each subsequent rate year, the Secretary must implement a standardized patient assessment instrument that collects data with respect to the following categories: functional status; cognitive function and mental status; special services, treatments, and interventions; medical conditions and comorbidities; impairments; and other categories as determined appropriate by the Secretary. This patient assessment instrument must enable comparison of such patient assessment data that IPFs submit across all such IPFs to which such data are applicable.

Section 4125(b) of the CAA, 2023 further amended section 1886(s) of the Act by adding a new subparagraph (6) that requires the Secretary to implement revisions to the methodology for determining the payment rates for psychiatric hospitals and psychiatric units (that is, payment rates under the IPF PPS), effective for RY 2031 (FY 2031), as the Secretary determines to be appropriate, to take into account the patient assessment data described in paragraph (4)(E)(ii).

To implement and periodically update the IPF PPS, we have published various proposed and final rules and notices in the Federal Register . For more information regarding these documents, we refer readers to the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​index.html?​redirect=​/​InpatientPsychFacilPPS/​.

B. Overview of the IPF PPS

On November 15, 2004, we published the RY 2005 IPF PPS final rule in the Federal Register (69 FR 66922). The RY 2005 IPF PPS final rule established the IPF PPS, as required by section 124 of the BBRA and codified at 42 CFR part 412, subpart N. The RY 2005 IPF PPS final rule set forth the Federal per diem base rate for the implementation year (the 18-month period from January 1, 2005 through June 30, 2006) and provided payment for the inpatient operating and capital costs to IPFs for covered psychiatric services they furnish (that is, routine, ancillary, and capital costs, but not costs of approved educational activities, bad debts, and other services or items that are outside the scope of the IPF PPS). Covered psychiatric services include services for which benefits are provided under the fee-for-service Part A (Hospital Insurance Program) of the Medicare program.

The IPF PPS established the Federal per diem base rate for each patient day in an IPF derived from the national average daily routine operating, ancillary, and capital costs in IPFs in FY 2002. The average per diem cost was updated to the midpoint of the first year under the IPF PPS, standardized to account for the overall positive effects of the IPF PPS payment adjustments, and adjusted for budget neutrality.

The Federal per diem payment under the IPF PPS is comprised of the Federal per diem base rate described previously and certain patient- and facility-level payment adjustments for characteristics that were found in the regression analysis to be associated with statistically significant per diem cost differences, with statistical significance defined as p less than 0.05. A complete discussion of the regression analysis that established the IPF PPS adjustment factors can be found in the RY 2005 IPF PPS final rule (69 FR 66933 through 66936).

The patient-level adjustments include age, Diagnosis-Related Group (DRG) assignment, and comorbidities, as well as adjustments to reflect higher per diem costs at the beginning of a patient's IPF stay and lower costs for later days of the stay. Facility-level adjustments include adjustments for the IPF's wage index, rural location, teaching status, a cost-of-living adjustment for IPFs located in Alaska and Hawaii, and an adjustment for the presence of a qualifying emergency department (ED).

The IPF PPS provides additional payment policies for outlier cases, interrupted stays, and a per treatment payment for patients who undergo ECT. During the IPF PPS mandatory 3-year transition period, stop-loss payments were also provided; however, since the transition ended as of January 1, 2008, these payments are no longer available.

C. Annual Requirements for Updating the IPF PPS

Section 124 of the BBRA did not specify an annual rate update strategy for the IPF PPS and was broadly written to give the Secretary discretion in establishing an update methodology. Therefore, in the RY 2005 IPF PPS final rule, we implemented the IPF PPS using the following update strategy:

• Calculate the final Federal per diem base rate to be budget neutral for the 18- month period of January 1, 2005 through June 30, 2006.
• Use a July 1 through June 30 annual update cycle.
• Allow the IPF PPS first update to be effective for discharges on or after July 1, 2006 through June 30, 2007.

The RY 2005 final rule (69 FR 66922) implemented the IPF PPS. In developing the IPF PPS, and to ensure that the IPF PPS can account adequately for each IPF's case-mix, we performed an extensive regression analysis of the relationship between the per diem costs and certain patient and facility characteristics to determine those characteristics associated with statistically significant cost differences on a per diem basis. That regression analysis is described in detail in our RY 2004 IPF proposed rule (68 FR 66923; 66928 through 66933) and our RY 2005 IPF final rule (69 FR 66933 through 66960). For characteristics with statistically significant cost differences, we used the regression coefficients of those variables to determine the size of the corresponding payment adjustments.

In the RY 2005 IPF final rule, we explained the reasons for delaying an update to the adjustment factors, derived from the regression analysis, including waiting until we have IPF PPS data that yields as much information as possible regarding the patient-level characteristics of the population that each IPF serves. We indicated that we did not intend to update the regression analysis and the patient-level and facility-level adjustments until we complete that analysis. Until that analysis is complete, we stated our intention to publish a notice in the Federal Register each spring to update the IPF PPS (69 FR 66966).

On May 6, 2011, we published a final rule in the Federal Register titled, “Inpatient Psychiatric Facilities Prospective Payment System—Update for Rate Year Beginning July 1, 2011 (RY 2012)” (76 FR 26432), which changed the payment rate update period to a RY that coincides with a FY update. Therefore, final rules are now published in the Federal Register in the summer to be effective on October 1st. When proposing changes in IPF payment policy, a proposed rule is issued in the spring, and the final rule in the summer to be effective on October 1st. For a detailed list of updates to the IPF PPS, we refer readers to our regulations at 42 CFR 412.428. Beginning October 1, 2012, we finalized that we would refer to the 12-month period from October 1 through September 30 as a “fiscal year” (FY) rather than a RY (76 FR 26435). Therefore, in this final rule we refer to rules that took effect after RY 2012 by the FY, rather than the RY, in which they took effect.

The most recent IPF PPS annual update was published in a final rule on August 2, 2023 in the Federal Register titled, “Medicare Program; FY 2024 Inpatient Psychiatric Facilities Prospective Payment System—Rate Update” (88 FR 51054), which updated the IPF PPS payment rates for FY 2024. That final rule updated the IPF PPS Federal per diem base rates that were published in the FY 2023 IPF PPS Rate Update final rule (87 FR 46846) in accordance with our established policies.

III. Provisions of the Proposed Regulations

A. Proposed FY 2025 Market Basket Update and Productivity Adjustment for the IPF PPS

1. Background

Originally, the input price index used to develop the IPF PPS was the Excluded Hospital with Capital market basket. This market basket was based on 1997 Medicare cost reports for Medicare-participating inpatient rehabilitation facilities (IRFs), IPFs, long-term care hospitals (LTCHs), cancer hospitals, and children's hospitals. Although “market basket” technically describes the mix of goods and services used in providing health care at a given point in time, this term is also commonly used to denote the input price index (that is, cost category weights and price proxies) derived from that market basket. Accordingly, the term “market basket,” as used in this document, refers to an input price index.

Since the IPF PPS inception, the market basket used to update IPF PPS payments has been rebased and revised to reflect more recent data on IPF cost structures. We last rebased and revised the IPF market basket in the FY 2024 IPF PPS rule, where we adopted a 2021-based IPF market basket, using Medicare cost report data for both Medicare participating freestanding psychiatric hospitals and psychiatric units. We refer readers to the FY 2024 IPF PPS final rule for a detailed discussion of the 2021-based IPF PPS market basket and its development (88 FR 51057 through 51081). References to the historical market baskets used to update IPF PPS payments are listed in the FY 2016 IPF PPS final rule (80 FR 46656).

2. Proposed FY 2025 IPF Market Basket Update

For FY 2025 (beginning October 1, 2024 and ending September 30, 2025), we are proposing to update the IPF PPS payments by a market basket increase factor with a productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act. Consistent with historical practice, we are proposing to estimate the market basket update for the IPF PPS based on the most recent forecast available at the time of rulemaking from IHS Global Inc. (IGI). IGI is a nationally recognized economic and financial forecasting firm with which CMS contracts to forecast the components of the market baskets and productivity adjustment. For the proposed rule, based on IGI's fourth quarter 2023 forecast with historical data through the third quarter of 2023, the 2021-based IPF market basket increase factor for FY 2025 is 3.1 percent.

Section 1886(s)(2)(A)(i) of the Act 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 (MFP) (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or other annual period) (the “productivity adjustment”). The United States Department of Labor's Bureau of Labor Statistics (BLS) publishes the official measures of productivity for the United States 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 MFP. Beginning with the November 18, 2021 release of productivity data, BLS replaced the term “multifactor productivity” 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) of the Act is now published by BLS as private nonfarm business TFP. However, as mentioned previously, the data and methods are unchanged. We refer readers to 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/​data-research/​statistics-trends-and-reports/​medicare-program-rates-statistics/​market-basket-research-and-information. In addition, in the FY 2022 IPF final rule (86 FR 42611), 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.

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the RY beginning in 2012 (a RY that coincides with a FY) and each subsequent RY. For this proposed rule, based on IGI's fourth quarter 2023 forecast, the proposed productivity adjustment for FY 2025 (the 10-year moving average of TFP for the period ending FY 2025) is projected to be 0.4 percent. Accordingly, we are proposing to reduce the 3.1 percent IPF market basket increase by this 0.4 percentage point productivity adjustment, as mandated by the Act. This results in a proposed FY 2025 IPF PPS payment rate update of 2.7 percent (3.1−0.4 = 2.7). We are also proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 IPF market basket increase and productivity adjustment for the final rule.

We solicit comment on the proposed IPF market basket increase and productivity adjustment for FY 2025.

3. Proposed FY 2025 IPF Labor-Related Share

Due to variations in geographic wage levels and other labor-related costs, we believe that payment rates under the IPF PPS should continue to be adjusted by a geographic wage index, which would apply to the labor-related portion of the Federal per diem base rate (hereafter referred to as the labor-related share). 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 are proposing 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 2021-based IPF market basket, we are proposing to continue to include in the labor-related share the sum of the 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 2021-based IPF market basket. For more details regarding the methodology for determining specific cost categories for inclusion in the labor-related share based on the 2021-based IPF market basket, we refer readers to the FY 2024 IPF PPS final rule (88 FR 51078 through 51081).

The relative importance reflects the different rates of price change for these cost categories between the base year (FY 2021) and FY 2025. Based on IGI's fourth quarter 2023 forecast of the 2021-based IPF market basket, the sum of the FY 2025 relative importance moving average 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 is 75.7 percent. We are proposing, consistent with prior rulemaking, 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 is 6.8 percent of the 2021-based IPF market basket for FY 2025, we are proposing to take 46 percent of 6.8 percent to determine a labor-related share of Capital-Related costs for FY 2025 of 3.1 percent. Therefore, we are proposing a total labor-related share for FY 2025 of 78.8 percent (the sum of 75.7 percent for the labor-related share of operating costs and 3.1 percent for the labor-related share of Capital-Related costs). We are also proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 labor-related share for the final rule. For more information on the labor-related share and its calculation, we refer readers to the FY 2024 IPF PPS final rule (88 FR 51078 through 51081).

Table 1 shows the proposed FY 2025 labor-related share and the final FY 2024 labor-related share using the 2021- based IPF market basket relative importance.

We solicit comment on the proposed labor-related share for FY 2025.

B. Proposed Revisions to the IPF PPS Rates for FY Beginning October 1, 2024

The IPF PPS is based on a standardized Federal per diem base rate calculated from the IPF average per diem costs and adjusted for budget neutrality in the implementation year. The Federal per diem base rate is used as the standard payment per day under the IPF PPS and is adjusted by the patient-level and facility-level adjustments that are applicable to the IPF stay. A detailed explanation of how we calculated the average per diem cost appears in the RY 2005 IPF PPS final rule (69 FR 66926).

1. Determining the Standardized Budget Neutral Federal per Diem Base Rate

Section 124(a)(1) of the BBRA required that we implement the IPF PPS in a budget neutral manner. In other words, the amount of total payments under the IPF PPS, including any payment adjustments, must be projected to be equal to the amount of total payments that would have been made if the IPF PPS were not implemented. Therefore, we calculated the budget neutrality factor by setting the total estimated IPF PPS payments to be equal to the total estimated payments that would have been made under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been implemented. A step-by-step description of the methodology used to estimate payments under the TEFRA payment system appears in the RY 2005 IPF PPS final rule (69 FR 66926).

Under the IPF PPS methodology, we calculated the final Federal per diem base rate to be budget neutral during the IPF PPS implementation period (that is, the 18-month period from January 1, 2005 through June 30, 2006) using a July 1 update cycle. We updated the average cost per day to the midpoint of the IPF PPS implementation period (October 1, 2005), and this amount was used in the payment model to establish the budget neutrality adjustment.

Next, we standardized the IPF PPS Federal per diem base rate to account for the overall positive effects of the IPF PPS payment adjustment factors by dividing total estimated payments under the TEFRA payment system by estimated payments under the IPF PPS. The information concerning this standardization can be found in the RY 2005 IPF PPS final rule (69 FR 66932) and the RY 2006 IPF PPS final rule (71 FR 27045). We then reduced the standardized Federal per diem base rate to account for the outlier policy, the stop loss provision, and anticipated behavioral changes. A complete discussion of how we calculated each component of the budget neutrality adjustment appears in the RY 2005 IPF PPS final rule (69 FR 66932 through 66933) and in the RY 2007 IPF PPS final rule (71 FR 27044 through 27046). The final standardized budget neutral Federal per diem base rate established for cost reporting periods beginning on or after January 1, 2005 was calculated to be $575.95.

The Federal per diem base rate has been updated in accordance with applicable statutory requirements and 42 CFR 412.428 through publication of annual notices or proposed and final rules. A detailed discussion on the standardized budget neutral Federal per diem base rate and the ECT payment per treatment appears in the FY 2014 IPF PPS update notice (78 FR 46738 through 46740). These documents are available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​index.html.

As discussed in section III.B.2 of this proposed rule, we are proposing to revise the patient-level adjustment factors and increase the ECT payment amount for FY 2025. Section 1866(s)(5)(D)(iii) of the Act, as added by section 4125(a) of the CAA, 2023, requires that revisions to the IPF PPS adjustment factors must be made budget-neutrally. Therefore, as discussed in section III.F of this proposed rule, we are proposing to apply a standardization factor to the FY 2025 base rate that takes these refinements into account to keep total IPF PPS payments budget neutral.

2. Proposed Increase in the Electroconvulsive Therapy (ECT) Payment per Treatment

a. Background

In the RY 2005 IPF PPS final rule (69 FR 66951), we analyzed the costs of IPF stays that included ECT treatment using the FY 2002 MedPAR data. based on comments we received on the RY 2005 IPF PPS proposed rule. Consistent with the comments we received about ECT, our analysis and review indicated that cases with ECT treatment are substantially more costly than cases without ECT treatment. Based on this analysis, in that final rule we finalized an additional payment for each ECT treatment furnished during the IPF stay. This ECT payment per treatment is made in addition to the per diem and outlier payments under the IPF PPS. To receive the payment per ECT treatment, IPFs must indicate on their claims the revenue code and procedure code for ECT (Rev Code 901; procedure code 90870) and the number of units of ECT, that is, the number of ECT treatments the patient received during the IPF stay.

To establish the ECT per treatment payment, we used the pre-scaled and pre-adjusted median cost for procedure code 90870 developed for the Hospital Outpatient Prospective Payment System (OPPS), based on hospital claims data. We explained in the RY 2005 IPF PPS final rule that we used OPPS data because after a careful review and analysis of IPF claims, we were unable to separate out the cost of a single ECT treatment (69 FR 66922). We used the unadjusted hospital claims data under the OPPS because we did not want the ECT payment under the IPF PPS to be affected by factors that are relevant to OPPS, but not specifically applicable to IPFs. The median cost was then standardized and adjusted for budget neutrality. We also adjusted the ECT rate for wage differences in the same manner that we adjust the per diem rate.

Since the ECT payment rate was established in the RY 2005 IPF PPS rule, it has been updated annually by application of each year's market basket, productivity adjustment, and wage index budget neutrality factor to the previous year's ECT payment rate (referred to as our “standard methodology” in this section). While the ECT payment rate has been updated each year by these factors, we have not recalculated the ECT payment per treatment based on more recent cost data since the establishment of the IPF PPS.

b. Proposed Increase to the Electroconvulsive Therapy Payment per Treatment

For this FY 2025 IPF PPS proposed rule, we analyzed data in both the IPF PPS and the OPPS. In the IPF PPS setting, our analysis of recent IPF PPS data indicates that IPF costs have increased for stays that include ECT treatments. As discussed in the next paragraph, our analysis of these costs leads us to consider whether the current payment per treatment for ECT is aligned with the additional costs associated with stays that include ECT treatments. We began by analyzing IPF stays with ECT treatment using the CY 2022 Medicare Provider and Analysis Review (MedPAR) data. IPF stays with ECT treatment comprised about 1.7 percent of all stays, which is a decrease from the FY 2002 MedPAR data discussed in the RY 2005 IPF PPS final rule, where stays with ECT treatment were 6.0 percent of all IPF stays. A total of 288 IPF facilities had stays with ECT treatment in 2022, with an average 6.7 units of ECT per stay. We compared the total cost for stays with and without ECT treatment, and found that IPF stays with ECT treatment were approximately three times more costly than IPF stays without ECT treatment ($44,687.50 per stay vs. $15,432.30 per stay). Most of the variance in cost was due to differences in the IPF length of stay (LOS) (28.00 days for stays with ECT treatment vs. 13.43 days for stays without ECT treatment). We note that the IPF PPS makes additional per diem payments for longer lengths of stay, which makes the total payment larger for a longer stay. However, we also observed that there are differences in the per-day cost for stays with and without ECT. We calculated the average cost per day for stays with and without ECT treatment and found that stays with ECT treatment have an average cost per day of $1,595.76, while stays without ECT treatment have an average cost per day of $1,149.51.

Furthermore, as we discuss in section III.C.3.d.(2) of this proposed rule, our latest regression analysis includes a control variable to account for the presence of ECT during an IPF stay. That control variable indicates that, holding all other patient-level and facility-level factors constant, there is a statistically significant increase in cost per day for IPF stays that include ECT, further demonstrating that resource use is higher for IPF stays with ECT than those without ECT. As we previously noted in the RY 2005 IPF PPS final rule (69 FR 66922), IPF claims and cost data are not sufficiently granular to identify the per-treatment cost of ECT. Therefore, we examined the difference in ancillary costs for IPF stays with and without ECT treatment. In the CY 2022 MedPAR data, the ancillary costs per IPF stay with ECT treatment were $7,116.85 higher than ancillary costs per IPF stay without ECT treatment. The ancillary costs were calculated as follows: for each ancillary department (for example, drugs or labs), the charges were multiplied by the department-level CCR, and those department-level costs were summed across departments for each stay. The average ancillary costs per stay were calculated accordingly for stays with and without ECT treatment, revealing that average ancillary costs per day are three times higher for stays with ECT treatment: $99.36 for stays without ECT treatment versus $301.77 for stays with ECT treatment. Accounting for differences in length of stay between stays with and without ECT, the average additional ancillary cost per ECT unit was approximately $849.72.

Application of our standard methodology for updating the ECT payment would result in an FY 2025 payment of $377.54 per ECT treatment (based on the FY 2024 ECT payment amount of $385.58, increased by the market basket update of 2.7 percent and reduced by the FY 2025 wage index budget neutrality factor of 0.9998 and a refinement standardization factor of 0.9536, which is the standardization factor that would account for all other proposed refinements without increasing the ECT per treatment). As we noted above, this ECT payment would be added to the per diem and any applicable outlier payments for the entire stay. CMS considered this rate in proposing to adjust the ECT per treatment rate. However, the analysis of ancillary costs for IPF stays with ECT treatment suggested that a further increase to the current ECT payment amount per treatment could better align IPF PPS payments with the increased costs of furnishing ECT. The ancillary cost data show that costs for furnishing ECT have risen by a factor greater than the standard methodology for updating the rate would adjust for.

It continues to be the case that, as we discussed in the RY 2005 IPF PPS final rule, current IPF cost and claims data are not sufficiently granular to identify the per-treatment cost of ECT. We believe that using the costs in the OPPS setting are the most accurate for purposes of updating the ECT per treatment rate because we believe this treatment requires comparable resources when performed in outpatient and inpatient settings. Thus, we analyzed the most recent OPPS cost information to consider changes to the ECT payment per treatment for FY 2025.

The original methodology for determining the ECT payment per treatment was based on the median cost for procedure code 90870 developed for the OPPS, as discussed in the RY 2005 IPF PPS final rule (69 FR 66951). Since that time, the OPPS has adopted certain changes to its methodology for calculating costs. In the CY 2013 OPPS/ASC final rule with comment period (77 FR 68259 through 68270), CMS finalized a methodology for developing the relative payment weights for Ambulatory Payment Classifications using geometric mean costs instead of median costs. We explained that geometric means better capture the range of costs associated with providing services, including those cases where very efficient hospitals have provided services at much lower costs. While medians and geometric means both capture the impact of uniform changes, that is, those changes that influence all providers, only geometric means capture cost changes that are introduced slowly into the system on a case-by-case or hospital-by-hospital basis, allowing us to detect changes in the cost of services earlier.

We believe the rationale for using geometric mean cost in the OPPS setting as the underpinning methodology for establishing payments applies equally to the costs of providing ECT on a per treatment basis under the IPF PPS. Therefore, in considering changes for the IPF PPS ECT payment per treatment for FY 2025, we compared the costs observed in the IPF setting to the geometric mean cost for an ECT treatment posted as part of the CY 2024 OPPS/ASC update, which is based on CY 2022 outpatient hospital claims. Although we are proposing to increase the ECT payment with reference to the CY 2024 OPPS ECT geometric mean cost for FY 2025, we are not proposing to adopt the OPPS rate (which is distinct from the geometric mean cost) for the ECT payment per treatment for FY 2025 because the final OPPS rates include policy decisions and payment rate updates that are specific to the OPPS. We intend to continue to monitor the costs associated with ECT treatment and may propose adjustments in the future as needed.

The pre-scaled and pre-adjusted CY 2024 OPPS geometric mean cost for ECT is $675.93. Comparatively, the FY 2024 IPF ECT payment rate was $385.58 (88 FR 51054). As discussed in the prior paragraphs, our analysis of updated ancillary cost data indicates that the IPF PPS ECT payment rate per treatment, when updated according to the standard methodology alone, has not kept pace with the cost of furnishing the treatment in the IPF setting. As we stated previously, we believe this treatment requires comparable resources when performed in outpatient and inpatient settings. Therefore, we are proposing to use the pre-scaled and pre-adjusted CY 2024 OPPS geometric mean cost of $675.93 as the basis for the IPF PPS ECT payment per treatment in FY 2025, as discussed below. We are proposing to update $675.93 by the FY 2025 IPF PPS payment rate update of 2.7 percent (3.1 percent IPF market basket increase, reduced by the 0.4 percentage point productivity adjustment), and the wage index budget neutrality factor of 0.9998 for FY 2025, in alignment with our current standard methodology.

To account for budget neutrality, as discussed in section III.F of this proposed rule, we are proposing to apply a refinement standardization factor to the FY 2025 IPF PPS Federal per diem base rate and to the ECT payment amount per treatment to account for this proposed change to the ECT payment amount per treatment and all proposed changes to the patient-level adjustment factors and to the ED adjustment factor for FY 2025. We note that this proposed increase to the ECT per treatment amount would be associated with a minor decrease to the IPF Federal per diem base rate as a result of the refinement standardization factor (0.9514 instead of 0.9536). We estimate that this change would increase payments for IPFs that provide ECT, and would decrease payments for IPFs that do not provide ECT. However, the decrease in payments associated with this change would be no more than approximately 0.2 percent, which would be offset by various other proposed changes such as the proposed wage index changes, proposed revisions to the IPF PPS patient-level adjustments, and the proposed market basket increase for FY 2025.

We note that we have monitored the provision of ECT through analysis of claims data since the beginning of the IPF PPS, and have not observed any indicators that payment is inappropriately incentivizing the provision of ECT to IPF patients. We intend to continue monitoring the provision of ECT through further analysis of IPF PPS claims data.

A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule. We welcome comments regarding our analysis, including any comments that could inform our understanding of where ECT costs are allocated in cost reports in order to potentially inform improved collection of data on ECT treatment costs in the IPF setting. We also welcome comments on whether it may be appropriate to collect additional ECT-specific costs on the hospital cost report. Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 Federal per diem base rate and ECT payment per treatment for the FY 2025 IPF PPS final rule.

IPFs must include a valid procedure code for ECT services provided to IPF beneficiaries to bill for ECT services, as described in our Medicare Claims Processing Manual, Chapter 3, Section 190.7.3 (available at https://www.cms.gov/​Regulations-and-Guidance/​Guidance/​Manuals/​Downloads/​clm104c03.pdf). There were no changes to the ECT procedure codes used on IPF claims in the final update to the ICD-10-PCS code set for FY 2024. Addendum B to this proposed rule shows the ECT procedure codes for FY 2025 and is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.

3. Proposed Update of the Federal per Diem Base Rate and Electroconvulsive Therapy Payment per Treatment

The current (FY 2024) Federal per diem base rate is $895.63 and the ECT payment per treatment is $385.58. For the proposed FY 2025 Federal per diem base rate, we applied the payment rate update of 2.7 percent,—that is, the proposed 2021-based IPF market basket increase for FY 2025 of 3.1 percent reduced by the proposed productivity adjustment of 0.4 percentage point—the proposed wage index budget neutrality factor of 0.9998 (as discussed in section III.D.1 of this proposed rule), and a proposed refinement standardization factor of 0.9514 (as discussed in section III.F of this proposed rule) to the FY 2024 Federal per diem base rate of $895.63, yielding a proposed Federal per diem base rate of $874.93 for FY 2025. As discussed in section III.B.2 of this proposed rule, we are proposing to increase the ECT payment per treatment for FY 2025 in addition to our routine updates to the rate. We applied the proposed 2.7 percent payment rate update, the proposed 0.9998 wage index budget neutrality factor, and the proposed 0.9514 refinement standardization factor to the proposed payment per treatment based on the CY 2024 OPPS geometric mean cost of $675.93, yielding a proposed ECT payment per treatment of $660.30 for FY 2025.

Section 1886(s)(4)(A)(i) of the Act requires that for RY 2014 and each subsequent RY, in the case of an IPF that fails to report required quality data with respect to such RY, the Secretary will reduce any annual update to a standard Federal rate for discharges during the RY by 2.0 percentage points. Therefore, we are applying a 2.0 percentage point reduction to the annual update to the Federal per diem base rate and the proposed ECT payment per treatment as follows:

• For IPFs that fail to report required data under the IPFQR Program, we would apply a 0.7 percent payment rate update—that is, the proposed IPF market basket increase for FY 2025 of 3.1 percent reduced by the proposed productivity adjustment of 0.4 percentage point for an update of 2.7 percent, and further reduced by 2.0 percentage points in accordance with section 1886(s)(4)(A)(i) of the Act. We would also apply the proposed refinement standardization factor of 0.9514 and the proposed wage index budget neutrality factor of 0.9998 to the FY 2024 Federal per diem base rate of $895.63, yielding a proposed Federal per diem base rate of $857.89 for FY 2025.
• For IPFs that fail to report required data under the IPFQR Program, we would apply the proposed 0.7 percent annual payment rate update, the proposed 0.9514 refinement standardization factor, and the proposed 0.9998 wage index budget neutrality factor to the proposed payment per treatment based on the CY 2024 OPPS geometric mean cost of $675.93, yielding a proposed ECT payment per treatment of $647.45 for FY 2025.

We are proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 Federal per diem base rate and ECT payment per treatment for the FY 2025 IPF final rule.

C. Proposed Updates and Revisions to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors and Proposed Revisions

The current (FY 2024) IPF PPS payment adjustment factors were derived from a regression analysis of 100 percent of the FY 2002 Medicare Provider and Analysis Review (MedPAR) data file, which contained 483,038 cases. For a more detailed description of the data file used for the regression analysis, we refer readers to the RY 2005 IPF PPS final rule (69 FR 66935 through 66936).

For FY 2025, we are proposing to implement revisions to the methodology for determining payment rates under the IPF PPS. As we noted earlier in this FY 2025 IPF PPS proposed rule, section 1886(s)(5)(D) of the Act, as added by section 4125(a) of the CAA, 2023 requires that the Secretary implement revisions to the methodology for determining the payment rates under the IPF PPS for psychiatric hospitals and psychiatric units, effective for RY 2025 (FY 2025). The revisions may be based on a review of the data and information collected under section 1886(s)(5)(A) of the Act. Accordingly, we are proposing to revise the patient-level IPF PPS payment adjustment factors as discussed in section III.C.4. of this proposed rule, effective for FY 2025. We have developed proposed adjustment factors based on a regression analysis of IPF cost and claims data, which is discussed in greater detail in the following sections of this proposed rule. The primary sources of this analysis are CY 2019 through 2021 MedPAR files and Medicare cost report data (CMS Form 2552-10, OMB No. 0938-0050) ^[1] from the FY 2019 through 2021 Hospital Cost Report Information System (HCRIS). For each year (2019 through 2021), if a provider did not have a Medicare cost report for that year, we used the provider's most recent available Medicare cost report prior to the year for which a Medicare cost report was missing, going back to as early as 2018. Section III.C.3 of this proposed rule discusses the development of the proposed revised case-mix adjustment regression.

2. History of IPF PPS Cost and Claims Analyses

In the FY 2023 IPF PPS proposed rule (87 FR 19428 through 19429), we briefly discussed past analyses and areas of interest for future refinement, about which we previously solicited comments. CMS also released a technical report posted to the CMS website ^[2] accompanying the rule, summarizing these analyses. In that same proposed rule, we described the results of the agency's latest analysis of the IPF PPS and solicited comments on certain topics from the report. We summarized the considerations and findings related to our analyses of the IPF PPS adjustment factors in the FY 2023 IPF PPS final rule (46864 through 46865).

In the FY 2024 IPF PPS proposed rule (88 FR 21269 through 21272), we requested information from the public to inform revisions to the IPF PPS required by the CAA, 2023. Specifically, we sought information about which data and information would be most appropriate and useful for the purposes of refining IPF PPS payments. We requested information related to the specific types of data and information mentioned in the CAA, 2023. We also solicited comments on the reporting of ancillary charges, such as labs and drugs, on IPF claims. Lastly, we presented and solicited comments on the latest results of our analysis of social drivers of health (SDOH).

In response to the requests for information, commenters offered a number of suggestions for further analysis, including recommendations to consider adjusting payment for patients with sleep apnea, violent behavior, and patients that transfer from an acute care unit. We discuss the analysis conducted and our findings, as related to patient-level adjustment factors, in section III.C.3 of this proposed rule.

The primary goal in refining the IPF PPS payment adjustment factors is to pay each IPF an appropriate amount for the efficient delivery of care to Medicare beneficiaries. The system must be able to account adequately for each IPF's case-mix to allow for both fair distribution of Medicare payments and access to adequate care for those beneficiaries who require more costly care. As required by section 1886(s)(5)(D)(iii) of the Act, as added by section 4125(a) of the CAA, 2023, proposed revisions to the IPF PPS adjustment factors must be budget neutral. As discussed in section III.F of this proposed rule, we are applying a refinement standardization factor to the proposed IPF PPS payment rates to maintain budget neutrality for FY 2025.

3. Development of the Proposed Revised Case-Mix Adjustment Regression

To ensure that the IPF PPS continues to account adequately for each IPF's case-mix, we performed an extensive regression analysis of the relationship between the per diem costs and both patient and facility characteristics to identify those characteristics associated with statistically significant cost differences. We discuss the results of this regression analysis in section III.C.3.e. of this proposed rule. We further discuss proposed revisions to the IPF PPS patient-level adjustment factors based on this regression analysis in section III.C.4 of this proposed rule.

As discussed in greater detail in section III.C.3.c. of this proposed rule, we computed a per diem cost for each Medicare inpatient psychiatric stay, including routine operating, ancillary, and capital components using information from the CY 2019 through CY 2021 MedPAR files and data from the 2019 through 2021 Medicare cost reports, backfilling with Medicare cost reports from the most recent prior year when necessary.

We began with a 100 percent sample of the CY 2019 through CY 2021 MedPAR data files, which contain a total of 1,111,459 stays from 1,684 IPFs. As discussed in section III.C.3.b. of this proposed rule, we applied several data restrictions and exclusions to obtain the set of data used for our regression analysis. The MedPAR data files used for this regression analysis contain a total of 806,611 stays from 1,643 IPFs, which reflect the removal of 41 providers and 304,848 stays with missing or erroneous data. To include as many IPFs as possible in the regression, we used the cost report information for each provider corresponding to the year of claims, when available, and substituted the most recent prior available cost report information for routine cost and ancillary cost to charge ratios if the corresponding year's data was not available.

a. Data Sources

For the regression analysis, we chose to use a combined set of CY 2019 through 2021 MedPAR data. Our analysis showed that using a combined set of data from multiple years yields the most stable and consistent result. When we looked at the results for each year individually, we found that some DRGs and comorbidity categories were not statistically significant due in part to small sample size. In addition, during FY 2020, the U.S. healthcare system undertook an unprecedented response to the Public Health Emergency (PHE) declared by the Secretary of the Department of Health and Human Services on January 31, 2020 in response to the outbreak of respiratory disease caused by a novel (new) coronavirus that has been named “SARS CoV 2” and the disease it causes, which has been named “coronavirus disease 2019” (abbreviated “COVID-19”). We believe the aggregated three-year regression serves to smooth the impact of changes in utilization driven by the COVID-19 PHE, as well as significant changes in staffing and labor costs that commenters noted in response to the FY 2023 and FY 2024 IPF PPS proposed rules. As discussed earlier in this proposed rule, we used 2019 through 2021 Medicare cost report data to retain as many records as possible for analysis.

We also used several other data sources to identify the IPF population for analysis and to construct variables in the regression model:

• Provider of Services (POS) File: The POS file contains facility characteristics including name, address, and types of services provided.

• Provider Specific Data for Public Use Files for the IPF PPS: The Provider Specific File (PSF) contains data used to calculate COLA factors and identify the Core-Based Statistical Area (CBSA). CBSA is used to match providers with corresponding wage index data, which is used to adjust the calculation of the Federal per diem base rate to account for geographic differences in costs.

• Common Working File (CWF) Inpatient Claims Data: The CWF contains data regarding ECT treatments provided during an IPF stay.

Among the 1,643 providers included in the regression analysis sample, the majority had their most recent Medicare cost report information corresponding to the year of the MedPAR data file. Specifically, for the CY 2019 MedPAR data file, 99.5 percent (1,551 providers) used FY 2019 Medicare cost reports, and 0.5 percent (8 providers) used FY 2018 Medicare cost reports. For CY 2020, 99.7 percent (1,523 providers) used FY 2020 Medicare cost reports, and 0.3 percent (5 providers) used FY 2019 Medicare cost reports. For CY 2021, 97.6 percent (1,435 providers) used FY 2021 Medicare cost reports, and 2.4 percent (35 providers) used FY 2020 Medicare cost reports. This approach allowed us to use the most current and relevant cost report data, ensuring the robustness and accuracy of our analysis.

b. Trims and Assumptions

To identify the IPF population for analysis, we matched MedPAR records to facility-level information from Medicare cost reports, the POS file, and the PSF. We included MedPAR stays that met the following criteria:

• Hospital CMS Certification Number (CCN) contains “40,” “41,” “42,” “43,” or “44” in the third and fourth position or a special unit code of “S” or “M” for psychiatric unit or psychiatric unit in a critical access hospital.
• Beneficiary primary payer code is equal to “Z” or blank, indicating Medicare is the primary payer.
• Group Health Organization (GHO) paid code is equal to zero or blank, indicating that a GHO has not paid the facility for the stay.
• National Claims History (NCH) claim type code is equal to “60,” an inpatient claim.
• Number of utilization days was greater than zero.

To promote the accuracy and completeness of data included in the regression model, we completed a series of trimming steps to remove missing and outlier data. Before any trims or exclusions were applied, there were 1,684 providers in the MedPAR data file. First, we matched facilities from the MedPAR dataset to the most recent Medicare cost report file available from CY 2018 to CY 2021, and excluded facilities that did not have a Medicare cost report available from 2018 to 2021. If facilities had more than one Medicare cost report in a given year, we used the Medicare cost report representing the longest time span. We identified 1 provider in CY 2019, 5 providers in CY 2020, and 4 providers in CY 2021 that had no available Medicare cost report information. In total, we excluded data from 5 unique providers that had no available Medicare cost report information from CY 2019 to CY 2021.

Next, we trimmed facilities with extraordinarily high or low costs per day. We removed facilities with outlier routine per diem costs, defined as those falling outside of the range of the mean logarithm of routine costs per diem plus or minus 3.00 standard deviations. We also removed stays with outlier total per diem costs, defined as those falling outside the range of the mean per diem cost by facility type (psychiatric hospitals and psychiatric units) plus or minus 3.00 standard deviations. The average and standard deviations of the total per diem cost (routine and ancillary costs) were computed separately for stays in psychiatric hospitals and psychiatric units because we did not want to systematically exclude a larger proportion of cases from one type of facility. In applying these trims across all three data years used in our regression model, there were 104 providers with routine per diem costs outside 3.00 standard deviations from the mean, and 47 providers with total per diem costs outside 3.00 standard deviations from the mean. Specifically, this includes 24 providers in CY 2019, 41 providers in CY 2020, and 39 providers in CY 2021 excluded for outlier routine per diem costs. We identified 25 providers in CY 2019, 1 provider in CY 2020, and 21 providers in CY 2021 that we excluded for outlier total per diem costs. In total, we excluded data from 23 unique providers with outlier routine per diem costs and 8 unique providers with outlier total per diem costs.

We also removed stays at providers without a POS file or PSF. There were 5 providers without a POS file or PSF during the period CY 2019 to CY 2021; therefore, we are excluding data from these 5 providers. Only 1 unique provider was entirely excluded with no POS file or PSF from CY 2019 to CY 2021. Additionally, 1 provider was excluded because no stays had one of the recognized IPF PPS DRGs assigned.

In summary, the application of these data preparation steps resulted in excluding 5 providers because they did not have a cost report available from 2018 to 2021, 23 providers with routine per diem costs outside 3.00 standard deviations from the mean, and 8 providers with total per diem costs outside 3.00 standard deviations from the mean. We also excluded 1 provider without a POS file or PSF, 1 provider with no stays with IPF PPS DRGs, and 3 providers based on IPF stays restrictions. In total, the exclusion of these 41 providers resulted in the removal of 304,848 stays from our original total of 1,111,459 stays.

We considered trimming stays from facilities where 95 percent or more of stays had no ancillary charges because we assumed that the cost data from these facilities were inaccurate or incomplete. This is the trimming methodology that we applied to the analysis described in the technical report released along with the FY 2023 IPF PPS proposed rule. As previously discussed, the IPF PPS regression model uses the sum of routine and ancillary costs as the dependent variable, and we assumed that data from facilities without ancillary charge data would be inadequate to capture variation in costs. When we examined the claims from 2018, which we used for prior analysis, this trimming step resulted in removing almost one-quarter of total stays from the unrestricted 2018 MedPAR dataset (82,491 out of 364,080 total stays). This trimming step also resulted in disproportionate exclusion of certain types of facilities, particularly freestanding psychiatric hospitals that were for-profit or government-operated, as well as all-inclusive rate providers. Approximately 55 percent of stays from freestanding facilities would be removed, compared to just 0.3 percent of stays in psychiatric units. In the analysis described in the FY 2023 IPF PPS proposed rule (87 FR 19429), we attempted to address this disproportionate removal of stays by facility type by applying weights by facility type and ownership in the regression model to account for excluded providers and to avoid biasing the sample towards stays from providers in psychiatric units.

In response to the analysis described in the FY 2023 IPF PPS proposed rule (87 FR 19429), commenters raised concerns about the large number of stays excluded from the regression analysis, and questioned whether the ancillary charge data were truly missing, as all-inclusive rate providers are not required to report separate ancillary charges. We agree that this trimming step reduces the representativeness of the IPF population used in the regression model and may increase the potential for bias of the regression coefficients used for payment adjustments. Furthermore, as discussed in section III.E.4. of this proposed rule, we are clarifying cost reporting requirements and implementing operational changes that we believe will increase the accuracy of the cost information reported in the future. Specifically, CMS will issue instructions to the MACs and put in place edits for cost reporting periods beginning on or after October 1, 2024, ensuring that only government-owned or tribally owned IPF hospitals will be permitted to file an all-inclusive cost report. All other IPF hospitals would be required to have a charge structure and to report ancillary costs and charges on their cost reports. We expect that this proposed change would support increased accuracy of future payment refinements to the IPF PPS.

When we examined the claims from CY 2019 to CY 2021, this trimming step would have resulted in a loss of a significant number of providers (324 providers in CY 2019, 330 providers in CY 2020, and 336 providers in CY 2021). Due to the concerns that commenters previously raised (which we summarized in the FY 2024 IPF PPS final rule (88 FR 51097 through 51098)), and to include as many claims as possible in the regression analysis, we have not trimmed stays from facilities with zero or minimal ancillary charges. As a result, we observed a significant reduction in data loss when comparing our latest regression model with the model described in the FY 2023 IPF PPS proposed rule. By including, rather than trimming, facilities with low or no ancillary charge data, we prevented the loss of 288 providers across the three years, allowing for a more inclusive analysis. These providers accounted for approximately 194,673 stays included in our data set.

We present our regression results in section III.C.3.e. of this proposed rule without the application of any trimming or subsequent weighting to account for the removal of stays from facilities with zero or minimal ancillary charges.

c. Calculation of the Dependent Variable

The IPF PPS regression model uses the natural logarithm of per diem total cost as the dependent variable. We computed a per diem cost for each Medicare inpatient psychiatric stay, including routine operating, ancillary, and capital components, using information from the combined CY 2019 through 2021 MedPAR file and data from the 2018 through 2021 Medicare cost reports. For each MedPAR CY, we examined the corresponding Medicare cost report, and if a provider's cost-to-charge ratio was missing from the matching year's cost report, we looked at the provider's cost report from the prior year to obtain the most recent cost-to-charge value for the provider. We applied a prior-year cost-to-charge ratio to 8 providers from the CY 2019 MedPAR claims, 5 providers from the CY 2020 MedPAR claims, and 35 providers from the CY 2021 MedPAR claims.

To calculate the total cost per day for each inpatient psychiatric stay, routine costs were estimated by multiplying the routine cost per day from the IPF's Medicare cost report (Worksheet D-1, Part II, column 1, line 38) by the number of Medicare covered days in the MedPAR stay record. Ancillary costs were estimated by multiplying each departmental cost-to-charge ratio (calculated by dividing the amount obtained from Worksheet C, columns 5, by the sum of Worksheet C, columns 6 and 7) by the corresponding ancillary charges in the MedPAR stay record. The total cost per day was calculated by summing routine and ancillary costs for the stay and dividing it by the number of Medicare covered days for each day of the stay.

To address extreme cost-to-charge ratios, we winsorized the distributions of the 17 ancillary cost centers from Worksheet C of the cost report at the 2nd and 98th percentiles. That is, if the cost-to-charge ratio was missing and there was a charge on the claim, the cost-to-charge ratio was imputed to the calculated median value for each respective cost center.

The total cost per day (also referred to as per diem cost) was adjusted for differences in cost across geographic areas using the FY 2019 through 2021 IPF wage index and COLA corresponding to each MedPAR data year. We adjusted the labor-related portion of the per diem cost using the IPF wage index to account for geographic differences in labor cost and adjusted the non-labor portion of the per diem cost by the COLA adjustment factors for IPFs in Alaska and Hawaii. We used IPF PPS labor-related share and non-labor-related share finalized for each year, FY 2019 through FY 2021, to determine the amount of the per diem cost that is adjusted by the wage index and the COLA, respectively. We calculated the adjusted cost using the following formula:

Wage adjusted per diem cost = per diem cost/(wage index * labor-related share + COLA * (1-labor-related share)).

d. Independent Variables

Independent variables in the regression model are patient-level and facility-level characteristics that affect the dependent variable in the model, which is per diem cost. As discussed in the following sections, the updated regression model for this proposed rule includes adjustment-related variables and control variables. Adjustment related variables are used for adjusting payment, and as we discuss in section III.C.4 of this proposed rule, we are proposing to revise the IPF PPS patient-level adjustment factors based on the regression results for many of the adjustment-related variables in the model. Control variables are used to account for variation in the dependent variable that is associated with factors outside the adjustment factors of the payment model.

(1) Adjustment-Related Variables

Patient-level adjustment-related variables included in the regression model are variables for DRG assignment, comorbidity categories, age, and length of stay. We note that facility-level adjustment-related variables for rural status and teaching status are also included in the model; however, we are not proposing revisions to the rural or teaching adjustments for FY 2025. We discuss the latest results of the regression analysis for facility-level adjustments in greater detail in section IV.A. of this proposed rule.

(2) Control Variables

The regression model used to determine IPF PPS payment adjustments in the RY 2005 IPF PPS final rule (69 FR 66922) included control variables to account for facilities' occupancy rate, a control variable to indicate if the patient received ECT, and a control variable for IPFs that do not bill for ancillary charges. In the updated regression model for this FY 2025 IPF PPS proposed rule, we have removed the occupancy control variables and the control variable for IPFs that do not bill for ancillary charges. In addition, we have retained the control variable for patients receiving ECT and added control variables for the data year. We also added a control variable for the presence of ED charges on the claim. We discuss considerations related to these control variables and others in the following paragraphs.

The 2004 regression model included two control variables for occupancy rate. One was a continuous variable for the facility's logarithmic-transformed occupancy rate. The other was a categorical variable indicating a facility had an occupancy rate below 30 percent. Both of these variables were found to be associated with statistically significant increases in cost. In the RY 2005 IPF PPS final rule, we adopted the structural approach and included these control variables in the regression. We explained that it was appropriate to control for variations in the occupancy rate in estimating the effects of the payment variables on per diem cost to avoid compensating facilities for inefficiency associated with underutilized fixed costs (69 FR 66934). As we discussed in the FY 2023 IPF PPS proposed rule, our analysis found that the occupancy control variables were associated with rural status. We solicited comments on the potential removal of the occupancy control variables from the model (87 FR 19429). In response, we received several comments in support of removing the occupancy control variables, due to the relationship between these control variables and the rural adjustment (87 FR 46865). Commenters cited the importance of rural IPFs as the primary points of care and access for many Medicare beneficiaries who cannot travel to urban areas for mental health services. We considered the potential negative impact to rural facilities of retaining the occupancy control variables in the regression model. We agree with the commenters who noted the importance of maintaining stability in payments for rural IPFs; therefore, we did not include any occupancy control variables in our regression model.

In addition, we considered including a control variable for IPFs that do not bill for ancillary services. As we discussed in the RY 2005 IPF PPS final rule (69 FR 66936), we included variables in the regression to control for psychiatric hospitals that do not bill ancillary costs. However, at that time, the number of IPFs who did not bill for ancillary costs was relatively small and consisted mostly of government-operated facilities. As we discuss later in section III.E.4 of this proposed rule, an increasing number of IPFs have stopped reporting ancillary charges on their claims, which means that ancillary cost information is not available for stays at these IPFs.

We considered whether to include a control variable for facilities that do not report ancillary charges. We considered that the inclusion of a control variable would only account for differences in the level of cost between IPFs with and without reported ancillary costs and would not facilitate comparison of costs between all IPFs in our sample. In addition, we found that facilities that did not report ancillary charges also tended to have lower routine costs; that is, our analysis showed that these facilities would have overall lower costs per day, regardless of whether ancillary costs were considered in the cost variable. We considered that the inclusion of a control variable in the regression model would account for these differences in overall cost, which would impact the size of payment-related adjustment factors that are correlated with the prevalence of missing ancillary charge data. For this reason, in developing a regression model for proposing revisions to the IPF PPS, we did not include a control variable to account for facilities that report zero or minimal ancillary charges.

As noted earlier, the original model also included a control variable for the presence of ECT. This is because ECT is paid on a per-treatment basis under the IPF PPS. As discussed in more detail in section III.B.2. of this FY 2025 IPF PPS proposed rule, we continue to observe that IPF stays with ECT have significantly higher costs per day. We are proposing to continue paying for ECT on a per-treatment basis; therefore, we included a control variable to account for the additional costs associated with ECT, which would continue to be paid for outside the regression model.

Similarly, we included a control variable for stays with emergency department (ED)-related charges. The original model did not include an ED control variable, because ED costs were excluded from the dependent variable of IPF per diem costs. Our regression model for this FY 2025 IPF PPS proposed rule includes all costs associated with each IPF stay, including ED costs. As discussed in section III.D.4. of this proposed rule, we are proposing to calculate the ED adjustment in accordance with our longstanding methodology, separate from the regression model. However, we included a control variable for stays with ED charges to control for the additional costs associated with ED admissions, which are paid under the ED adjustment outside the regression model.

Lastly, we included control variables for the data year. Because the model used a combined set of data from 3 years, these control variables are included in the model to account for differences in cost levels between 2019, 2020, and 2021, which would be driven by economic inflation and other external factors unrelated to the independent variables in the regression model.

e. Regression Results

Table 2 presents the results of our regression model. We discuss these results and our related proposals to revise the IPF PPS patient-level adjustment factors in section III.C.4 of this proposed rule.

This regression model includes a total of 806,611 stays, and the r-squared value of the model is 0.32340, meaning that the independent variables included in the regression model can explain approximately 32.3 percent of the variation in per diem cost among IPF stays.

Except for the teaching variable, each of the adjustment factors in Table 2 is the exponentiated regression coefficient of our regression model, which as we previously noted uses the natural logarithm of per diem total cost as the dependent variable. We present the exponentiated regression results, as these most directly translate to the way that IPF PPS adjustment factors are calculated for payment purposes. That is, the exponentiated adjustment factors presented below represent a percentage increase or decrease in per diem cost for IPF stays with each characteristic. In the case of the teaching variable, the result in Table 2 is the un-exponentiated regression coefficient. As discussed in section III.D of this proposed rule, the current IPF PPS teaching adjustment is calculated as 1 + a facility's ratio of interns and residents to beds, raised to the power of 0.5150. The coefficient for teaching status presented in Table 2 can be interpreted in the same way.

For certain categorical variables, including DRG, age, length of stay, and the year control variables, results for the reference groups are not shown in Table 2. The DRG reference group is DRG 885, because this DRG represents the majority of IPF PPS stays. The age reference group is the Under 45 category, because this group is associated with the lowest costs after accounting for all other patient characteristics in the model. The reference group for length of stay is 10 days, which corresponds to the reference group used in the original regression model from the RY 2005 IPF PPS final rule. Lastly, the year control reference group is CY 2021. Each of these reference groups not shown in Table 2 effectively has an adjustment factor of 1.00 in the regression model.

As shown in Column 5 of Table 2, we considered the regression factors to be statistically significant when the p-value was less than or equal to the significance level of 0.05 (*), 0.01 (**), and 0.001 (***). Columns 6 and 7 of Table 2 show the lower and upper bounds of the 95-percent confidence interval (CI).

4. Proposed Updates and Revisions to the IPF PPS Patient-Level Adjustments

The IPF PPS includes payment adjustments for the following patient-level characteristics: Medicare Severity Diagnosis Related Groups (MS-DRGs) assignment of the patient's principal diagnosis, selected comorbidities, patient age, and the variable per diem adjustments. As discussed in section III.C.3. of this proposed rule, we are proposing to derive updated IPF PPS adjustment factors for FY 2025 using a regression analysis of data from the CY 2019 through 2021 MedPAR data files and Medicare cost report data from the 2018 through FY 2021 Hospital Cost Report Information System (HCRIS). However, we have used more recent claims (specifically, the December, 2023 update of the FY 2023 IPF PPS MedPAR claims) and cost data from the January, 2024 update of the provider-specific file (PSF) to simulate payments to finalize the outlier fixed dollar loss threshold amount and to assess the impact of the IPF PPS updates. More information about the data used for the impact simulations is found in section VIII.C of this FY 2025 IPF PPS proposed rule. As discussed in section III.C.3. of this proposed rule, by adjusting for DRGs, comorbidities, age, and length of the stay, along with the facility-level variables and control variables in the model, we were able to explain approximately 32.3 percent of the variation in per diem cost among IPF stays.

In addition, we are proposing routine coding updates for FY 2025 for our longstanding code first and IPF PPS comorbidities. Furthermore, as discussed in section III.C.4.a.(2) of this proposed rule, we are proposing to adopt a sub-regulatory process for future routine coding updates.

a. Proposed Updated and Revisions to MS-DRG Assignment

(1) Background

We believe it is important to maintain for IPFs the same diagnostic coding and DRG classification used under the IPPS for providing psychiatric care. For this reason, when the IPF PPS was implemented for cost reporting periods beginning on or after January 1, 2005, we adopted the same diagnostic code set (ICD-9-CM) and DRG patient classification system (MS-DRGs) that were utilized at the time under the IPPS. In the RY 2009 IPF PPS notice (73 FR 25709), we discussed CMS's effort to better recognize resource use and the severity of illness among patients. CMS adopted the new MS-DRGs for the IPPS in the FY 2008 IPPS final rule with comment period (72 FR 47130). In the RY 2009 IPF PPS notice (73 FR 25716), we provided a crosswalk to reflect changes that were made under the IPF PPS to adopt the new MS-DRGs. For a detailed description of the mapping changes from the original DRG adjustment categories to the current MS-DRG adjustment categories, we refer readers to the RY 2009 IPF PPS notice (73 FR 25714).

The IPF PPS includes payment adjustments for designated psychiatric DRGs assigned to the claim based on the patient's principal diagnosis. The DRG adjustment factors were expressed relative to the most frequently reported psychiatric DRG in FY 2002, that is, DRG 430 (psychoses). The coefficient values and adjustment factors were derived from the regression analysis discussed in detail in the RY 2004 IPF proposed rule (68 FR 66923; 66928 through 66933) and the RY 2005 IPF final rule (69 FR 66933 through 66960). Mapping the DRGs to the MS-DRGs resulted in the current 17 IPF MS-DRGs, instead of the original 15 DRGs, for which the IPF PPS provides an adjustment.

In the FY 2015 IPF PPS final rule published August 6, 2014 in the Federal Register titled, “Inpatient Psychiatric Facilities Prospective Payment System—Update for FY Beginning October 1, 2014 (FY 2015)” (79 FR 45945 through 45947), we finalized conversions of the ICD-9-CM-based MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which were implemented on October 1, 2015. Further information on the ICD-10-CM/PCS MS-DRG conversion project can be found on the CMS ICD-10-CM website at https://www.cms.gov/​medicare/​coding-billing/​icd-10-codes/​icd-10-ms-drg-conversion-project.

(2) Proposal To Adopt Sub-Regulatory Process for Publication of Coding Changes

As discussed in the FY 2015 IPF PPS proposed rule (79 FR 26047) every year, changes to the ICD-10-CM and the ICD-10-PCS coding system have been addressed in the IPPS proposed and final rules. The changes to the codes are effective October 1 of each year and must be used by acute care hospitals as well as other providers to report diagnostic and procedure information. In accordance with § 412.428(e), we have historically described in the IPF PPS proposed and final rules the ICD-10-CM coding changes and DRG classification changes that have been discussed in the annual proposed and final hospital IPPS regulations. This has typically involved a discussion in the proposed rule about coding updates to be effective October 1 of each year, with a summary of comments in the final rule along with a description of additional finalized codes for October.

In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44950 through 44956), we adopted an April 1 implementation date for ICD-10-CM diagnosis and ICD-10-PCS procedure code updates in addition to the annual October 1 update of ICD-10-CM diagnosis and ICD-10-PCS procedure codes, beginning with April 1, 2022. In that rule, we noted the intent of this April 1 implementation date is to allow flexibility in the ICD-10 code update process. Currently, as noted earlier in this proposed rule, the IPF PPS uses the IPPS DRG assignments, which are applied to IPF PPS claims; these DRG assignments reflect the change in process that the IPPS adopted for FY 2022. To maintain consistency with IPPS policy, we are proposing to follow the same process beginning in FY 2025. This means that for routine coding updates that incorporate new or revised codes, we are proposing to adopt these changes through a sub-regulatory process. Beginning in FY 2025, we would operationalize such coding changes in a Transmittal/Change Request, which would align with the way coding changes are announced under the IPPS.

For example, we are proposing that for April 2025, we would adopt routine coding updates for the IPF PPS comorbidity categories, code first policy, ECT code list, and DRG assignment via sub-regulatory guidance. These coding updates would take effect April 1, 2025. In accordance with § 412.428(e), we would describe these coding changes, along with any coding updates that would be effective for October 1, 2025, in the FY 2026 IPF PPS proposed rule. We would summarize and respond to any comments on these April and October coding changes in the FY 2026 IPF PPS final rule.

The proposed update aims to allow flexibility in the ICD-10 code update process for the IPF PPS and reduces the lead time for making routine coding updates to the IPF PPS code first list, comorbidities, and ECT coding categories. In addition, the IPPS sub-regulatory process continues to manage DRG assignment changes which apply to the DRG assignments used in the IPF PPS. Finally, we are clarifying that we would only apply this sub-regulatory process for routine coding updates. Any future substantive revisions to the IPF PPS DRG adjustments, comorbidities, code first policy, or ECT payment policy would be proposed through notice and comment rulemaking. We solicit public comments on this proposal.

(3) Routine Coding Updates for DRG Assignments

The diagnoses for each IPF MS-DRG will be updated as of October 1, 2024, using the final IPPS FY 2025 ICD-10-CM/PCS code sets. The FY 2025 IPPS/LTCH PPS final rule will include tables of the changes to the ICD-10-CM/PCS code sets that underlie the proposed FY 2025 IPF MS-DRGs. Both the FY 2025 IPPS final rule and the tables of final changes to the ICD-10-CM/PCS code sets, which underlie the FY 2025 MS-DRGs, will be available on the CMS IPPS website at https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​acute-inpatient-pps.

(4) Code First

As discussed in the ICD-10-CM Official Guidelines for Coding and Reporting, certain conditions have both an underlying etiology and multiple body system manifestations due to the underlying etiology. For such conditions, the ICD-10-CM has a coding convention that requires the underlying condition be sequenced first, followed by the manifestation. Wherever such a combination exists, there is a “use additional code” note at the etiology code, and a “code first” note at the manifestation code. These instructional notes indicate the proper sequencing order of the codes (etiology followed by manifestation). In accordance with the ICD-10-CM Official Guidelines for Coding and Reporting, when a primary (psychiatric) diagnosis code has a code first note, the provider will follow the instructions in the ICD-10-CM Tabular List. The submitted claim goes through the CMS processing system, which will identify the principal diagnosis code as non-psychiatric and search the secondary codes for a psychiatric code to assign a DRG code for adjustment. The system will continue to search the secondary codes for those that are appropriate for comorbidity adjustment. For more information on the code first policy, we refer readers to the RY 2005 IPF PPS final rule (69 FR 66945). We also refer readers to sections I.A.13 and I.B.7 of the FY 2020 ICD-10-CM Coding Guidelines, which is available at https://www.cdc.gov/​nchs/​data/​icd/​10cmguidelinesFY2020_​final.pdf. In the FY 2015 IPF PPS final rule, we provided a code first table for reference that highlights the same or similar manifestation codes where the code first instructions apply in ICD-10-CM that were present in ICD-10-CM (79 FR 46009). In FY 2018, FY 2019, and FY 2020, there were no changes to the final ICD-10-CM codes in the IPF Code First table. For FY 2021 and FY 2022, there were 18 ICD-10-CM codes deleted from the final IPF Code First table. For FY 2023, there were 2 ICD-10-CM codes deleted and 48 ICD-10-CM codes added to the IPF Code First table. For FY 2024, there were no proposed changes to the Code First Table.

We are proposing to continue our existing code first policy. As outlined in our proposal to incorporate a sub-regulatory process for the publication of coding changes, we are proposing to adopt a sub-regulatory approach to handle the coding updates, which removes the requirement to discuss coding updates in the Federal Register during regulatory updates prior to implementation, which would mirror the approach taken by the IPPS. The proposed FY 2025 Code First table is shown in Addendum B on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-forServicePayment/​InpatientPsychFacilPPS/​tools.html.

(5) Proposed Revisions to MS-DRG Adjustment Factors

For FY 2025, we are proposing to revise the payment adjustments for designated psychiatric DRGs assigned to the claim based on the patient's principal diagnosis, following our longstanding policy of using the ICD-10-CM/PCS-based MS-DRG system. As discussed in the following paragraphs, we are proposing to maintain DRG adjustments for 15 of the existing 17 IPF MS-DRGs for which we currently adjust payment in FY 2024. We are proposing to replace two existing DRGs with two new DRGs to reflect changes in coding practices over time and proposing to add two DRGs that are associated with poisoning. We are also proposing to revise the adjustment factors for the DRG adjustments as described in Table 3, based on the results of our latest regression analysis described in Section III.C.3 of this proposed rule. Addendum A is available on the CMS website at https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-psychiatric-facility/​tools-and-worksheets. The website includes the proposed DRG adjustment factors for FY 2025. In accordance with our longstanding policy, we are proposing that psychiatric principal diagnoses that do not group to one of the 19 proposed designated MS-DRGs would still receive the Federal per diem base rate and all other applicable adjustments; however, the payment would not include an MS-DRG adjustment.

(a) Proposed Replacement of DRGs

We are proposing to remove DRGs 080 (Nontraumatic stupor & coma w MCC) and 081 (Nontraumatic stupor & coma w/o MCC), and to replace these with DRGs 947 (Signs and Symptoms w MCC) and 948 (Signs and Symptoms w/out MCC). As previously discussed, we observed that the number of cases in DRGs 080 and 081 have decreased significantly since 2004. We selected DRGs 947 and 948 as the most clinically appropriate replacements, because most of the ICD-10-CM codes that previously grouped to DRGs 080 or 081 now group to DRGs 947 or 948. Table 3 compares the current adjustment factors for DRGs 080 and 081 to the regression-derived adjustment factors for DRGs 947 and 948. As shown in Table 3, the proposed adjustment factors for DRGs 947 and 948 would each be greater than the current DRG adjustment for DRGs 080 and 081. Therefore, we are proposing that claims with DRGs 080 or 081 would still receive the Federal per diem base rate and all other applicable adjustments; however, the payment would not include an MS-DRG adjustment.

As discussed in section III.F of this proposed rule, we are proposing to implement this revision to the DRG adjustments budget-neutrally. A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule. Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 DRG adjustment factors.

(b) Proposed Additions of DRGs

We are proposing to recognize DRG adjustments for two DRGs associated with poisoning; specifically, DRG 917 (Poisoning and toxic effects of drugs w MCC) and 918 (Poisoning and toxic effects of drugs w/out MCC). As discussed earlier in this proposed rule, we have identified that a small but increasing number of IPF stays contain these poisoning-related DRG assignments, and that stays with these DRGs have increased costs per day that are statistically significant. Table 4 summarizes the frequency of these stays and the proposed adjustment factors for FY 2025. As discussed in section III.F of this proposed rule, we are proposing to implement this revision to the DRG adjustments budget-neutrally. A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule.

Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 DRG adjustment factors.

(c) Proposed Revisions to Adjustment Factors for Existing DRG Adjustments

We are proposing to revise the adjustment factors for the remaining 15 of the existing 17 DRGs that currently receive a DRG adjustment in FY 2024. These proposed revisions are based on the results of our latest regression analysis described in section III.C.3 of this proposed rule.

As previously discussed, our analysis found that some of the adjustment factors in the regression model for DRGs that currently receive an adjustment are no longer statistically significant. Specifically, we found that the adjustment factors for DRG 882 (Neuroses except depressive), DRG 887 (Other mental disorder diagnoses), and DRG 896 (Alcohol, Drug Abuse or Dependence w/out rehab therapy w MCC) were not statistically significant. For each of these DRGs, we examined whether the current adjustment factor falls within the confidence interval for our latest regression analysis. The current adjustment for DRG 882 is 1.02, and this falls within the confidence interval of 0.96798 to 1.07811 for the latest regression model discussed in section III.C.3 of this proposed rule. We believe it would be appropriate to maintain the current adjustment factor of 1.02 for DRG 882, because the latest regression results indicate that the current adjustment factor would be a reasonable approximation of the increased costs associated with DRG 882. For DRGs 887 and 896; however, the current adjustment factors (0.92 and 0.88, respectively) do not fall within the confidence interval for each of these DRGs. Therefore, we are proposing to apply an adjustment factor of 1.00 for IPF stays with these DRGs.

Table 5 summarizes the frequency of these stays and the proposed adjustment factors for FY 2025. As discussed in section III.F of this proposed rule, we are proposing to implement this revision to the DRG adjustments budget-neutrally. A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule.

Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 DRG adjustment factors.

b. Proposed Payment for Comorbid Conditions

(1) Proposed Revisions to Comorbidity Adjustments

The intent of the comorbidity adjustments is to recognize the increased costs associated with comorbid conditions by providing additional payments for certain existing medical or psychiatric conditions that are expensive to treat.

Comorbidities are specific patient conditions that are secondary to the patient's principal diagnosis and that require treatment during the stay. Diagnoses that relate to an earlier episode of care and have no bearing on the current hospital stay are excluded and must not be reported on IPF claims. Comorbid conditions must exist at the time of admission or develop subsequently, and affect the treatment received, LOS, or both treatment and LOS.

The current comorbidity adjustments were determined based on the regression analysis using the diagnoses reported by IPFs in FY 2002. The principal diagnoses were used to establish the DRG adjustments and were not accounted for in establishing the comorbidity category adjustments, except where ICD-9-CM code first instructions applied. In a code first situation, the submitted claim goes through the CMS processing system, which identifies the principal diagnosis code as non-psychiatric and searches the secondary codes for a psychiatric code to assign an MS-DRG code for adjustment. The system continues to search the secondary codes for those that are appropriate for a comorbidity adjustment.

In our RY 2012 IPF PPS final rule (76 FR 26451 through 26452), we explained that the IPF PPS includes 17 comorbidity categories and identified the new, revised, and deleted ICD-9-CM diagnosis codes that generate a comorbid condition payment adjustment under the IPF PPS for RY 2012 (76 FR 26451).

As discussed in section C.4.a.(1) of this proposed rule, it is our policy to maintain the same diagnostic coding set for IPFs that is used under the IPPS for providing the same psychiatric care. The 17 comorbidity categories formerly defined using ICD-9-CM codes were converted to ICD-10-CM/PCS in our FY 2015 IPF PPS final rule (79 FR 45947 through 45955). The goal for converting the comorbidity categories is referred to as replication, meaning that the payment adjustment for a given patient encounter is the same after ICD-10-CM implementation as it would be if the same record had been coded in ICD-9-CM and submitted prior to ICD-10-CM/PCS implementation on October 1, 2015. All conversion efforts were made with the intent of achieving this goal.

For each claim, an IPF may receive only one comorbidity adjustment within a comorbidity category, but it may receive an adjustment for more than one comorbidity category. Current billing instructions for discharge claims, on or after October 1, 2015, require IPFs to enter the complete ICD-10-CM codes for up to 24 additional diagnoses if they co-exist at the time of admission, or develop subsequently and impact the treatment provided.

As previously discussed in section III.C.4.a.(2) of this proposed rule, we are proposing to adopt an April 1 implementation date for ICD-10-CM diagnosis and ICD-10-PCS procedure code updates, in addition to the annual October 1 update, beginning with April 1, 2025 for the IPF PPS. For FY 2025 and future years, coding updates related to the IPF PPS comorbidity categories would be adopted following a sub-regulatory process as discussed earlier in this proposed rule.

For FY 2025, we are proposing to revise the comorbidity adjustment factors based on the results of the 2019 through 2021 regression analysis described in section III.C.3.e. of this proposed rule. We are also proposing additions and changes to the comorbidity categories for which we adjust payment based on our analysis of ICD-10-CM codes currently included in each category as well as public comments received in response to the FY 2022 and FY 2023 IPF PPS proposed rules.

Based on analysis of the ICD-10-CM codes, we considered the statistical significance of the adjustment factor and whether the current (FY 2024) adjustment factor fell within the confidence interval in the 2019 through 2021 regression to determine the FY 2025 IPF PPS proposed comorbidity categories and adjustment factors. As previously discussed for the DRG adjustment factors, when the regression factor is not statistically significant, but the current adjustment factor is within the confidence interval, we are proposing to maintain the current adjustment factor. When a regression factor is not statistically significant and the current adjustment factor is not within the confidence interval, we are proposing to remove the comorbidity category.

Specifically, we are proposing to increase the adjustment factors for the Gangrene, Severe Protein Malnutrition, Oncology Treatment, Poisoning, and Tracheostomy comorbidity categories based on the adjustment factors derived from the regression analysis discussed in section III.C.3 of this proposed rule. For these comorbidity categories, the regression results produced a statistically significant increase in the adjustment factors.

We are proposing to remove the comorbidity categories for the Coagulation Factor Deficit, Drug/Alcohol Induced Mental Disorders, and Infectious Diseases adjustment factors because the regression factor for the ICD-10-CM codes associated with Coagulation Factor Deficit and Infectious Diseases were not statistically significant, and the current adjustment factors did not fall within the confidence intervals in the 2019 through 2021 regression.

The current adjustment factor for Drug/Alcohol Induced Mental Disorders is 1.03; however, the adjustment factor derived from our latest regression results was statistically significant at 0.96084, meaning payments would be reduced if we applied the regression-derived adjustment factor as a comorbidity adjustment for this category. In order to understand the drivers of changing costs for the Drug/Alcohol Induced Mental Disorders comorbidity category, we examined a subset of ICD-10-CM codes within the comorbidity category associated with opioid disorders which make up the majority of stays that qualify for the current Drug/Alcohol Induced Mental Disorders comorbidity adjustment. These opioid disorder codes are listed in Table 6. When we separately analyzed these codes associated with opioid disorder, the results suggested that patients with opioid disorder are significantly less expensive than patients without opioid disorder. Because stays with opioid disorders make up the majority of stays in the Drug/Alcohol Induced Mental Disorders comorbidity category, we observe a statistically-significant negative adjustment factor for the comorbidity category overall. The application of a comorbidity adjustment derived from our latest regression analysis would result in reduced payments for all stays in this comorbidity category. We do not believe it is appropriate to apply negative adjustment factors (that is, adjustment factors less than 1.00) for comorbidities because that would result in reduced rather than increased payments. Although we apply adjustment factors less than 1.00 for DRGs, this is because the DRG adjustment reflects the cost of stays relative to stays with the baseline DRG 885. In contrast, comorbidity adjustments reflect the cost relative to a stay with no comorbidities. A negative payment adjustment would not be consistent with the intent of a comorbidity adjustment, which is intended to provide additional payments to providers to account for the costs of treating patients with comorbid conditions. Therefore, we have not historically included any negative adjustment factors for comorbid conditions.

Therefore, we are proposing to remove the Drug/Alcohol Induced Mental Disorders comorbidity category beginning in FY 2025. IPF stays that include these codes as a non-principal diagnosis would no longer receive the current Drug/Alcohol Induced Mental Disorders comorbidity category adjustment factor of 1.03; nor would they receive a reduction in payment. However, many IPF stays that include these ICD-10-CM diagnosis codes as a principal diagnosis would continue to receive a DRG adjustment. We refer readers to section III.C.3.a of this proposed rule for a detailed discussion of proposed DRG adjustments under the IPF PPS.

We believe removal of the Drug/Alcohol Induced Mental Disorders comorbidity category under the IPF PPS would more appropriately align payment with resource use, as reflected in the latest regression results. As previously discussed in section III.F of this proposed rule, all of these proposed revisions would be applied budget-neutrally. Therefore, we believe the removal of the Drug/Alcohol Induced Mental Disorders comorbidity adjustment would appropriately increase the IPF PPS Federal per diem base rate and thereby increase payment for IPF stays that are costlier. However, we are soliciting comments on whether a lack of ancillary charge data may be contributing to the results of our regression analysis as it relates to opioid disorders. We note that our analysis of the ICD-10-CM codes associated with opioid disorder also indicates that there is significant overlap between facility characteristics and stays including opioid disorder diagnoses. In particular, for-profit freestanding IPFs were found to serve the majority of patients with opioid disorders. As discussed in section III.E.4 of this proposed rule, our ongoing analysis has found an increase in the number of for-profit freestanding IPFs that are consistently reporting no ancillary charges or very minimal ancillary charges on their cost report. As a result, we have previously noted that data that is necessary for accurate Medicare ratesetting is excluded from the information these facilities are reporting.

As stated previously, the regression factor for Drug/Alcohol Induced Mental Disorders was statistically significant, but is less than 1, meaning payments would be reduced if we applied it as a comorbidity adjustment. We are interested in understanding whether there is data and information that could better inform our understanding of the costs of treating these conditions. In addition, we are interested in understanding whether commenters believe it may be more appropriate to maintain the existing Drug/Alcohol Induced Mental Disorders comorbidity category adjustment factor of 1.03, given that many providers that treat these patients also report minimal or no ancillary charges on their claims and cost reports. We note that if we were to maintain the adjustment factor of 1.03 for these IPF stays, we expect it would have a negative impact on the refinement standardization factor, thereby slightly reducing the IPF PPS Federal per diem base rate and ECT per treatment amount.

We are also proposing to modify the Eating and Conduct Disorders comorbidity category and redesignate it as the Eating Disorders comorbidity category. That is, we are proposing to remove conduct disorders from the codes eligible for a comorbidity adjustment. When we separately analyzed the ICD-10-CM codes for eating disorders (specifically, F5000 Anorexia nervosa, unspecified, F5001 Anorexia nervosa, restricting type, F5002 Anorexia nervosa, binge eating/purging type, and F509 Eating disorder, unspecified) and conduct disorders (F631 Pyromania, F6381 Intermittent explosive disorder, and F911 Conduct disorder, childhood-onset type), our regression results identified a positive, statistically significant adjustment factor associated with eating disorders. In contrast, conduct disorders had a negative and non-significant factor. These results suggest that eating disorders are associated with an increased level of resource use compared to conduct disorders, and that only eating disorders have an increase resource use at a level that is statistically significant. Based on these findings, we are proposing to remove conduct disorders from the proposed newly designated Eating Disorders comorbidity category.

In addition, we are proposing to modify the Chronic Obstructive Pulmonary Disease comorbidity category to include ICD-10-CM codes associated with sleep apnea (specifically, G 4733 Obstructive sleep apnea (adult) (pediatric), 5A09357 Assistance with Respiratory Ventilation, <24 Hrs, CPAP, Z9981 Dependence on supplemental oxygen, and Z9989 Dependence on other enabling machines and devices). In response to the FY 2023 and FY 2024 IPF PPS proposed rules, commenters requested that CMS analyze the additional cost associated with patients with sleep apnea. Patients with sleep apnea often need to use a continuous positive airway pressure (CPAP) machine with a cord to manage their condition. Based on the clinical expertise of CMS Medical Officers, we determined that patients with sleep apnea in the IPF setting would have increased ligature risk (that is, anything that could be used to attach a cord, rope, or other material for the purpose of hanging or strangulation), similar to the risk associated with patients in the IPF setting that have chronic obstructive pulmonary disease. We expect the additional staffing resources involved in treating IPF patients with sleep apnea would be similar to the resources involved in treating IPF patients with chronic obstructive pulmonary disease, as patients with chronic obstructive pulmonary disease may also require the presence of an additional device with a cord in the patient's room, such as a bilevel positive airway pressure (BiPAP) machine. We evaluated adding codes associated with sleep apnea to our regression model, on the basis of our expectation that we would observe higher costs associated with these codes that would be comparable to the costs associated with chronic obstructive pulmonary disease. The results of our 2019 through 2021 regression model suggest that sleep apnea is in fact associated with an increased level of resource use. Therefore, we are proposing to redesignate the Chronic Obstructive Pulmonary Disease category as the Chronic Obstructive Pulmonary Disease and Sleep Apnea comorbidity category.

Further, we analyzed costs associated with the ICD-10-CM codes in Table 7 that indicate high-risk behavior. In response to the FY 2023 and FY 2024 IPF PPS proposed rules, commenters requested that CMS analyze the additional cost associated with patients exhibiting violent behavior during their stay in an IPF. We considered these comments in coordination with CMS Medical Officers, and determined that patients exhibiting violent behavior would require more intensive management during an IPF stay. We determined that certain ICD-10-CM codes could describe the types of high-risk behaviors that require intensive management during an IPF stay. These could include patients exhibiting violent behavior as well as other high-risk, non-violent behaviors. We examined ICD-10-CM codes in the R45 code family (Symptoms and Signs Related to Emotional State) that could indicate high-risk behavior during an IPF stay, which would lead to increased resource use. The regression analysis found that several codes, R451 Restlessness and agitation, R454 Irritability and anger, and R4584 Anhedonia codes are associated with a statistically significant adjustment factor. In other words, patients presenting with restlessness and agitation, irritability and anger, or anhedonia are more costly than patients who do not present these conditions. Therefore, we are proposing to add a new comorbidity category recognizing the costs associated with Intensive Management for High-Risk Behavior.

Lastly, we are proposing to maintain the adjustment factors for the Developmental Disabilities and Uncontrolled Diabetes comorbidity categories. Based on the regression analysis, the Developmental Disabilities comorbidity category adjustment factor was not statistically significant; however, the current adjustment factor is within the confidence interval. As discussed in section III.C.3.a of this proposed rule, a non-statistically significant adjustment factor within the confidence interval indicates that the current adjustment factor would be a reasonable approximation of the increased costs. The Uncontrolled Diabetes comorbidity category adjustment factor did not change from the current adjustment factor based on the 2019 through 2021 regression.

We are also proposing to decrease the adjustment factors for the following comorbidity categories: Renal Failure—Acute, Artificial Openings—Digestive & Urinary, Cardiac conditions, Renal Failure—Chronic, Chronic Obstructive Pulmonary Disease, Infectious Diseases, and Severe Musculoskeletal & Connective Tissue Diseases.

The regression analysis found the Renal Failure—Acute, Artificial Openings—Digestive & Urinary, Cardiac conditions, Renal Failure—Chronic, Chronic Obstructive Pulmonary Disease, Infectious Diseases, and Severe Musculoskeletal & Connective Tissue Diseases comorbidity categories resulted in a statistically significant adjustment factor. While payment would still be increased when the claim includes one of these comorbidity categories, the proposed adjustment factors for FY 2025 would be less than the current adjustment factors for these categories. The proposed FY 2025 comorbidity adjustment factors are displayed in Table 8, and can be found in Addendum A, available on the CMS website at https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-psychiatric-facility/​tools-and-worksheets.

As discussed in section III.F of this proposed rule, we are proposing to implement revisions to the comorbidity category adjustments budget-neutrally. A detailed discussion of the distributional impacts of these proposed changes is found in section VIII.C of this proposed rule.

We solicit comments on these proposed revisions to the comorbidity category adjustment factors. Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the final FY 2025 comorbidity category adjustment factors.

(2) Proposed Coding Updates for FY 2025

For FY 2025, we are proposing to add 2 ICD-10-CM/PCS codes to the Oncology Treatment comorbidity category. The proposed FY 2025 comorbidity codes are shown in Addenda B, available on the CMS website at https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-psychiatric-facility/​tools-and-worksheets.

In accordance with the policy established in the FY 2015 IPF PPS final rule (79 FR 45949 through 45952), we reviewed all new FY 2025 ICD-10-CM codes to remove codes that were site “unspecified” in terms of laterality from the FY 2023 ICD-10-CM/PCS codes in instances where more specific codes are available. As we stated in the FY 2015 IPF PPS final rule, we believe that specific diagnosis codes that narrowly identify anatomical sites where disease, injury, or a condition exists should be used when coding patients' diagnoses whenever these codes are available. We finalized in the FY 2015 IPF PPS rule, that we would remove site “unspecified” codes from the IPF PPS ICD-10-CM/PCS codes in instances when laterality codes (site specified codes) are available, as the clinician should be able to identify a more specific diagnosis based on clinical assessment at the medical encounter. There were no proposed changes to the FY 2025 ICD-10-CM/PCS codes, therefore, we are not proposing to remove any of the new codes.

c. Proposed Patient Age Adjustments

As explained in the RY 2005 IPF PPS final rule (69 FR 66922), we analyzed the impact of age on per diem cost by examining the age variable (range of ages) for payment adjustments. In general, we found that the cost per day increases with age. The older age groups are costlier than the under 45 age group, the differences in per diem cost increase for each successive age group, and the differences are statistically significant. While our regression analysis of CY 2019 through CY 2021 data supports maintaining a payment adjustment factor based on age as was established in the RY 2005 IPF PPS final rule, the results suggest that revisions to the adjustment factor for age are warranted.

For FY 2025, we are proposing to revise the patient age adjustments as shown in Addendum A of this proposed rule, which is available on the CMS website at (see https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-psychiatric-facility/​tools-and-worksheets). We are proposing to adopt the patient age adjustments derived from the regression model using a blended set of 2019 through 2021 data, as discussed in section III.C.3 of this proposed rule. Table 9 summarizes the current and proposed patient age adjustment factors for FY 2025. As discussed in section III.F of this proposed rule, we are proposing to implement this revision to the patient age adjustments budget-neutrally. A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule.

We solicit comment on these proposed revisions to the patient age adjustment factors. Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the final FY 2025 patient age adjustment factors.

d. Proposed Variable Per Diem Adjustments

We explained in the RY 2005 IPF PPS final rule (69 FR 66946) that the regression analysis indicated that per diem cost declines as the LOS increases. The variable per diem adjustments to the Federal per diem base rate account for ancillary and administrative costs that occur disproportionately in the first days after admission to an IPF. As discussed in the RY 2005 IPF PPS final rule, where a complete discussion of the variable per diem adjustments can be found, we used a regression analysis to estimate the average differences in per diem cost among stays of different lengths (69 FR 66947 through 66950). As a result of this analysis, we established variable per diem adjustments that begin on day 1 and decline gradually until day 21 of a patient's stay. For day 22 and thereafter, the variable per diem adjustment remains the same each day for the remainder of the stay. However, the adjustment applied to day 1 depends upon whether the IPF has a qualifying ED. If an IPF has a qualifying ED, it receives a 1.31 adjustment factor for day 1 of each stay. If an IPF does not have a qualifying ED, it receives a 1.19 adjustment factor for day 1 of the stay. The ED adjustment is explained in more detail in section III.D.4 of this proposed rule.

For FY 2025, we are proposing to revise the variable per diem adjustment factors as indicated in the table below, and shown in Addendum A to this rule, which is available on the CMS website at https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-psychiatric-facility/​tools-and-worksheets. We are proposing to increase the adjustment factors for days 1 through 9. As shown in Table 10, the results of the latest regression analysis indicate that there is not a statistically significant decrease in cost per day after day 10; therefore, we are proposing that days 10 and above would receive a 1.00 adjustment. Table 10 summarizes the current and proposed variable per diem adjustment factors for FY 2025. As discussed in section III.F of this proposed rule, we are proposing to implement this revision to the variable per diem adjustments budget-neutrally. A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule.

We solicit comments on these proposed revisions to the variable per diem adjustment factors. Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the final FY 2025 variable per diem adjustment factors.

D. Proposed Updates to the IPF PPS Facility-Level Adjustments

The IPF PPS includes facility-level adjustments for the wage index, IPFs located in rural areas, teaching IPFs, cost of living adjustments for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED. We are proposing to use the existing regression-derived facility-level adjustment factors established in the RY 2005 IPF final rule for FY 2025.

As previously discussed, in section I.A of this proposed rule, we are proposing to revise the methodology for determining payments under the IPF PPS as required by the CAA, 2023. We are not proposing changes to the facility-level adjustment factors for rural location and teaching status for FY 2025; however, section IV.A of this proposed rule includes a request for information regarding potential future updates to these facility-level adjustments. We are particularly interested in comments on the results of our updated regression analysis as they apply to facility-level adjustors.

1. Wage Index Adjustment

a. Background

As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), and the RY 2009 IPF PPS (73 FR 25719) and RY 2010 IPF PPS notices (74 FR 20373), to provide an adjustment for geographic wage levels, the labor-related portion of an IPF's payment is adjusted using an appropriate wage index. Currently, an IPF's geographic wage index value is determined based on the actual location of the IPF in an urban or rural area, as defined in § 412.64(b)(1)(ii)(A) and (C).

Due to the variation in costs and because of the differences in geographic wage levels, in the RY 2005 IPF PPS final rule, we required that payment rates under the IPF PPS be adjusted by a geographic wage index. We proposed and finalized a policy to use the unadjusted, pre-floor, pre-reclassified IPPS hospital wage index to account for geographic differences in IPF labor costs. We implemented use of the pre-floor, pre-reclassified IPPS hospital wage data to compute the IPF wage index since there was not an IPF-specific wage index available. We believe that IPFs generally compete in the same labor market as IPPS hospitals therefore, the pre-floor, pre-reclassified IPPS hospital wage data should be reflective of labor costs of IPFs. We believe this pre-floor, pre-reclassified IPPS hospital wage index to be the best available data to use as proxy for an IPF-specific wage index. As discussed in the RY 2007 IPF PPS final rule (71FR 27061 through 27067), under the IPF PPS, the wage index is calculated using the IPPS wage index for the labor market area in which the IPF is located, without considering geographic reclassifications, floors, and other adjustments made to the wage index under the IPPS. For a complete description of these IPPS wage index adjustments, we refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41390). Our wage index policy at § 412.424(a)(2) provides that we use the best Medicare data available to estimate costs per day, including an appropriate wage index to adjust for wage differences.

When the IPF PPS was implemented in the RY 2005 IPF PPS final rule, with an effective date of January 1, 2005, the pre-floor, pre-reclassified IPPS hospital wage index that was available at the time was the FY 2005 pre-floor, pre-reclassified IPPS hospital wage index. Historically, the IPF wage index for a given RY has used the pre-floor, pre-reclassified IPPS hospital wage index from the prior FY as its basis. This has been due in part to the pre-floor, pre-reclassified IPPS hospital wage index data that were available during the IPF rulemaking cycle, where an annual IPF notice or IPF final rule was usually published in early May. This publication timeframe was relatively early compared to other Medicare payment rules because the IPF PPS follows a RY, which was defined in the implementation of the IPF PPS as the 12-month period from July 1 to June 30 (69 FR 66927). Therefore, the best available data at the time the IPF PPS was implemented was the pre-floor, pre-reclassified IPPS hospital wage index from the prior FY (for example, the RY 2006 IPF wage index was based on the FY 2005 pre-floor, pre-reclassified IPPS hospital wage index).

In the RY 2012 IPF PPS final rule, we changed the reporting year timeframe for IPFs from a RY to FY, which begins October 1 and ends September 30 (76 FR 26434 through 26435). In that FY 2012 IPF PPS final rule, we continued our established policy of using the pre-floor, pre-reclassified IPPS hospital wage index from the prior year (that is, from FY 2011) as the basis for the FY 2012 IPF wage index. This policy of basing a wage index on the prior year's pre-floor, pre-reclassified IPPS hospital wage index has been followed by other Medicare payment systems, such as hospice and inpatient rehabilitation facilities. By continuing with our established policy, we remained consistent with other Medicare payment systems.

In FY 2020, we finalized the IPF wage index methodology to align the IPF PPS wage index with the same wage data timeframe used by the IPPS for FY 2020 and subsequent years. Specifically, we finalized the use of the pre-floor, pre-reclassified IPPS hospital wage index from the FY concurrent with the IPF FY as the basis for the IPF wage index. For example, the FY 2020 IPF wage index was based on the FY 2020 pre-floor, pre-reclassified IPPS hospital wage index rather than on the FY 2019 pre-floor, pre-reclassified IPPS hospital wage index.

We explained in the FY 2020 proposed rule (84 FR 16973), that using the concurrent pre-floor, pre-reclassified IPPS hospital wage index will result in the most up-to-date wage data being the basis for the IPF wage index. We noted that it would also result in more consistency and parity in the wage index methodology used by other Medicare payment systems. We indicated that the Medicare skilled nursing facility (SNF) PPS already used the concurrent IPPS hospital wage index data as the basis for the SNF PPS wage index. We proposed and finalized similar policies to use the concurrent pre-floor, pre-reclassified IPPS hospital wage index data in other Medicare payment systems, such as hospice and inpatient rehabilitation facilities. Thus, the wage adjusted Medicare payments of various provider types are based upon wage index data from the same timeframe. For FY 2025, we are proposing to continue to use the concurrent pre-floor, pre-reclassified IPPS hospital wage index as the basis for the IPF wage index.

In the FY 2023 IPF PPS final rule (87 FR 46856 through 46859), we finalized a permanent 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, and we stated that we would apply this cap in a budget neutral manner. In addition, we finalized a policy that a new IPF 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 IPF would not have a wage index in the prior FY. We amended the IPF PPS regulations at § 412.424(d)(1)(i) to reflect this permanent cap on wage index decreases. We refer readers to the FY 2023 IPF PPS final rule for a more detailed discussion about this policy.

We are proposing to apply the IPF wage index adjustment to the labor-related share of the national IPF PPS base rate and ECT payment per treatment. The proposed labor-related share of the IPF PPS national base rate and ECT payment per treatment is 78.8 percent in FY 2025. This percentage reflects the labor-related share of the 2021-based IPF market basket for FY 2025 and is 0.1 percentage point higher than the FY 2024 labor-related share (see section III.A.3 of this proposed rule).

b. Office of Management and Budget (OMB) Bulletins

(1) Background

The wage index used for the IPF PPS is calculated using the unadjusted, pre-reclassified and pre-floor IPPS wage index data and is assigned to the IPF based on the labor market area in which the IPF is geographically located. IPF labor market areas are delineated based on the Core-Based Statistical Area (CBSAs) established by the OMB.

Generally, OMB issues major revisions to statistical areas every 10 years, based on the results of the decennial census. However, OMB occasionally issues minor updates and revisions to statistical areas in the years between the decennial censuses through OMB Bulletins. These bulletins contain information regarding CBSA changes, including changes to CBSA numbers and titles. OMB bulletins may be accessed online at https://www.whitehouse.gov/​omb/​information-for-agencies/​bulletins/​. In accordance with our established methodology, the IPF PPS has historically adopted any CBSA changes that are published in the OMB bulletin that corresponds with the IPPS hospital wage index used to determine the IPF wage index and, when necessary and appropriate, has proposed and finalized transition policies for these changes.

In the RY 2007 IPF PPS final rule (71 FR 27061 through 27067), we adopted the changes discussed in the OMB Bulletin No. 03-04 (June 6, 2003), which announced revised definitions for Metropolitan Statistical Areas (MSAs), and the creation of Micropolitan Statistical Areas and Combined Statistical Areas. In adopting the OMB CBSA geographic designations in RY 2007, we did not provide a separate transition for the CBSA-based wage index since the IPF PPS was already in a transition period from TEFRA payments to PPS payments.

In the RY 2009 IPF PPS notice, we incorporated the CBSA nomenclature changes published in the most recent OMB bulletin that applied to the IPPS hospital wage index used to determine the current IPF wage index and stated that we expected to continue to do the same for all the OMB CBSA nomenclature changes in future IPF PPS rules and notices, as necessary (73 FR 25721).

Subsequently, CMS adopted the changes that were published in past OMB bulletins in the FY 2016 IPF PPS final rule (80 FR 46682 through 46689), the FY 2018 IPF PPS rate update (82 FR 36778 through 36779), the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), and the FY 2021 IPF PPS final rule (85 FR 47051 through 47059). We direct readers to each of these rules for more information about the changes that were adopted and any associated transition policies.

As discussed in the FY 2023 IPF PPS final rule, we did not adopt OMB Bulletin 20-01, which was issued March 6, 2020, because we determined this bulletin had no material impact on the IPF PPS wage index. This bulletin creates only one Micropolitan statistical area, and Micropolitan areas are considered rural for the IPF PPS wage index. That is, the constituent county of the new Micropolitan area was considered rural effective as of FY 2021 and would continue to be considered rural if we adopted OMB Bulletin 20-01.

Finally, on July 21, 2023, OMB issued Bulletin 23-01, which revises the CBSA delineations based on the latest available data from the 2020 census. This bulletin contains information regarding updates of statistical area changes to CBSA titles, numbers, and county or county equivalents.

(2) Proposed Implementation of New Labor Market Area Delineations

We believe it is important for the IPF PPS to use, as soon as is reasonably possible, the latest available labor market area delineations to maintain a more accurate and up-to-date payment system that reflects the reality of population shifts and labor market conditions. We believe that using the most current delineations would increase the integrity of the IPF PPS wage index system by creating a more accurate representation of geographic variations in wage levels. We have carefully analyzed the impacts of adopting the new OMB delineations and find no compelling reason to delay implementation. Therefore, we are proposing to implement the new OMB delineations as described in the July 21, 2023, OMB Bulletin No. 23-01, effective beginning with the FY 2025 IPF PPS wage index. We are proposing to adopt the updates to the OMB delineations announced in OMB Bulletin No. 23-01 effective for FY 2025 under the IPF PPS.

As previously discussed, we finalized a 5-percent permanent cap on any decrease to a provider's wage index from its wage index in the prior year. For more information on the permanent 5-percent cap policy, we refer readers to the FY 2023 IPF PPS final rule (87 FR 46856 through 46859). In addition, we are proposing to phase out the rural adjustment for IPFs that are transitioning from rural to urban based on these CBSA revisions, as discussed in section III.D.1.c. of this proposed rule.

(a) Micropolitan Statistical Areas

OMB defines a “Micropolitan Statistical Area” as a CBSA associated with at least one urban cluster that has a population of at least 10,000, but less than 50,000 (75 FR 37252). We refer to these as Micropolitan Areas. After extensive impact analysis, consistent with the treatment of these areas under the IPPS as discussed in the FY 2005 IPPS final rule (69 FR 49029 through 49032), we determined the best course of action would be to treat Micropolitan Areas as “rural” and include them in the calculation of each state's IPF PPS rural wage index. We refer readers to the FY 2007 IPF PPS final rule (71 FR 27064 through 27065) for a complete discussion regarding treating Micropolitan Areas as rural. We are not proposing any changes to this policy for FY 2025.

(b) Change to County-Equivalents in the State of Connecticut

The June 6, 2022 Census Bureau Notice (87 FR 34235 through 34240), OMB Bulletin No. 23-01 replaced the 8 counties in Connecticut with 9 new “Planning Regions.” Planning regions now serve as county-equivalents within the CBSA system. We have evaluated the changes and are proposing to adopt the planning regions as county equivalents for wage index purposes. We believe it is necessary to adopt this migration from counties to planning region county-equivalents to maintain consistency with OMB updates. We are providing the following crosswalk for each county in Connecticut with the current and proposed FIPS county and county-equivalent codes and CBSA assignments.

(c) Urban Counties That Would Become Rural Under the Revised OMB Delineations

As previously discussed, we are proposing to implement the new OMB labor market area delineations (based upon OMB Bulletin No. 23-01) beginning in FY 2025. Our analysis shows that a total of 53 counties (and county equivalents) and 15 providers are located in areas that were previously considered part of an urban CBSA but would be considered rural beginning in FY 2025 under these revised OMB delineations. Table 12 lists the 53 urban counties that would be rural if we finalize our proposal to implement the revised OMB delineations.

We are proposing that the wage data for all providers located in the counties listed above would now be considered rural, beginning in FY 2025, when calculating their respective state's rural wage index. This rural wage index value would also be used under the IPF PPS. We recognize that rural areas typically have lower area wage index values than urban areas, and providers located in these counties may experience a negative impact in their IPF payment due to the proposed adoption of the revised OMB delineations. However, as discussed in section III.D.1.c of this proposed rule, providers located in these counties would receive a rural adjustment beginning in FY 2025, which would mitigate the impact of decreases to the wage index for these providers. In addition, the permanent 5-percent cap on wage index decreases under the IPF PPS would further mitigate large wage index decreases for providers in these areas.

(d) Rural Counties That Would Become Urban Under the Revised OMB Delineations

As previously discussed, we are proposing to implement the new OMB labor market area delineations (based upon OMB Bulletin No. 23-01) beginning in FY 2025. Analysis of these OMB labor market area delineations shows that a total of 54 counties (and county equivalents) and 10 providers are located in areas that were previously considered rural but would now be considered urban under the revised OMB delineations. Table 13 lists the 54 rural counties that would be urban if we finalize our proposal to implement the revised OMB delineations.

We are proposing that when calculating the area wage index, beginning with FY 2025, the wage data for providers located in these counties would be included in their new respective urban CBSAs. Typically, providers located in an urban area receive a wage index value higher than or equal to providers located in their state's rural area. We also note that providers located in these areas would no longer be considered rural beginning in FY 2025. We refer readers to section III.D.1.c of this proposed rule for a discussion of the proposed policy to phase out the payment of the rural adjustment for providers in these areas.

(e) Urban Counties That Would Move to a Different Urban CBSA Under the New OMB Delineations

In certain cases, adopting the new OMB delineations would involve a change only in CBSA name and/or number, while the CBSA continues to encompass the same constituent counties. For example, CBSA 10540 (Albany-Lebanon, OR) would experience a change to its name, and become CBSA 10540 (Albany, OR), while its one constituent county would remain the same. Table 14 shows the current CBSA code and our proposed CBSA code where we are proposing to change either the name or CBSA number only. We are not discussing further in this section these proposed changes because they are inconsequential changes with respect to the IPF PPS wage index.

In some cases, if we adopt the new OMB delineations, counties would shift between existing and new CBSAs, changing the constituent makeup of the CBSAs. We consider this type of change, where CBSAs are split into multiple new CBSAs, or a CBSA loses one or more counties to another urban CBSA to be significant modifications.

Table 15 lists the urban counties that would move from one urban CBSA to another newly proposed or modified CBSA if we adopted the new OMB delineations.

We have identified 68 IPF providers located in the affected counties listed in Table 15. If providers located in these counties move from one CBSA to another under the revised OMB delineations, there may be impacts, either negative or positive, upon their specific wage index values.

c. Proposed Adjustment for Rural Location

In the RY 2005 IPF PPS final rule, (69 FR 66954), we provided a 17-percent payment adjustment for IPFs located in a rural area. This adjustment was based on the regression analysis, which indicated that the per diem cost of rural facilities was 17-percent higher than that of urban facilities after accounting for the influence of the other variables included in the regression. This 17-percent adjustment has been part of the IPF PPS each year since the inception of the IPF PPS. As discussed earlier in this rule, we are proposing a number of revisions to the patient-level adjustment factors as well as changes to the CBSA delineations. In order to minimize the scope of changes that would impact providers in any single year, we are proposing to use the existing regression-derived adjustment factor, which was established in RY 2005, for FY 2025 for IPFs located in a rural area as defined at § 412.64(b)(1)(ii)(C). See 69 FR 66954 for a complete discussion of the adjustment for rural locations. However, as discussed in the section IV.A of this FY 2025 IPF PPS proposed rule, we have completed analysis of more recent cost and claims information and are soliciting comments on those results.

As proposed earlier in this proposed rule, the adoption of OMB Bulletin No. 23-01 in accordance with our established methodology would determine whether a facility is classified as urban or rural for purposes of the rural payment adjustment in the IPF PPS. Overall, we believe implementing updated OMB delineations would result in the rural payment adjustment being applied where it is appropriate to adjust for higher costs incurred by IPFs in rural locations. However, we recognize that implementing these changes would have distributional effects among IPF providers, and that some providers would experience a loss of the rural payment adjustment because of our proposals. Therefore, we believe it would be appropriate to consider, as we have in the past, whether a transition period should be used to implement these proposed changes.

Prior changes to the CBSA delineations have included a phase-out policy for the rural adjustment for IPFs transitioning from rural to urban status. On February 28, 2013, OMB issued OMB Bulletin No. 13-01, which 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. We adopted these new OMB CBSA delineations in the FY 2016 IPF final rule ( 80 FR 46682 through 46689), and identified 105 counties and 37 IPFs that would move from rural to urban status due to the new CBSA delineations. To reduce the impact of the loss of the 17-percent rural adjustment, we adopted a budget-neutral 3-year phase-out of the rural adjustment for existing FY 2015 rural IPFs that became urban in FY 2016 and that experienced a loss in payments due to changes from the new CBSA delineations. These IPFs received two-thirds of the rural adjustment for FY 2016 and one-third of the rural adjustment in FY 2017. For FY 2018, these IPFs did not receive a rural adjustment.

For subsequent adoptions of OMB Bulletin No. 15-01 for FY 2018 (82 FR 36779 through 36780), OMB Bulletin 17-01 for FY 2020 (84 FR 38453 through 38454), and OMB Bulletin 18-04 for FY 2021 (85 FR 47053 through 47059), we identified that fewer providers were affected by these changes than by the changes relating to the adoption of OMB Bulletin 13-01. We did not phase out the rural adjustment when adopting these delineation changes.

For facilities located in a county that transitioned from rural to urban in Bulletin 23-01, we considered whether it would be appropriate to phase out the rural adjustment for affected providers consistent with our past practice of using transition policies to help mitigate negative impacts on hospitals of OMB Bulletin proposals that have a material effect on a number of IPFs. Adoption of the updated CBSAs in Bulletin 23-01 will change the status of 10 IPF providers currently designated as “rural” to “urban” for FY 2025 and subsequent fiscal years. As such, these 10 newly urban providers will no longer receive the 17-percent rural adjustment. Consistent with the transition policy adopted for IPFs in FY 2016 (80 FR 46682 through 4668980 FR 46682 through 46689), we are proposing a 3-year budget neutral phase-out of the rural adjustment for IPFs located in the 54 rural counties that will become urban under the new OMB delineations, given the potentially significant payment impacts for these IPFs. We believe that a phase-out of the rural adjustment transition period for these 10 IPFs specifically is appropriate because we expect these IPFs will experience a steeper and more abrupt reduction in their payments compared to other IPFs. Therefore, we are proposing to phase out the rural adjustment for these providers to reduce the impact of the loss of the FY 2024 rural adjustment of 17-percent over FYs 2025, 2026, and 2027. This policy would allow IPFs that are classified as rural in FY 2024 and would be classified as urban in FY 2025 to receive two-thirds of the rural adjustment for FY 2025. For FY 2026, these IPFs would receive one-third of the rural adjustment. For FY 2027, these IPFs would not receive a rural adjustment. We believe a 3-year budget-neutral phase-out of the rural adjustment for IPFs that transition from rural to urban status under the new CBSA delineations would best accomplish the goals of mitigating the loss of the rural adjustment for existing FY 2024 rural IPFs. The purpose of the gradual phase-out of the rural adjustment for these providers is to mitigate potential payment reductions and promote stability and predictability in payments for existing rural IPFs that may need time to adjust to the loss of their FY 2024 rural payment adjustment or that experience a reduction in payments solely because of this re-designation. This policy would be specifically for rural IPFs that become urban in FY 2025. We are not proposing a transition policy for urban IPFs that become rural in FY 2025 because these IPFs will receive the full rural adjustment of 17-percent beginning October 1, 2024. We solicit comments on this proposed policy.

d. Proposed Wage Index Budget Neutrality Adjustment

Changes to the wage index are made in a budget neutral manner so that updates do not increase expenditures. Therefore, for FY 2025, we are proposing to continue to apply a budget neutrality adjustment in accordance with our existing budget neutrality policy. This policy requires us to update the wage index in such a way that total estimated payments to IPFs for FY 2025 are the same with or without the changes (that is, in a budget neutral manner) by applying a budget neutrality factor to the IPF PPS rates. We are proposing to use the following steps to ensure that the rates reflect the FY 2025 update to the wage indexes (based on the FY 2021 hospital cost report data) and the labor-related share in a budget neutral manner:

Step 1: Simulate estimated IPF PPS payments, using the FY 2024 IPF wage index values (available on the CMS website) and labor-related share (as published in the FY 2024 IPF PPS final rule (88 FR 51054).

Step 2: Simulate estimated IPF PPS payments using the proposed FY 2025 IPF wage index values (available on the CMS website), and the proposed FY 2025 labor-related share (based on the latest available data as discussed previously).

Step 3: Divide the amount calculated in step 1 by the amount calculated in step 2. The resulting quotient is the proposed FY 2025 budget neutral wage adjustment factor of 0.9995.

Step 4: Apply the FY 2025 budget neutral wage adjustment factor from step 3 to the FY 2024 IPF PPS Federal per diem base rate after the application of the IPF market basket increase reduced by the productivity adjustment described in section III.A of this proposed rule to determine the FY 2025 IPF PPS Federal per diem base rate. As discussed in section III.F of this proposed rule, we are also proposing to apply a refinement standardization factor to determine the FY 2025 IPF PPS Federal per diem base rate.

2. Proposed Teaching Adjustment

Background

In the RY 2005 IPF PPS final rule, we implemented regulations at § 412.424(d)(1)(iii) to establish a facility-level adjustment for IPFs that are, or are part of, teaching hospitals. The teaching adjustment accounts for the higher indirect operating costs experienced by hospitals that participate in graduate medical education (GME) programs. The payment adjustments are made based on the ratio of the number of fulltime equivalent (FTE) interns and residents training in the IPF and the IPF's average daily census.

Medicare makes direct GME payments (for direct costs such as resident and teaching physician salaries, and other direct teaching costs) to all teaching hospitals including those paid under a PPS and those paid under the TEFRA rate-of-increase limits. These direct GME payments are made separately from payments for hospital operating costs and are not part of the IPF PPS. The direct GME payments do not address the estimated higher indirect operating costs teaching hospitals may face.

The results of the regression analysis of FY 2002 IPF data established the basis for the payment adjustments included in the RY 2005 IPF PPS final rule. The results showed that the indirect teaching cost variable is significant in explaining the higher costs of IPFs that have teaching programs. We calculated the teaching adjustment based on the IPF's “teaching variable,” which is (1 + [the number of FTE residents training in the IPF's average daily census]). The teaching variable is then raised to the 0.5150 power to result in the teaching adjustment. This formula is subject to the limitations on the number of FTE residents, which are described in this section of this proposed rule.

We established the teaching adjustment in a manner that limited the incentives for IPFs to add FTE residents for the purpose of increasing their teaching adjustment. We imposed a cap on the number of FTE residents that may be counted for purposes of calculating the teaching adjustment. The cap limits the number of FTE residents that teaching IPFs may count for the purpose of calculating the IPF PPS teaching adjustment, not the number of residents teaching institutions can hire or train. We calculated the number of FTE residents that trained in the IPF during a “base year” and used that FTE resident number as the cap. An IPF's FTE resident cap is ultimately determined based on the final settlement of the IPF's most recent cost report filed before November 15, 2004 (69 FR 66955). A complete discussion of the temporary adjustment to the FTE cap to reflect residents due to hospital closure or residency program closure appears in the RY 2012 IPF PPS proposed rule (76 FR 5018 through 5020) and the RY 2012 IPF PPS final rule (76 FR 26453 through 26456).

In the regression analysis that informed the FY 2004 IPF PPS final rule, the logarithm of the teaching variable had a coefficient value of 0.5150. We converted this cost effect to a teaching payment adjustment by treating the regression coefficient as an exponent and raising the teaching variable to a power equal to the coefficient value. We note that the coefficient value of 0.5150 was based on the regression analysis holding all other components of the payment system constant. A complete discussion of how the teaching adjustment was calculated appears in the RY 2005 IPF PPS final rule (69 FR 66954 through 66957) and the RY 2009 IPF PPS notice (73 FR 25721).

We are proposing to retain the coefficient value of 0.5150 for the teaching adjustment to the Federal per diem base rate as we are not proposing refinements to the facility-level payment adjustments for rural location or teaching status for FY 2025. As noted earlier, given the scope of changes to the wage index and patient-level adjustment factors, we believe this will minimize the total impacts to providers in any given year.

3. Proposed Cost of Living Adjustment for IPFs Located in Alaska and Hawaii

The IPF PPS includes a payment adjustment for IPFs located in Alaska and Hawaii based upon the area in which the IPF is located. As we explained in the RY 2005 IPF PPS final rule, the FY 2002 data demonstrated that IPFs in Alaska and Hawaii had per diem costs that were disproportionately higher than other IPFs. As a result of this analysis, we provided a COLA in the RY 2005 IPF PPS final rule. We refer readers to the FY 2024 IPF PPS final rule for a complete discussion of the currently applicable COLA factors (88 FR 51088 through 51089).

We adopted a new methodology to update the COLA factors for Alaska and Hawaii for the IPF PPS in the FY 2015 IPF PPS final rule (79 FR 45958 through 45960). For a complete discussion, we refer readers to the FY 2015 IPF PPS final rule.

We also specified that the COLA updates would be determined every 4 years, in alignment with the IPPS market basket labor-related share update (79 FR 45958 through 45960). Because the labor-related share of the IPPS market basket was updated for FY 2022, the COLA factors were updated in FY 2022 IPPS/LTCH rulemaking (86 FR 45547). As such, we also finalized an update to the IPF PPS COLA factors to reflect the updated COLA factors finalized in the FY 2022 IPPS/LTCH rulemaking effective for FY 2022 through FY 2025 (86 FR 42621 through 42622). This is reflected in Table 16 below. We are proposing to maintain the COLA factors in Table 16 for FY 2025 in alignment with the policy described in this paragraph.

The proposed IPF PPS COLA factors for FY 2025 are also shown in Addendum A to this proposed rule, which is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.

4. Proposed Adjustment for IPFs With a Qualifying ED

The IPF PPS includes a facility-level adjustment for IPFs with qualifying EDs. As defined in § 412.402, qualifying emergency department means an emergency department that is staffed and equipped to furnish a comprehensive array of emergency services and meets the requirements of 42 CFR 489.24(b) and § 413.65.

We provide an adjustment to the Federal per diem base rate to account for the costs associated with maintaining a full-service ED. The adjustment is intended to account for ED costs incurred by a psychiatric hospital with a qualifying ED, or an excluded psychiatric unit of an IPPS hospital or a critical access hospital (CAH), and the overhead cost of maintaining the ED. This payment applies to all IPF admissions (with one exception which we describe in this section), regardless of whether the patient was admitted through the ED. The ED adjustment is made on every qualifying claim except as described in this section of this proposed rule. As specified at § 412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is discharged from an IPPS hospital or CAH, and admitted to the same IPPS hospital's or CAH's excluded psychiatric unit. We clarified in the RY 2005 IPF PPS final rule (69 FR 66960) that an ED adjustment is not made in this case because the costs associated with ED services are reflected in the DRG payment to the IPPS hospital or through the reasonable cost payment made to the CAH.

a. Proposed Update for FY 2025

For FY 2025, we are proposing to update the adjustment factor from 1.31 to 1.53 for IPFs with qualifying EDs using the same methodology used to determine ED adjustments in prior years. Thus, we are proposing to use the following steps, as used in prior years, to calculate the updated ED adjustment factor. (A complete discussion of the steps involved in the calculation of the ED adjustment factors can be found in the RY 2005 IPF PPS final rule (69 FR 66959 through 66960) and the RY 2007 IPF PPS final rule (71 FR 27070 through 27072).)

Step 1: Estimate the proportion by which the ED costs of a stay would increase the cost of the first day of the stay. Using the IPFs with ED admissions in years 2019 through 2021, we divided the average ED cost per stay when admitted through the ED ($519.97) by the average cost per day ($1,338.93), which equals 0.39.

Step 2: Adjust the factor estimated in step 1 to account for the fact that we would pay the higher first day adjustment for all cases in the qualifying IPFs, not just the cases admitted through the ED. Since on average, 66 percent of the cases in IPFs with ED admissions are admitted through the ED, we multiplied 0.39 by 0.66, which equals 0.26.

Step 3: Add the adjusted factor calculated in the previous 2 steps to the variable per diem adjustment derived from the regression equation that we used to derive our other payment adjustment factors. As discussed in section III.C.4.d. of this proposed rule, the proposed first day payment factor for FY 2025 is 1.27. Adding 0.26, we obtained a first day variable per adjustment for IPFs with a qualifying ED equal to 1.53.

The ED adjustment is incorporated into the variable per diem adjustment for the first day of each stay for IPFs with a qualifying ED. We are proposing that those IPFs with a qualifying ED would receive an adjustment factor of 1.53 as the variable per diem adjustment for day 1 of each patient stay. If an IPF does not have a qualifying ED, we are proposing that it would receive an adjustment factor of 1.27 as the variable per diem adjustment for day 1 of each patient stay, as discussed in section III.C.4.d. of this proposed rule. As discussed in section III.F of this proposed rule, we are proposing to implement this revision to the ED adjustment budget—neutrally by applying a refinement standardization factor. A detailed discussion of the distributional impacts of this proposed change is found in section VIII.C of this proposed rule.

We solicit comment on this proposal. Lastly, we are proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2025 ED adjustment factor.

b. Alternatives Considered

In response to the FY 2023 IPF PPS proposed rule (87 FR 19428 through 19429) comment solicitation on our technical report describing the analysis of IPF PPS adjustments, two commenters requested that we conduct further analysis related to the exception for the ED adjustment. These commenters indicated that patients transferred to an IPF from an acute care unit or hospital often have higher costs per stay than patients with similar comorbidities admitted from the community. Commenters requested that CMS analyze data related to source of admission and consider a payment adjustment to account for the resources used by these patients. In response to these comments, we conducted a regression analysis to investigate whether the source of admission is a statistically significant variable in the cost of a patient's care in an IPF. We analyzed the following sources of admission: clinic referral, transfer from hospital (different facility), transfer from a SNF or Intermediate Care Facility (ICF), transfer from another health care facility, court/law enforcement, information not available, transfer from hospital inpatient in the same facility, transfer from ambulatory surgical center, and transfer from hospice. In this context, it is important to note that the source of admission indicator “court/law enforcement” is not the equivalent of an involuntary admission; we do not currently collect data on involuntary admissions.

The regression analysis found that the source of admission was not a statistically significant factor in the cost of care. The results for the two source of admission variables that indicate higher costs (transfer from hospital inpatient in the same facility and transfer from ambulatory surgical center) are accounted for by the known difference in cost structures between hospital psychiatric units and freestanding psychiatric hospitals. We considered the results of our analysis, as well as the potential that adjusting payment based on source of admission could inadvertently create incentives for IPFs to prioritize certain admissions over others. Based on these considerations, we are not proposing to add additional payment adjustments based on source of admission (other than the existing adjustment for a qualifying ED) to the IPF PPS in FY 2025.

E. Other Proposed Payment Adjustments and Policies

1. Outlier Payment Overview

The IPF PPS includes an outlier adjustment to promote access to IPF care for those patients who require expensive care and to limit the financial risk of IPFs treating unusually costly patients. In the RY 2005 IPF PPS final rule, we implemented regulations at § 412.424(d)(3)(i) to provide a per case payment for IPF stays that are extraordinarily costly. Providing additional payments to IPFs for extremely costly cases strongly improves the accuracy of the IPF PPS in determining resource costs at the patient and facility level. These additional payments reduce the financial losses that would otherwise be incurred in treating patients who require costlier care; therefore, reduce the incentives for IPFs to under-serve these patients. We make outlier payments for discharges in which an IPF's estimated total cost for a case exceeds a fixed dollar loss threshold amount (multiplied by the IPF's facility-level adjustments) plus the federal per diem payment amount for the case.

In instances when the case qualifies for an outlier payment, we pay 80 percent of the difference between the estimated cost for the case and the adjusted threshold amount for days 1 through 9 of the stay (consistent with the median LOS for IPFs in FY 2002), and 60 percent of the difference for day 10 and thereafter. The adjusted threshold amount is equal to the outlier threshold amount adjusted for wage area, teaching status, rural area, and the COLA adjustment (if applicable), plus the amount of the Medicare IPF payment for the case. We established the 80 percent and 60 percent loss sharing ratios because we were concerned that a single ratio established at 80 percent (like other Medicare PPSs) might provide an incentive under the IPF per diem payment system to increase LOS to receive additional payments.

After establishing the loss sharing ratios, we determined the current fixed dollar loss threshold amount through payment simulations designed to compute a dollar loss beyond which payments are estimated to meet the 2 percent outlier spending target. Each year when we update the IPF PPS, we simulate payments using the latest available data to compute the fixed dollar loss threshold so that outlier payments represent 2 percent of total estimated IPF PPS payments.

2. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount

In accordance with the update methodology described in § 412.428(d), we are proposing to update the fixed dollar loss threshold amount used under the IPF PPS outlier policy. Based on the regression analysis and payment simulations used to develop the IPF PPS, we established a 2 percent outlier policy, which strikes an appropriate balance between protecting IPFs from extraordinarily costly cases while ensuring the adequacy of the federal per diem base rate for all other cases that are not outlier cases. We are proposing to maintain the established 2 percent outlier policy for FY 2025.

Our longstanding methodology for updating the outlier fixed dollar loss threshold involves using the best available data, which is typically the most recent available data. We note that for FY 2022 and FY 2023 only, we made certain methodological changes to our modeling of outlier payments, and we discussed the specific circumstances that led to those changes for those years (86 FR 42623 through 42624; 87 FR 46862 through 46864). We direct readers to the FY 2022 and FY 2023 IPF PPS proposed and final rules for a more complete discussion.

We are proposing to update the IPF outlier threshold amount for FY 2025 using FY 2023 claims data and the same methodology that we have used to set the initial outlier threshold amount each year beginning with the RY 2007 IPF PPS final rule (71 FR 27072 and 27073). For this FY 2025 IPF PPS rulemaking, consistent with our longstanding practice, based on an analysis of the latest available data (the December 2023 update of FY 2023 IPF claims) and rate increases, we believe it is necessary to update the fixed dollar loss threshold amount to maintain an outlier percentage that equals 2 percent of total estimated IPF PPS payments. Based on an analysis of these updated data, we estimate that IPF outlier payments as a percentage of total estimated payments are approximately 2.1 percent in FY 2024. Therefore, we are proposing to update the outlier threshold amount to $35,590 to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF payments for FY 2025. This proposed rule update is an increase from the FY 2024 threshold of $33,470.

Lastly, we are proposing that if more recent data become available for the FY 2025 IPF PPS final rule, we would use such data as appropriate to determine the final outlier fixed dollar loss threshold amount for FY 2025.

3. Proposed Update to IPF Cost-to-Charge Ratio Ceilings

Under the IPF PPS, an outlier payment is made if an IPF's cost for a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS amount. To establish an IPF's cost for a particular case, we multiply the IPF's reported charges on the discharge bill by its overall cost-to-charge ratio (CCR). This approach to determining an IPF's cost is consistent with the approach used under the IPPS and other PPSs. In the FY 2004 IPPS final rule (68 FR 34494), we implemented changes to the IPPS policy used to determine CCRs for IPPS hospitals, because we became aware that payment vulnerabilities resulted in inappropriate outlier payments. Under the IPPS, we established a statistical measure of accuracy for CCRs to ensure that aberrant CCR data did not result in inappropriate outlier payments.

As indicated in the RY 2005 IPF PPS final rule (69 FR 66961), we believe that the IPF outlier policy is susceptible to the same payment vulnerabilities as the IPPS; therefore, we adopted a method to ensure the statistical accuracy of CCRs under the IPF PPS. Specifically, we adopted the following procedure in the RY 2005 IPF PPS final rule:

• Calculated two national ceilings, one for IPFs located in rural areas and one for IPFs located in urban areas.
• Computed the ceilings by first calculating the national average and the standard deviation of the CCR for both urban and rural IPFs using the most recent CCRs entered in the most recent Provider Specific File (PSF) available.

For FY 2025, we are proposing to continue following this methodology. To determine the rural and urban ceilings, we multiplied each of the standard deviations by 3 and added the result to the appropriate national CCR average (either rural or urban). The proposed upper threshold CCR for IPFs in FY 2025 is 2.3362 for rural IPFs, and 1.8600 for urban IPFs, based on current CBSA-based geographic designations. If an IPF's CCR is above the applicable ceiling, the ratio is considered statistically inaccurate, and we assign the appropriate national (either rural or urban) median CCR to the IPF.

We apply the national median CCRs to the following situations:

• New IPFs that have not yet submitted their first Medicare cost report. We continue to use these national median CCRs until the facility's actual CCR can be computed using the first tentatively or final settled cost report.
• IPFs whose overall CCR is in excess of three standard deviations above the corresponding national geometric mean (that is, above the ceiling).
• Other IPFs for which the Medicare Administrative Contractor (MAC) obtains inaccurate or incomplete data with which to calculate a CCR.

We are proposing to update the FY 2025 national median and ceiling CCRs for urban and rural IPFs based on the CCRs entered in the latest available IPF PPS PSF.

Specifically, for FY 2025, to be used in each of the three situations listed previously, using the most recent CCRs entered in the CY 2023 PSF, we provide an estimated national median CCR of 0.5720 for rural IPFs and a national median CCR of 0.4200 for urban IPFs. These calculations are based on the IPF's location (either urban or rural) using the current CBSA-based geographic designations. A complete discussion regarding the national median CCRs appears in the RY 2005 IPF PPS final rule (69 FR 66961 through 66964).

Lastly, we are proposing that if more recent data become available, we would use such data to calculate the rural and urban national median and ceiling CCRs for FY 2025.

4. Requirements for Reporting Ancillary Charges and All-Inclusive Status Eligibility Under the IPF PPS

a. Background

As discussed in section III.E.4.b of this proposed rule, to analyze variation in cost between patients with different characteristics, it is crucial for us to have complete cost information about each patient, including data on ancillary services provided. Currently, IPFs and psychiatric units are required to report ancillary charges on cost reports. As specified at 42 CFR 413.20, hospitals are required to file cost reports on an annual basis and maintain sufficient financial records and statistical data for proper determination of costs payable under the Medicare program.

However, our ongoing analysis has found a notable increase in the number of IPFs, specifically for-profit freestanding IPFs, that appear to be erroneously identifying on form CMS-2552-10, Worksheet S-2, Part I, line 115, as eligible for filing all-inclusive cost reports. These hospitals identifying as eligible for filing all-inclusive cost reports (indicating that they have one charge covering all services) are consistently reporting no ancillary charges or very minimal ancillary charges and are not using charge information to apportion costs in their cost report. Generally, based on the nature of IPF services and the conditions of participation applicable to IPFs, we expect to see ancillary services and correlating charges, such as labs and drugs, on most IPF claims.^[3]

In the FY 2016 IPF PPS final rule (80 FR 46693 through 46694), we discussed analysis conducted to better understand IPF industry practices for future IPF PPS refinements. This analysis revealed that in 2012 to 2013, over 20 percent of IPF stays show no reported ancillary charges, such as laboratory and drug charges, on claims. In the FY 2016 IPF PPS final rule (80 FR 46694), FY 2017 IPF PPS final rule (81 FR 50513), FY 2018 IPF PPS final rule (82 FR 36784), FY 2019 IPF PPS final rule (83 FR 38588), and FY 2020 IPF PPS final rule (84 FR 38458), we reminded providers that we only pay the IPF for services furnished to a Medicare beneficiary who is an inpatient of that IPF, except for certain professional services, and payments are considered to be payments in full for all inpatient hospital services provided directly or under arrangement (see 42 CFR 412.404(d)), as specified in 42 CFR 409.10.

On November 17, 2017, we issued Transmittal 12, which made changes to the hospital cost report form CMS-2552-10 (OMB No. 0938-0050) and included cost report level 1 edit 10710S, effective for cost reporting periods ending on or after August 31, 2017. Edit 10710S required that cost reports from psychiatric hospitals include certain ancillary costs or the cost report will be rejected. On January 30, 2018, we issued Transmittal 13, which changed the implementation date for Transmittal 12 to be for cost reporting periods ending on or after September 30, 2017. CMS suspended edit 10710S effective April 27, 2018, pending evaluation of the application of the edit to all-inclusive rate providers. We issued Transmittal 15 on October 19, 2018, reinstating the requirement that cost reports from psychiatric hospitals, except all-inclusive rate providers, include certain ancillary costs. This requirement is still currently in place. For details, we refer readers to see these Transmittals, which are available on the CMS website at https://www.cms.gov/​medicare/​regulations-guidance/​transmittals.

Under IPF PPS regulations at 42 CFR 412.404(e), all inpatient psychiatric facilities paid under the IPF PPS must meet the recordkeeping and cost reporting requirements as specified at § 413.24. Historically, in accordance with § 413.24(a)(1), most hospitals that were approved to file all-inclusive cost reports were Indian Health Services (IHS) hospitals, government-owned psychiatric and acute care hospitals, and nominal charge hospitals. Although IPFs are no longer reimbursed on the basis of reasonable costs, we continue to expect that most IPFs, other than government-owned or tribally owned IPFs, should report cost data that is based on an approved method of cost finding and on the accrual basis of accounting. The option to elect to file an all-inclusive rate cost report is limited to providers that do not have a charge structure and that, therefore, must use an alternative statistic to apportion costs associated with services rendered to Medicare beneficiaries.

Current cost reporting rules allow hospitals that do not have a charge structure to file an all-inclusive cost report using an alternative cost allocation method. We refer readers to the Provider Reimbursement Manual (PRM) 15-1; chapter 22, § 2208 for detailed information on the requirements to file an alternative method.

b. Challenges Related to Missing IPF Ancillary Cost Data

In general, most providers allocate their Medicare costs using costs and charges as described at § 413.53(a)(1)(i) and referred to as the Departmental Method, which is the ratio of beneficiary charges to total patient charges for the services of each ancillary department. For cost reporting periods beginning on or after October 1, 1982, the cost report uses the Departmental Method to apportion the cost of the department to the Medicare program. Added to this amount is the cost of routine services for Medicare beneficiaries, determined based on a separate average cost per diem for all patients for general routine patient care areas as required at § 413.53(a)(1)(i) and (e); and 15-1, chapter 22, § 2200.1.^[4]

We use cost-to-charge ratios (CCRs) from Medicare cost reports as the method of establishing reasonable costs for hospital services and as the basis for ratesetting for several hospital prospective payment systems. In general, detailed ancillary cost and charge information is necessary for accurate Medicare ratesetting. When hospitals identify as all-inclusive, they are excluded from ratesetting because they do not have CCRs but use an alternative basis for apportioning costs. When hospitals erroneously identify as all-inclusive but have a charge structure, data that is necessary for accurate Medicare ratesetting is improperly excluded.

Since the issuance of Transmittal 15, we have continued to identify an increase in the number of IPFs, specifically for-profit freestanding IPFs, that appear to be erroneously identifying on form CMS- 2552-10, Worksheet S-2, Part I, line 115, as filing all-inclusive cost reports. In conjunction with the FY 2023 IPF PPS proposed rule (87 FR 19428 through 19429), we posted a report on the CMS website that summarizes the results of the latest analysis of more recent IPF cost and claim information for potential IPF PPS adjustments and requested comments about the results summarized in the report. The report showed that approximately 23 percent of IPF stays were trimmed from the data set used in that analysis because they were stays at facilities where fewer than 5 percent of their stays had ancillary charges. The report is available on the CMS website at https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-psychiatric-facility/​ipf-reports-and-educational-resources.

Section 4125 of the CAA, 2023 authorizes the Secretary to collect data and information, specifically including charges related to ancillary services, as appropriate to inform revisions to the IPF PPS.

In the FY 2024 IPF PPS proposed rule (88 FR 21270 through 21272), we included a request for information (RFI) related to the reporting of charges for ancillary services, such as labs and drugs, on IPF claims. We were interested in better understanding IPF industry practices pertaining to the billing and provision of ancillary services to inform statutorily mandated IPF PPS refinements. We stated that we were considering whether to require charges for ancillary services to be reported on claims and potentially reject claims if no ancillary services are reported, and whether to consider payment for such claims to be inappropriate or erroneous and subject to recoupment.

In response to the comment solicitation, we received a comment from MedPAC regarding facilities that do not report ancillary charges on most or any of their claims. MedPAC stated that it is not known: whether IPFs fail to report ancillary charges separately because they were appropriately bundled with all other charges into an all-inclusive per diem rate; if no ancillary charges were incurred because the IPF cares for a patient mix with lower care needs or inappropriately fails to furnish the kinds of care reflected in ancillary charges when medically necessary; or if ancillary charges for services furnished during the IPF stay are inappropriately billed outside of the IPF base rate (unbundling). MedPAC recommended CMS conduct further investigation into the lack of certain ancillary charges and whether IPFs are providing necessary care and appropriately billing for inpatient psychiatric services under the IPF PPS.

MedPAC also encouraged CMS to require the reporting of ancillary charges and clarify the requirements related to IPFs' “all-inclusive-rate” hospital status. MedPAC noted that it observed in cost report data that IPFs that previously were not all-inclusive-rate hospitals have recently changed to an all-inclusive-rate status. MedPAC noted that the timing of many of these changes appears to correspond to CMS's transmittals requiring ancillary services to be reported on cost reports for IPFs that do not have an all-inclusive rate.

Other commenters, including IPFs and hospital associations, responded to the RFI stating that the lack of ancillary charges on claims does not indicate a lack of services being provided. The commenters strongly opposed any claim-level editing and stated that reporting ancillary charges at the claim level would be inefficient and burdensome, particularly for government and IHS all-inclusive hospitals.

c. Clarification of Eligibility Criteria for the Option To Elect To File an All-Inclusive Cost Report

After taking into consideration the feedback we received from both MedPAC and IPF providers, for FY 2025 we are clarifying the eligibility criteria to be approved to file all-inclusive cost reports. Only government-owned or tribally owned facilities are able to satisfy these criteria, and thus only these facilities will be permitted to file an all-inclusive cost report for cost reporting periods beginning on or after October 1, 2024.

We remind readers that in order to be approved to file an all-inclusive cost report, hospitals must either have an all-inclusive rate (one charge covering all services) or a no-charge structure.^[5] We are clarifying that this does not mean any hospital can elect to have an all-inclusive rate or no-charge structure. Our longstanding policy as discussed in the PRM 15-1, chapter 22, § 2208.1, only allows a hospital to use an all-inclusive rate or no charge structure if it has never had a charge structure in place. In addition, we are clarifying that our expectation is that any new IPF would have the ability to have a charge structure under which it could allocate costs and charges. As previously stated, only a government-owned or tribally owned facility will be able to satisfy these criteria and will be eligible to file its cost report using an all-inclusive rate or no charge structure.

For cost reporting periods beginning on or after October 1, 2024, we will issue instructions to the MACs and put in place edits to operationalize our longstanding policy that only government-owned or tribally owned IPF hospitals are permitted to file an all-inclusive cost report. All other IPF hospitals must have a charge structure and must report ancillary costs and charges on their cost reports. IPFs that have previously filed an all-inclusive cost report erroneously will no longer be able to do so. We further note that to the extent government-owned or tribally owned hospitals can report ancillary charges on their cost reports, we strongly encourage them to do so to allow CMS to review and analyze complete and accurate data.

We believe clarifying the current eligibility criteria to be approved to file all-inclusive cost reports and implementing these operational changes will appropriately require freestanding IPFs with the ability to have a charge structure, that is, all IPFs other than those which are government-owned or tribally owned, to track and report ancillary charge information. In addition, we expect that more IPFs reporting ancillary charge information will result in an increase of IPFs having a CCR, which will in turn result in an increased number of IPFs being included in ratesetting. Therefore, we believe these operational changes will improve the quality of data reported, which will result in increased accuracy of future payment refinements to the IPF PPS.

Furthermore, we believe collecting charges of ancillary services from freestanding IPFs supports the directive for competition under the Executive Order on Promoting Competition in the American Economy as it facilitates accurate payment, cost efficiency, and transparency.^[6]

F. Refinement Standardization Factor

Section 1886(s)(5)(D)(iii) of the Act, as added by section 4125(a) of the CAA, 2023, states that revisions in payment implemented pursuant to section 1886(s)(5)(D)(i) for a rate year shall result in the same estimated amount of aggregate expenditures under this title for psychiatric hospitals and psychiatric units furnished in the rate year as would have been made under this title for such care in such rate year if such revisions had not been implemented. We interpret this to mean that revisions in payment adjustments implemented for FY 2025 (and for any subsequent fiscal year) must be budget neutral.

Historically, we have maintained budget neutrality in the IPF PPS using the application of a standardization factor, which is codified in our regulations at § 412.424(c)(5) to account for the overall positive effects resulting from the facility-level and patient-level adjustments. As discussed in section III.B.1 of this proposed rule, section 124(a)(1) of the BBRA required that we implement the IPF PPS in a budget neutral manner. In other words, the amount of total payments under the IPF PPS, including any payment adjustments, must be projected to be equal to the amount of total payments that would have been made if the IPF PPS were not implemented. Therefore, we calculated the standardization factor by setting the total estimated IPF PPS payments, taking into account all of the adjustment factors under the IPF PPS, to be equal to the total estimated payments that would have been made under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been implemented. A step-by-step description of the methodology used to estimate payments under the TEFRA payment system appears in the RY 2005 IPF PPS final rule (69 FR 66926).

We believe the budget neutrality requirement of section 4125(a) of the CAA, 2023 is consistent with our longstanding methodology for maintaining budget neutrality under the IPF PPS. Therefore, for FY 2025, we are proposing to apply a refinement standardization factor in accordance with our existing policy at § 412.424(c)(5). This policy requires us to update IPF PPS patient-level adjustment factors, ED adjustment, and ECT per treatment amount as proposed in this FY 2025 IPF PPS proposed rule, in such a way that total estimated payments to IPFs for FY 2025 are the same with or without the changes (that is, in a budget neutral manner) by applying a refinement standardization factor to the IPF PPS rates. We are proposing to use the following steps to ensure that the rates reflect the FY 2025 update to the patient-level adjustment factors (as previously discussed in section III.C and III.D of this proposed rule, and summarized in Addendum A) in a budget neutral manner:

Step 1: Simulate estimated IPF PPS payments using the FY 2024 IPF patient-level and facility-level adjustment factor values and FY 2024 ECT payment per treatment (available on the CMS website).

Step 2: Simulate estimated IPF PPS payments using the proposed FY 2025 IPF patient-level and facility-level adjustment factor values (see Addendum A of this proposed rule, which is available on the CMS website) and ECT per treatment amount based on the CY 2022 geometric mean cost for ECT under the OPPS.

Step 3: Divide the amount calculated in step 1 by the amount calculated in step 2. The resulting quotient is the proposed FY 2025 refinement standardization factor of 0.9514.

Step 4: Apply the FY 2025 refinement standardization factor from step 3 to the FY 2024 IPF PPS Federal per diem base rate and ECT per treatment amount (based on the CY 2022 geometric mean cost for ECT under the OPPS), after the application of the wage index budget neutrality factor and the IPF market basket increase reduced by the productivity adjustment described in section III.A of this proposed rule to determine the FY 2025 IPF PPS Federal per diem base rate and FY 2025 ECT payment amount per treatment.

IV. Requests for Information (RFI) To Inform Future Revisions to the IPF PPS in Accordance With the CAA, 2023

As discussed in the following sections, we are requesting information on two main topics to inform future revisions to the IPF PPS, in accordance with the CAA, 2023. First, we are requesting information regarding potential revisions to the IPF PPS facility-level adjustments. Second, we are requesting information regarding the development of a patient assessment instrument under the IPFQR program.

Please note, each of these sections is a request for information (RFI) only. In accordance with the implementing regulations of the Paperwork Reduction Act of 1995 (PRA), specifically 5 CFR 1320.3(h)(4), this general solicitation is exempt from the PRA. Facts or opinions submitted in response to general solicitations of comments from the public, published in the Federal Register or other publications, regardless of the form or format thereof, provided that no person is required to supply specific information pertaining to the commenter, other than that necessary for self-identification, as a condition of the agency's full consideration, are not generally considered information collections and therefore not subject to the PRA. Respondents are encouraged to provide complete but concise responses. This RFI is issued solely for information and planning purposes; it does not constitute a Request for Proposal (RFP), applications, proposal abstracts, or quotations. This RFI does not commit the U.S. Government to contract for any supplies or services or make a grant award. Further, CMS is not seeking proposals through this RFI and will not accept unsolicited proposals. Responders are advised that the U.S. Government will not pay for any information or administrative costs incurred in response to this RFI; all costs associated with responding to this RFI will be solely at the interested party's expense. Not responding to this RFI does not preclude participation in any future procurement, if conducted. It is the responsibility of the potential responders to monitor this RFI announcement for additional information pertaining to this request. Please note that CMS will not respond to questions about the policy issues raised in this RFI. CMS may or may not choose to contact individual responders. Such communications would only serve to further clarify written responses. Contractor support personnel may be used to review RFI responses. Responses to this notice are not offers and cannot be accepted by the U.S. Government to form a binding contract or issue a grant. Information obtained as a result of this RFI may be used by the U.S. Government for program planning on a non-attribution basis. Respondents should not include any information that might be considered proprietary or confidential. This RFI should not be construed as a commitment or authorization to incur cost for which reimbursement would be required or sought. All submissions become U.S. Government property and will not be returned. CMS may publicly post the comments received, or a summary thereof.

A. Request for Information Regarding Revisions to IPF PPS Facility-Level Adjustments

The CAA, 2023 added section 1886(s)(5)(D) to require CMS to revise the IPF PPS methodology for determining payment rates for FY 2025, and for any subsequent FY as determined appropriate by the Secretary. As detailed in sections III.C and III.D of this proposed rule, we are proposing to revise the patient-level payment adjustments in FY 2025 and retain the current facility-level payment adjustments for rural location and teaching status. We have also conducted analysis of the IPF PPS facility-level adjustments using an updated regression analysis of cost and claims data for CY 2019 through 2021, as discussed in section III.C.3. of this proposed rule. The updated analysis identified potential changes in the regression factors for rural location and teaching status and suggests there may be value in including a new facility-level variable for safety net patient population, based on the Medicare Safety Net Index (MSNI) methodology developed by MedPAC for the IPPS. We note that the analysis of MSNI builds on prior analysis that CMS conducted regarding the applicability of an adjustment for disproportionate share intensity. Our review is ongoing and may be used to inform future rulemaking.

In the following sections, we describe the results of our latest analysis and request public comment on them. We are interested in comments regarding whether it would be appropriate to consider proposing revisions to the IPF PPS facility-level adjustments in the future based on the results of our latest regression analysis in future years.

1. Adjustment for Rural Location

In our MedPAR data set, which included data from CY 2019 through CY 2021, 101,483 stays, or 12.6 percent of all stays, were at rural IPFs. Our analysis shows that the regression coefficient for rural stays is 1.19. This means that holding all other variables constant and controlling for area wage differences, stays at rural IPFs have approximately 19-percent higher cost per day than stays at urban IPFs. As previously discussed, we did not include control variables in our regression model to account for occupancy rate. However, we note that if we included these control variables, we estimate the rural adjustment in the regression would decrease to approximately 1.13.

In addition, as discussed later in section IV.A.3 of this proposed rule, we evaluated the potential inclusion of a new variable for facilities' safety net patient population, as measured by the MSNI ratio. We observe that the inclusion of the MSNI ratio in the regression model would have an impact on the rural adjustment factor. In the regression model that includes the MSNI ratio, the rural adjustment factor is 1.16. In other words, if we were to adopt an MSNI payment adjustment, our FY 2025 regression model indicates that the rural adjustment factor would decrease relative to the rural adjustment factor calculated without the MSNI variable. However, for rural facilities with a high level of safety net patients, the combined effect of the rural adjustment and a safety net adjustment would increase payments. These results are presented in Table 17, and we are seeking public comments on these results.

We have modeled informational impacts reflecting the potential change in payments, as discussed in section IV.A.4 of this proposed rule, though we note future additional data and analysis may produce results that differ from those presented in this proposed rule.

2. Teaching Adjustment

In the IPF PPS payment methodology, the teaching status for each facility is calculated as one plus the facility's ratio of intern and resident FTEs to the average daily census (69 FR 66954 through 66955). The teaching variable used in the regression is the natural log of each facility's teaching status, resulting in a continuous variable with a distribution ranging from 0.0000 to 1.6079. The payment adjustment for teaching status, as explained in section III.D.2 of this proposed rule, is calculated by raising a facility's teaching ratio to the power of the teaching status coefficient derived from the regression analysis.

In our updated regression analysis of data for CY 2019 through CY 2021, there were 155,458 stays in teaching facilities, comprising 19.3 percent of IPF stays for the time period. As previously discussed in this proposed rule, we found that the occupancy variables used in the original IPF PPS regression model were correlated with rural status, and have been removed in this updated model. We note that if we were to include occupancy control variables in the regression model, the adjustment for teaching status would increase to 1.0087.

The teaching status variable continues to be statistically significant at the 0.001 level in all of our updated models; in other words, we found that a facility's teaching status explains differences in costs between IPF stays. As shown in Table 18, the teaching status coefficient would increase in either updated regression model compared to its current value.

As discussed in section IV.A.4. of this proposed rule, we have modeled informational impacts reflecting the potential change in payments from these adjustment factors. We are seeking public comment on these results. We note that future additional data and analysis may produce results that differ from those presented in this proposed rule.

3. Adjustment for Safety Net Patient Population

a. Prior Analysis of Disproportionate Share Hospital Status

In contrast to other Medicare hospital payment systems, the IPF PPS does not have an adjustment that recognizes disproportionate share intensity. Section 1886(s) of the Act does not require any specific adjustment of this type, nor does it require the use of any particular methodology. In the past, we have explored the application of the disproportionate share hospital (DSH) variable used in other Medicare prospective payment systems (that is, the sum of the proportion of Medicare days of care provided to recipients of Supplemental Security Income and the proportion of the total days of care provided to Medicaid beneficiaries) for the IPF PPS. We refer readers to the RY 2005 IPF PPS final rule (69 FR 66958 through 66959) and the FY 2023 IPF PPS final rule (87 FR 46865). For psychiatric units, both proportions are specific to the unit and not the entire hospital.

In the RY 2005 IPF PPS final rule, we explained that the DSH variable was highly significant in our cost regressions; however, we found that facilities with higher DSH had lower per diem costs. We note that the previously cited study for the American Psychiatric Association also found the same results. The relationship of high DSH with lower costs cannot be attributed to downward bias in the Medicaid proportion due to the IMD exclusion. This is because public psychiatric hospitals already have lower costs on average than other types of IPFs. Therefore, if we had proposed a DSH adjustment based on the regression analysis, IPFs with high DSH shares would have been paid lower per diem rates (69 FR 66958).

In the FY 2023 IPF PPS proposed rule, we summarized and discussed the results of more recent analysis using data from 2018 (87 FR 19428 through 19429). In response to that proposed rule, commenters encouraged CMS to continue evaluating ways to increase IPF PPS payments for disproportionate share intensity. MedPAC recommended that we consider the applicability of the MSNI, which has previously been discussed in the context of the IPPS, to the IPF PPS. As discussed in the following paragraphs, we have conducted analysis of the MSNI and are soliciting comments on our findings.

b. Analysis of the Medicare Safety Net Index in the IPF PPS

(1) Background

MSNI is an index that MedPAC developed as its recommended alternative to the current statutorily required methodology for disproportionate share payments to IPPS hospitals. In their March 2023 Report to Congress, MedPAC recommend that MSNI would better target scarce Medicare resources to support hospitals that are key sources of care for low-income Medicare beneficiaries and may be at risk of closure.^[7] For further discussion of this safety net index in the context of the Medicare program, we refer readers to the FY 2024 IPPS final rule (88 FR 58640), which includes a discussion of how MSNI could be calculated for acute care hospitals and an RFI on the potential use of MSNI or other safety net indicators in the IPPS, such as the area deprivation index (ADI) or Social Deprivation Index (SDI).

For our analysis, we constructed an MSNI for each IPF in our data set, which we calculated as the sum of three ratios:

• The low-income subsidy (LIS) volume ratio, which is the ratio of total stays for low-income beneficiaries to a facility's total stays for Medicare beneficiaries. For our analysis, low-income beneficiaries are identified based on dual-enrollment or enrollment in Part D low-income subsidies, and stays are identified from MedPAR claims. This ratio was defined the same way in the FY 2024 IPPS final rule's discussion of MSNI (88 FR 59306).
• The proportion of revenue spent on uncompensated care (UCC), defined the same way as it was in the FY 2024 IPPS final rule's discussion of MSNI (88 FR 59306). UCC and total revenue are available data elements from the hospital cost report, but only for the acute care hospital. These elements are not currently detailed at the level of the IPF unit.
• The Medicare dependency ratio, which is a hospital's total covered days for Medicare patients divided by its total patient days. This information comes from the hospital cost report. We have also defined this ratio in the same way as it was defined in the FY 2024 IPPS final rule's discussion of MSNI (88 FR 59306).

The final MSNI score is calculated as: LIS Volume Ratio + Proportion of Revenue Spent on UCC ratio + 0.5 * Medicare Dependency Ratio. This formula follows MedPAC's methodology based on its analysis of data for the IPPS hospital setting. As discussed in its March 2023 Report to Congress, the Medicare Dependency Ratio is multiplied by 0.5 because MedPAC's prior analysis of costs in the IPPS setting found that the Medicare Dependency Ratio had approximately half the effect on cost as the other two components of MSNI.

(2) Regression Analysis Results

The adjusted r-square, a measure of how much of the variation in costs between stays our model can explain, increases by approximately 2.8 percent when we add the variable for MSNI to the updated model analyzing cost and claims data for CY 2019 through CY 2021. The adjusted r-square for the model without the MSNI variable is 0.32340, while the adjusted r-square for the model with the MSNI variable is 0.33250. Our regression analysis indicates an MSNI coefficient of 0.5184, which is statistically significant at the .001 level.

Section 1886(s)(5)(D)(iii) of the Act, as added by section 4125(a) of the CAA, 2023, states that revisions in payment implemented pursuant to section 1886(s)(5)(D)(i) for a rate year shall result in the same estimated amount of aggregate expenditures under this title for psychiatric hospitals and psychiatric units furnished in the rate year as would have been made under this title for such care in such rate year if such revisions had not been implemented. Therefore, our estimates of payments associated with a potential MSNI payment adjustment include the application of a standardization factor, which we note would reduce the IPF PPS Federal per diem base rate by approximately $245. Total payments to IPFs would remain the same, but there would be significant distributional impacts, which would reduce payments to IPFs with a lower MSNI and increase payments to IPFs with a higher MSNI. We refer readers to section IV.A.4 of this proposed rule for informational analysis and discussion of the potential distributional impacts estimated for the MSNI payment adjustment.

We note that for certain elements of the MSNI calculation, some data was not available for IPFs at the same level of detail available for IPPS hospitals. We also identified that for some elements, data reported by IPFs may be incomplete. First, as mentioned above, both UCC amounts and total revenue amounts are reported at the hospital level only. As a result, we were able to calculate a UCC ratio for IPF units based on the overall ratio of the hospital's UCC to its revenues. This assumes that a hospital's overall UCC ratio would be comparable to that of its IPF unit. However, because we lack unit-level data, we are not able to validate this assumption. Table 20 shows that most freestanding IPF hospitals are not reporting any UCC, which leads to lower MSNI values for these IPFs. We recognize that the absence of UCC for nonprofit IPFs, which we believe in fact provide a significant amount of UCC, may reflect differences in reporting, rather than provision of UCC.

There are also a number of key differences between our analysis and the way that MedPAC has recommended that MSNI be applied to payments in the IPPS setting. For the IPPS, MedPAC recommends to the Congress in their March 2023 report that they create an MSNI pool of funds for MSNI add-on payments of about $2 billion, which could be increased each year by the market basket update. MedPAC contemplates hospitals choosing between an MSNI payment and other special payment rates designed to protect access, for example, in rural areas, or the adoption of a percentage-based cap on all special payment rates.^[8] In contrast, our modeling of an MSNI payment adjustment in the IPF PPS, assumes that IPFs could be eligible for both an MSNI payment and the payment adjustment for rural location, for example, without a cap imposed. Our modeling also assumes that an MSNI payment adjustment would be budget neutral; in other words, the payment would not be an add-on. In contrast to the recommended approach for the IPPS, which would come from a new funding pool, we estimate that the application of an MSNI adjustment would affect the Federal IPF PPS per diem base rate. As a result, the MSNI payment in our model would represent a redistribution of funds within the IPF PPS, as is statutorily required under section 4125(a) of the CAA, 2023.

We constructed the MSNI variable in our regression model similarly to the construction of the teaching adjustment (that is, as the natural log of a facility's MSNI ratio plus 1). Consequently, a payment adjustment derived from our regression results would work like the teaching status adjustment: the MSNI adjustment factor is expressed in an un-exponentiated form. A provider's MSNI factor plus one would be raised to the power of the MSNI adjustment factor to calculate the facility's MSNI payment adjustment.

We are considering the potential operational changes that would be necessary to implement an adjustment for MSNI in the future. For example, we anticipate the need to periodically recalculate facilities' MSNI ratios, which could potentially correspond to a facility's cost report settlement process. We also anticipate the need to develop a reconciliation process, should such an adjustment for MSNI be implemented in the future. Further, we expect that because a facility's LIS ratio would not be an available data element on the hospital cost report, we may need to develop and publish a facility-level file with this information or consider collecting additional data on the hospital cost report. As discussed in the following section, we are seeking public comment on our regression results, as well as our methodology used to construct the MSNI variable for IPFs, and on the operational considerations we have noted. We note that future additional data and analysis produce results that differ from those presented in this proposed rule.

(3) Request for Information

We are particularly seeking comment on the following questions:

• Should we consider adjusting payment using MedPAC's MSNI formula with adaptations, as described above? What, if any, changes to the methodology should we consider for the IPF setting? For example, should we develop a separate payment adjustment for each component (that is, the low-income ratio, uncompensated care ratio, and Medicare dependency ratio)?
• We note that our construction of the MSNI did not scale or index facility-level variables to a national standard or median value. We anticipate that doing so would result in less of a change to the IPF Federal per diem base rate but would still result in comparable distributional impacts (that is, IPFs with lower MSNIs would receive lower payments, and IPFs with higher MSNIs would receive higher payments). Should we consider scaling or indexing the MSNI to a national average MSNI for all IPFs?
• Is MedPAC's MSNI formula, as adapted, an accurate and appropriate measure of the extent to which an IPF acts as a safety-net hospital for Medicare beneficiaries?
• Should additional data be collected through the cost report to improve the calculation of MSNI, such as collecting UCC and revenue at the IPF unit level?
• Is the current cost report data submitted by IPFs sufficiently valid and complete to support the implementation of an MSNI payment? We note our concerns about the low or non-existent amounts reported for uncompensated care for freestanding IPFs and the use of hospital-level UCC and revenue amounts to calculate the UCC ratio for IPF units.
• What administrative burden or challenges might providers face in reporting their UCC and low-income patient stays?
• Would IPFs have the information necessary to report their low-income patient stays to CMS for the purpose of the MSNI calculation? What challenges might IPFs face in gathering and reporting this information?
• In the FY 2023 IPPS proposed rule, CMS noted that, when calculating the MSNI, the following circumstances may be encountered: new hospitals (for example, hospitals that begin participation in the Medicare program after the available audited cost report data), hospital mergers, hospitals with multiple cost reports and/or cost reporting periods that are shorter or longer than 365 days, cost reporting periods that span fiscal years, and potentially aberrant data. How should CMS consider addressing these circumstances when calculating the MSNI for IPFs?

4. Informational Impacts of Potential Facility-Level Revisions on IPF PPS Payments

We estimate that an MSNI payment adjustment in concert with the potential rural payment adjustment and teaching adjustments detailed in this section would have a refinement standardization factor of 0.7202. In other words, adoption of these facility-level payment adjustments as described in this section of this proposed rule would decrease the Federal per diem base rate by $244.81. In contrast, we estimate that updating only the rural and teaching adjustments without MSNI would have a refinement standardization factor of 0.9926, which would decrease the Federal per diem base rate by $6.48.

Estimates of distributional impacts by facility type, location, ownership, teaching status, and region are detailed in Table 21. We are seeking public comment on these informational impacts to potentially inform future rulemaking.

To illustrate the impacts of these potential changes to the IPF PPS facility-level adjustments, our analysis begins with the same FY 2023 IPF PPS claims (based on the 2023 MedPAR claims, December 2023 update) as discussed in section VIII.C of this proposed rule. We begin with estimated FY 2025 IPF PPS payments using these 2023 claims, the proposed FY 2025 IPF PPS Federal per diem base rate and ECT per treatment amount, the proposed refinements to the FY 2025 IPF PPS patient and facility level adjustment factors, and the proposed FY 2025 IPF PPS wage index. At each stage, total outlier payments are maintained at 2 percent of total estimated FY 2025 IPF PPS payments.

Each of the following changes is added incrementally to this baseline model in order for us to isolate the effects of each change:

• The potential updates to the IPF teaching adjustment and rural adjustment, without the addition of an adjustment for MSNI.
• Adding an adjustment for MSNI and reducing the IPF rural adjustment and teaching adjustment as shown in the third column of Tables 17 and 18 of this proposed rule.

B. Request for Information (RFI)—Patient Assessment Instrument Under IPFQR Program (IPF PAI) To Improve the Accuracy of the PPS

Section 4125(b)(1) of CAA, 2023 amended section 1886(s)(4) of the Act, by inserting a new paragraph (E), to require IPFs participating in the IPFQR Program to collect and submit to the Secretary certain standardized patient assessment data, using a standardized patient assessment instrument (PAI) developed by the Secretary, for RY 2028 (FY 2028) and each subsequent rate year. IPFs must submit such data with respect to at least the admission to and discharge of an individual from the IPF, or more frequently as the Secretary determines appropriate. For IPFs to meet this new data collection and reporting requirement for RY 2028 and each subsequent rate year, the Secretary must implement a standardized PAI that collects data with respect to the following categories: functional status; cognitive function and mental status; special services, treatments, and interventions for psychiatric conditions; medical conditions and comorbidities; impairments; and other categories as determined appropriate by the Secretary. This IPF-PAI must enable comparison of the patient assessment data across all IPFs which submit these data. In other words, the data must be standardized such that data from IPFs participating in the IPFQR Program can be compared; the IPF-PAI each IPF administers must be made up of identical questions and identical sets of response options to which identical standards and definitions apply.

As we develop the IPF-PAI, in accordance with these new statutory requirements, we seek to collect information that will help us achieve the following goals: (1) improve the quality of care in IPFs, (2) improve the accuracy of the IPF PPS in accordance with section 4125(b)(2) of CAA, 2023, and (3) improve health equity.^[9] In this Request for Information (RFI), we are soliciting comments for development of this IPF-PAI, in accordance with these new statutory requirements, and to achieve these goals.

This RFI consists of four sections. The first section discusses a general framework or set of principles for development of the IPF-PAI. The second section outlines potential approaches that could be used to develop the items or data elements that make up the PAI. This section also discusses patient assessment data elements in use in PAIs for skilled nursing facilities and other healthcare settings that could potentially be adapted for use in the IPF-PAI. The third section outlines potential approaches that could be used to collect patient assessment data. Finally, the fourth section solicits public comment on the principles and approaches listed in the first three sections and seeks other input regarding the IPF-PAI.

1. Framework for Development of the IPF-PAI

We considered similar legislatively derived PAIs previously implemented for certain post-acute care (PAC) providers to inform the goals and guiding principles for the IPF-PAI because of similarities of section 4125(b) of CAA, 2023 to the Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT Act) (Pub. L. 113-185, October 6, 2014), codified at section 1899B of the Act. Similar to section 4125(b) of CAA, 2023, section 1899B of the Act requires certain PAC providers, specifically home health agencies (HHAs), skilled nursing facilities (SNFs), inpatient rehabilitation facilities (IRFs), and long-term care hospitals (LTCHs), to submit certain standardized patient assessment data (as set forth at section 1899B(b)(1)(B)) using a standardized PAI under the PAC providers' respective quality reporting programs. While IPFs are acute care providers and not PAC providers, given the similarities between the CAA, 2023 and section 1899B of the Act, we considered the goals and guiding principles that we followed to implement section 1899B of the Act for certain PAC providers and examined their applicability and appropriateness for IPFs.

We previously identified four key considerations when assessing Standardized Patient Assessment Data Elements for the PAC PAIs to collect: (1) Overall clinical relevance; (2) Interoperable exchange to facilitate care coordination during transitions in care; (3) Ability to capture medical complexity and risk factors that can inform both payment and quality; and (4) Scientific reliability and validity, general consensus agreement for its usability.^[10] For the reasons discussed in the following subsections, we believe that these considerations are also appropriate for the development of the IPF-PAI. In addition, we seek to balance the need to collect meaningful patient data to improve care with the need to minimize administrative burden. The remainder of this section describes each of these considerations in the context of the IPF-PAI. As we discuss in section IV.B.4.a of this proposed rule, we are soliciting comment on these considerations.

a. Overall Clinical Relevance

In each category of assessment required by section 1886(s)(4)(E)(ii), as added by section 4125(b) of CAA, 2023, (functional status; cognitive function and mental status; special services, treatments, and interventions for psychiatric conditions; medical conditions and comorbidities; impairments, and other categories as determined appropriate by the Secretary), we seek to establish Standardized Patient Assessment Data Elements that providers can use to support high quality care and outcomes in the IPF setting. As we evaluate Standardized Patient Assessment Data Elements in PAIs designed for other care settings, we intend to work with CMS Medical Officers, including psychiatrists, to consider the clinical relevance for IPF patients as a determining factor in whether an item merits inclusion in the IPF-PAI. For an example of a PAI in use in another setting, we refer readers to the IRF-PAI instrument available at https://www.cms.gov/​files/​document/​irf-pai-version-40-eff-10012022-final.pdf. We are particularly interested in learning about specific instruments and tools in each area of assessment that have high clinical relevance in the IPF setting and welcome comments regarding Standardized Patient Assessment Data Elements that may not be clinically relevant to the IPF setting.

To ensure the clinical relevance of the instrument across a diverse group of IPF patients, we are considering structuring the assessment with conditional questions, so that certain sets of questions are only indicated if the questions are relevant to the patient. Furthermore, we note that some data elements may only be appropriate for collection at certain times during the patient's stay (for example, only at admission or only at discharge). We solicit comments regarding the most effective structure to employ in the development of the IPF-PAI.

b. Interoperability

Interoperability is a key priority and initiative at CMS. Across the organization, we aim to promote the secure exchange, access, and use of electronic health information to support better informed decision making and a more efficient healthcare system. As a part of this effort, we make interoperability a priority for standardized data collection. We intend to ensure that the IPF-PAI meets Health Level 7® (HL7®) Fast Healthcare Interoperability Resources® (FHIR®) standards.

As part of our interoperability considerations, we are interested in whether Standardized Patient Assessment Data Elements already in use in the CMS Data Element Library (DEL) are appropriate and clinically relevant for the IPF setting. In CY 2021, approximately 8,000 admissions to IPFs were individuals transferred from SNFs or IRFs. We are interested in whether Standardized Patient Assessment Data Elements already used in the DEL can be used to better support interoperability between providers, given the high number of transfers.

c. Ability To Capture Medical Complexity and Risk Factors

We intend to expand our efforts to refine the IPF PPS to increase the accuracy of the payment system by better identifying patient characteristics that best predict resource use during an IPF stay. To identify Standardized Patient Assessment Data Elements that would help predict resource use, we intend to evaluate Standardized Patient Assessment Data Elements for their ability to explain medical complexity, the need for special services and treatments, and to measure case-mix differences that impact costs. It is our expectation that an IPF-PAI that effectively differentiates treatment needs between patients will also help IPFs plan and distribute their resources. Our hope is that the IPF-PAI can therefore integrate with IPFs' business practices. In addition, Standardized Patient Assessment Data Elements that capture patient risk factors can contribute to quality of care and patient safety.

d. Scientific Reliability and Validity

Standardized Patient Assessment Data Elements considered for inclusion in the IPF-PAI must be scientifically reliable and valid in IPF settings. We intend to draw on our significant experience in development of quality measures in the IPFQR Program and development of Standardized Patient Assessment Data Elements for other PAIs, such as the IRF-PAI and the Minimum Data Set (MDS) (the PAI for SNFs), in our development of Standardized Patient Assessment Data Elements for the IPF-PAI.^[11] It is important to note that the statutorily required timeframe for implementation of the IPF-PAI for RY 2028 limits our ability to develop and test a full battery of new Standardized Patient Assessment Data Elements for the launch of the IPF-PAI. We anticipate the need and opportunity for incremental revisions to the IPF-PAI in the future.

We anticipate that our development process for new Standardized Patient Assessment Data Elements will include working with teams of researchers for each category including a group of advisors made up of clinicians and academic researchers for each team with expertise in IPFs. We expect to convene a Technical Expert Panel (TEP) to provide expert input on new and existing Standardized Patient Assessment Data Elements that merit consideration for inclusion and testing, including environmental scans and reviews of scientific literature. In an ideal scenario, Standardized Patient Assessment Data Elements would be tested in a representative sample of IPFs for appropriateness in different IPF settings and across a range of patients. Standardized Patient Assessment Data Elements would be tested for inter-rater (that is, consistency in results regardless of who is administering the assessment) and inter-organizational reliability, for validity in all IPF settings, for internal consistency, and for breadth of application among a range of IPF patients. We anticipate that Standardized Patient Assessment Data Elements would also need to be tested for their ability to detect differences among patients and costs of treatment. Due to the constraints of the statutorily required implementation timeframe, it may not be possible to complete all testing before launching the IPF-PAI.

The process for scientifically testing each question and set of responses is lengthy and resource-intensive. This process is based on the steps for quality measure development described in the Blueprint Measure Lifecycle,^[12] developed by the CMS Measures Management System. These steps include literature review and environmental scanning; various levels of field testing to understand the “real world” performance of the data elements; and iterative expert and interested parties engagement to include broader perspectives on topics, candidate data elements, and interpretation of testing results. If appropriate, using data currently collected by IPFs or Standardized Patient Assessment Data Elements that have been tested and validated for use in other clinical settings can reduce these timeframes because test data are already available.

e. Administrative Burden

In evaluating Standardized Patient Assessment Data Elements for inclusion in the IPF-PAI, we are considering the burden of data collection through the PAI and aiming to minimize additional burden by considering whether any data that is currently collected through IPFQR Program measures or on IPF claims could be collected as Standardized Patient Assessment Data Elements to avoid duplication of data that IPFs are already reporting. We are also considering how collecting some data for some IPFQR Program measures through the IPF-PAI and collecting other data through the Hospital Quality Reporting (HQR) system would affect the reporting burden for participating IPFs. Licensing, permissions costs, or copyright restrictions that would add to administrative costs and burdens are also a consideration as we evaluate existing PAIs and mechanisms or tools for submitting IPF-PAI data.

As we develop the IPF-PAI, we are interested in receiving information about how to find a balance between collecting the most relevant and useful information and the administrative burden of administering the assessment and submitting the assessment data.

2. Elements of the IPF-PAI

Section 1886(s)(4)(E)(ii) of the Act, added by section 4125(b)(1)(C) of the CAA, 2023, requires that the standardized patient assessment data to be collected in the IPF-PAI must be with respect to six enumerated categories.

a. Functional Status

The first enumerated category of data for the IPF-PAI is functional status. Section 1886(s)(4)(E)(ii)(I) of the Act provides that functional status may include mobility and self-care at admission to a psychiatric hospital or unit and before discharge from a psychiatric hospital or unit. We note that information in this category is generally found in a patient's discharge summary and are interested in learning about standardized elements that correspond to functional status as relevant to IPFs. We are interested in what assessments may be currently in use in the IPF setting and meet criteria for inclusion in the IPF-PAI.

b. Cognitive Function and Mental Status

The second enumerated category of data for the IPF-PAI is cognitive function and mental status. Section 1886(s)(4)(E)(ii)(II) of the Act provides that cognitive function may include the ability to express ideas and to understand, and mental status may include depression and dementia. We note that in the IPF setting, a patient's diagnoses, which can be abstracted from their medical chart, provide some information related to this category. We are aware that IPFs may be currently assessing cognitive function using existing instruments. We are interested in hearing from IPFs about which instruments are currently in use to measure cognitive function in IPFs and which have high clinical relevance for the IPF setting.

c. Special Services, Treatments, and Interventions

The third enumerated category of data for the IPF-PAI is special services, treatments, and interventions for psychiatric conditions. Section 1886(s)(4)(E)(ii)(III) of the Act neither addresses what these terms mean nor provides any illustrative examples. As discussed in section V.C. of this rule, the IPFQR Program already collects information about the use of restraint and seclusion through quality measures (Hospital Based Inpatient Psychiatric Services (HBIPS)-2, Hours of Physical Restraint, and HBIPS-3, Hours of Seclusion Use), while claims include information about ECT treatments provided. Other areas of interest in this category may include high-cost medications, use of chemical restraints, one-to-one observation, and high-cost technologies. We are interested in whether these or any other special services, treatments, or interventions should be considered for inclusion in the IPF-PAI.

d. Medical Conditions and Comorbidities

The fourth enumerated category of data for the IPF-PAI is medical conditions and comorbidities. Section 1886(s)(4)(E)(ii)(IV) of the Act provides that medical conditions and comorbidities may include diabetes, congestive heart failure, and pressure ulcers. We note that IPF claims record a significant number of medical conditions and comorbidities to receive the payment adjustment for comorbidities in the IPF PPS and conditions that are relevant to the IPF stay. In reviewing Standardized Patient Assessment Data Elements listed in this category in PAIs in use in PAC settings, we observed that these PAIs include Standardized Patient Assessment Data Elements regarding pain interference in this category, such as the effect of pain on sleep, pain interference with therapy activities, and pain interference with day-to-day activities. We are interested in learning from commenters whether these existing data elements from the PAC settings would be clinically relevant for inclusion in this category for the IPF-PAI.

e. Impairments

The fifth enumerated category of data for the IPF-PAI is impairments. Section 1886(s)(4)(E)(ii)(V) of the Act provides that impairments may include incontinence and an impaired ability to hear, see, or swallow. PAIs in use in other settings include Standardized Patient Assessment Data Elements regarding hearing and vision (for example, Section B, “Hearing, Speech, and Vision” of the IRF-PAI Version 4.2 (Effective October 1, 2024)).^[13] We are interested both in whether Standardized Patient Assessment Data Elements regarding additional impairments merit consideration for the IPF-PAI, and whether the Standardized Patient Assessment Data Elements regarding hearing and vision included in the IRF-PAI are appropriate for the IPF setting. We note that the Standardized Patient Assessment Data Element categories are not intended to be duplicative, so we would seek to avoid any overlap in measuring cognitive deficits in the Cognitive Function category with the Impairments category.

f. Other Categories Deemed Appropriate

The sixth enumerated category of data for the IPF-PAI is other categories as determined appropriate by the Secretary. We believe this provision allows for flexibility to include additional areas in the IPF-PAI.

One of our strategic priorities, as laid out in the CMS Strategic Plan,^[14] reflects our deep commitment to improvements in health equity by addressing the health disparities that underlie our health system. In line with that strategic priority, we are interested in Standardized Patient Assessment Data Elements that would provide insight about any demographic factors (for example, race, national origin, primary language, ethnicity, sexual orientation, and gender identity) as well as SDOH (for example, housing status and food security) associated with underlying inequities. We are also interested in whether there are Standardized Patient Assessment Data Elements that would provide insight into special interventions that IPFs are providing to support patients after discharge which could serve to potentially reduce the incidence of readmissions.

We note that, beginning with mandatory reporting of CY 2025 data for FY 2027 payment determination, the IPFQR Program includes the Screening for SDOH measure, which assesses the percentage of patients, aged 18 years and over at the time of admission, who are screened for five specific health-related social needs (HRSNs)—food insecurity, housing instability, transportation needs, utility difficulties, and interpersonal safety, but which does not require reporting of that information at the patient-level (88 FR 51117). Furthermore, we note that PAIs adopted for the PAC settings discussed previously include collection of SDOH data under section 1899B(b)(1)(B)(vi) of the Act, which contains a similar provision for other categories deemed appropriate by the Secretary.^[15]

We note that, if we deem it appropriate to add a SDOH category for the IPF-PAI and these SDOH data are included as Standardized Patient Assessment Data Elements in the PAI, they could potentially be used to risk adjust or stratify measures collected for the IPFQR Program. We are interested in learning whether using some of these SDOH data adopted in other PAIs to risk adjust or stratify these measures would make the measures in the IPFQR Program more meaningful.

3. Implementation of the PAI—Data Submission

We plan to develop flexible methods for providers to submit IPF-PAI data to CMS, including batch uploads in specified formats and a portal for submission of files. We welcome public comment on tools and methods for submission of data that balance administrative burden and ease of use.

4. Request for Information on IPF-PAI

In this proposed rule, we are requesting information from the public to inform the selection of Standardized Patient Assessment Data Elements to be collected on the IPF-PAI and the implementation process. We are seeking information about PAIs IPFs currently use upon admission and discharge, as well as information about how IPFs estimate resource needs to determine capacity before a patient is admitted. We are also seeking information about methods for IPFs to submit patient assessment data and the potential administrative burden on IPFs, MACs, and CMS. Finally, we are seeking input on the relationship between the IPF-PAI and the measures within the IPFQR Program.

We solicit comment on the following topics:

a. Principles for Selecting Standardized Patient Assessment Data Elements

• To what extent do you agree with the principles for selecting and developing Standardized Patient Assessment Data Elements for the IPF-PAI?

• What, if any, principles should CMS eliminate from the Standardized Patient Assessment Data Element selection criteria?

• What, if any, principles should CMS add to the Standardized Patient Assessment Data Element selection criteria?

b. Patient Assessments Recommended for Use in the IPF-PAI

• Are there PAIs currently available for use, or that could be adapted or developed for use in the IPF-PAI, to assess patients': (1) functional status; (2) cognitive function and mental status; (3) special services, treatments, and interventions for psychiatric conditions; (4) medical conditions and comorbidities; (5) impairments; (6) health disparities; or (7) other areas not mentioned in this RFI?

c. Functional Status Standardized Patient Assessment Data Elements

• What aspects of function are most predictive of medical complexity or increased resource needs to treat a patient in the IPF setting?
• Which of the Standardized Patient Assessment Data Elements related to mobility (that is, the ability to toilet transfer, walk 10 feet, car transfer, walk 10 feet on an uneven surface, 1 step up (that is, a curb), 4 steps up, 12 steps up, and pick up an object) currently collected by PAC settings in their respective PAIs are clinically relevant in the IPF setting? Do they otherwise meet the principles for inclusion in the IPF-PAI?

d. Cognitive Function and Mental Status Standardized Patient Assessment Data Elements

• What aspects of cognitive function and mental status are most predictive of medical complexity or increased resource needs to treat a patient in the IPF setting?
• What components or instruments are used to assess cognitive function, mental status, or a combination thereof upon admission? What, if any, differences are there between assessments administered at admission and at discharge? What are the components of the mental status assessments administered at admission and discharge?

e. Special Services, Treatments, and Interventions for Psychiatric Conditions Standardized Patient Assessment Data Elements

• What special services, treatments, and interventions are most predictive of increased resource intensity during an IPF stay?
• Do data currently collected as part of the IPFQR Program related to special services and treatments (such as HBIPS-2 Hours of Physical Restraint Use and HBIPS-3 Hours of Seclusion Use) meet the criteria for inclusion in the IPF-PAI?

f. Medical Conditions and Comorbidities Standardized Patient Assessment Data Elements

• Is the Standardized Patient Assessment Data Element regarding pain interference (effect on sleep, interference with therapy activities, interference with day-to-day activities) currently collected by PAC settings in their respective PAIs clinically relevant in the IPF setting? Does it otherwise meet the criteria for inclusion in the IPF-PAI?
• Do the medical conditions and comorbidities coded on IPF claims meet the criteria for inclusion in the IPF-PAI?

g. Impairments Standardized Patient Assessment Data Elements

• Are Standardized Patient Assessment Data Elements related to impairments (that is, the ability to hear and see in adequate light) currently collected PAC settings in their respective PAIs clinically relevant in the IPF setting? Do they otherwise meet the principles for inclusion in the IPF-PAI?
• What impairments are most predictive of increased resource intensity during an IPF stay?

h. Other Categories of Standardized Patient Assessment Data Elements

• What other assessment elements would contribute to the clinical utility of the IPF-PAI?
• What other assessment elements would best capture medical complexity in the interest of refining and improving the accuracy of the IPF PPS?
• What other assessment elements would inform CMS's understanding of health equity for IPF patients?
• Are there special interventions that IPFs provide which support patients after discharge, and which could serve to reduce the incidence of hospital readmissions for psychiatric conditions? What, if any, assessment elements would inform CMS's understanding of such interventions?

i. Implementation

• We anticipate that IPFs will need to make changes to systems and processes and train staff in order to administer the assessment and submit assessment data by the implementation date. What operational or practical limitations would IPFs face in making those necessary changes? Are there particular categories of Standardized Patient Assessment Data Elements that would be more or less feasible for IPFs to operationalize? We are particularly interested in impacts to facilities of varying sizes and ownership characteristics.
• What forms of training and guidance would be most useful for CMS to provide to support IPFs in the implementation of the IPF-PAI?

j. Relationship to the IPFQR Program

• Would having some measures which require data submission through the HQR system and having other measures, which require data collection and submission through the IPF-PAI increase operational complexity or administrative burden? If so, how would you recommend mitigating this complexity or burden?
• Would any of the current chart-abstracted measures be easier to report through the IPF-PAI? If so, which measures?
• Would any of the current measures in the program be more meaningful if they were stratified or risk-adjusted using data from the required patient assessment categories or other categories not specified by the CAA, 2023 that should be added to the IPF-PAI?
• What new measure concepts, which would use data collected through Standardized Patient Assessment Data Elements in the IPF-PAI, should we consider?

V. Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program

A. Background and Statutory Authority

The Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program is authorized by section 1886(s)(4) of the Act, and it applies to psychiatric hospitals and psychiatric units paid by Medicare under the IPF PPS (see section II.A. of this proposed rule for a detailed discussion of entities covered under the IPF PPS). Section 1886(s)(4)(A)(i) requires the Secretary to reduce by 2 percentage points the annual update to the standard Federal rate for discharges occurring during such rate year ^[16] for any IPF that does not comply with quality data submission requirements under IPFQR program, set forth in section 1886(s)(4)(C) of the Act, with respect to an applicable rate year.

Section 1886(s)(4)(C) of the Act requires IPFs to submit to the Secretary data on quality measures specified by the Secretary under section 1886(s)(4)(D) of the Act. Except as provided in section 1886(s)(4)(D)(ii) of the Act, section 1886(s)(4)(D)(i) of the Act requires that any measure specified by the Secretary must have been endorsed by the consensus-based entity (CBE) with a contract under section 1890(a) of the Act. Section 1886(s)(4)(D)(ii) of the Act provides that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the CBE with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

Section 4125(b)(1) of CAA, 2023 amended section 1886(s)(4) of the Act, by inserting a new paragraph (E), to require IPFs participating in the IPFQR Program to collect and submit to the Secretary certain standardized patient assessment data, using a standardized patient assessment instrument (PAI) developed by the Secretary, for RY 2028 (FY 2028) and each subsequent rate year. We refer readers to section IV.B of this proposed rule in which we solicit public comment on the development of this PAI.

We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589) for a discussion of the background and statutory authority of the IPFQR Program. We have codified procedural requirements and reconsideration and appeals procedures for IPFQR Program decisions in our regulations at 42 CFR 412.433 and 412.434. Consistent with previous IPFQR Program regulations, we refer to both inpatient psychiatric hospitals and psychiatric units as “facilities” or “IPFs.” This usage follows the terminology in our IPF PPS regulations at § 412.402.

For additional information on procedural requirements related to statutory authority, participation and withdrawal, data submission, quality measure retention and removal, extraordinary circumstances exceptions, and public reporting we refer readers to 42 CFR 412.433 Procedural requirements under the IPFQR Program.

For the IPFQR Program, we refer to the year in which an IPF would receive the 2-percentage point reduction to the annual update to the standard Federal rate as the payment determination year. An IPF generally meets IPFQR Program requirements by submitting data on specified quality measures in a specified time and manner during a data submission period that occurs prior to the payment determination year. These data reflect a period prior to the data submission period during which the IPF furnished care to patients; this period is known as the performance period. For example, for a measure for which CY 2025 is the performance period which is required to be submitted in CY 2026 and affects FY 2027 payment determination, if an IPF did not submit the data for this measure as specified during CY 2026 (and meets all other IPFQR Program requirements for the FY 2027 payment determination) we would reduce by 2-percentage points that IPF's update for the FY 2027 payment determination year.

B. Measure Adoption

We strive to put patients and caregivers first, ensuring they are empowered to partner with their clinicians in their healthcare decision making using information from data driven insights that are increasingly aligned with meaningful quality measures. We support technology that reduces burden and allows clinicians to focus on providing high-quality healthcare for their patients. We also support innovative approaches to improve quality, accessibility, and affordability of care while paying particular attention to improving clinicians' and beneficiaries' experiences when interacting with our programs. In combination with other efforts across HHS, we believe the IPFQR Program helps to incentivize IPFs to improve healthcare quality and value while giving patients and providers the tools and information needed to make the best individualized decisions. Consistent with these goals, our objective in selecting quality measures for the IPFQR Program is to balance the need for information on the full spectrum of care delivery and the need to minimize the burden of data collection and reporting. We have primarily focused on measures that evaluate critical processes of care that have significant impact on patient outcomes and support CMS and HHS priorities for improved quality and efficiency of care provided by IPFs. When possible, we also propose to incorporate measures that directly evaluate patient outcomes and experience. We refer readers to the CMS National Quality Strategy,^[17] the Behavioral Health Strategy,^[18] the Framework for Health Equity,^[19] and the Meaningful Measures Framework ^[20] for information related to our priorities in selecting quality measures.

1. Measure Selection Process

Section 1890A(a) of the Act requires that the Secretary establish and follow a pre-rulemaking process, in coordination with the CBE contracted under 1890(a) of the Act, to solicit input from multi-stakeholder groups on the selection of quality and efficiency measures for the IPFQR Program. Before being proposed for inclusion in the IPFQR Program, measures are placed on a list of Measures Under Consideration (MUC list), which is published annually. Following publication on the MUC list, a multi-stakeholder group convened by the CBE reviews the measures under consideration for the IPFQR Program, among other federal programs, and provides input on those measures to the Secretary. Under the Partnership for Quality Measurement (PQM), which is convened by the entity which currently holds the contract under 1890(a) of the Act, this process is known as the Pre-Rulemaking Measure Review (PRMR). We consider the input and recommendations provided by this multi-stakeholder group in selecting all measures for the IPFQR Program, including the 30-Day Risk-Standardized All-Cause Emergency Department (ED) Visit Following an IPF Discharge measure discussed in this proposed rule.

2. Proposal To Adopt the 30-Day Risk-Standardized All-Cause ED Visit Following an IPF Discharge Measure Beginning With the CY 2025 Performance Period/FY 2027 Payment Determination

a. Background

We have consistently stated our commitment to identifying measures that examine the care continuum for patients with mental health conditions and substance use disorders and to quantify outcomes following IPF-discharge (see for example, the adoption of the Medication Continuation Following Hospitalization in an IPF measure in the FY 2020 IPF PPS Final Rule, 84 FR 38460 through 38462). Post-discharge outcomes are an important part of our measurement strategy because patient-centered discharge planning and coordination of care for patients with any combination of mental health conditions and substance use disorders improves long-term outcomes, including reducing readmissions and other post-discharge acute care services.^[21 22]

Although not all post-discharge acute care visits are preventable, there are actions that the IPF can take to maximize the chance for patients' successful community reintegration.^[23] For example, care transition models to reduce the need for additional acute care following an inpatient stay have been adapted to the inpatient psychiatric setting. To implement these models, IPFs may need to consider how to include the patient and their caregivers, including family, in discharge planning, how to communicate with post-discharge providers, and how to ensure whole-person care for patients during and following their discharge.^[24] Specifically, IPFs may need to assist patients in connecting with outpatient providers, such as coordinating with the patient and their caregiver to schedule the patient's first post-discharge follow-up appointment, arranging for the patient's intensive outpatient (IOP) care, or connecting to peer support services. Additionally, IPFs may need to identify and address barriers patients may face in accessing medications and adhering to scheduled post-discharge follow-up appointments. Barriers may include financial factors, transportation, and childcare, which may necessitate support from social services, beginning during hospitalization and continuing after discharge.^[25 26] Barriers may also include the patient's concerns regarding the stigmatization associated with seeking care post-discharge. This can be addressed through treatment provided during the IPF stay.^[27 28] Improvements in patient experience of care and patient-centeredness of care have been associated with improved follow-up post-discharge and a reduction in patients requiring post-discharge acute care.^[29 30] In summary, by proactively addressing potential barriers to post-charge care, improving patient experience of care and patient-centeredness of care, and implementing care transition models, IPFs can reduce the need for post-discharge acute care.

The IPFQR Program currently has three measures that assess post-discharge outcomes: (1) Follow-up After Psychiatric Hospitalization (FAPH); (2) Medication Continuation Following Inpatient Psychiatric Discharge; and (3) Thirty Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization (CBE #2860, the IPF Unplanned Readmission measure). Each of these measures serves a unique role in assessing care coordination and post-discharge outcomes.

The FAPH measure, which we adopted in the FY 2022 IPF PPS Final Rule (86 FR 42640 through 42645), uses Medicare FFS claims to determine the percentage of inpatient discharges from an IPF stay for which the patient received a follow-up visit for treatment of mental illness. The FAPH measure represents an important component of post-discharge care coordination, specifically the transition of care to an outpatient provider. However, this measure does not quantify patient outcomes.

The Medication Continuation Following Inpatient Psychiatric Discharge measure, which we adopted in FY 2020 IPF PPS Final Rule (84 FR 38460 through 38465), assesses whether patients admitted to IPFs with diagnoses of Major Depressive Disorder (MDD), schizophrenia, or bipolar disorder filled at least one evidence-based medication prior to discharge or during the post-discharge period. Medication continuation is important for patients discharged from the IPF setting with these disorders because of significant negative outcomes associated with non-adherence to medication regimes. However, this measure does not quantify patient outcomes with respect to the use of acute care services post-discharge.

The IPF Unplanned Readmission measure, which we adopted in the FY 2017 IPPS/LTCH PPS final rule (81 FR 57241 through 57246), assesses outcomes associated with worsening condition, potentially due to insufficient discharge planning and post-discharge care coordination, by assessing post-discharge use of acute care. The IPF Unplanned Readmission measure estimates the incidence of unplanned, all-cause readmissions to IPFs or short-stay acute care hospitals following discharge from an eligible IPF index admission. A readmission is defined as any admission that occurs within 3 to 30 days after the discharge date from an eligible index admission to an IPF, except those considered planned.^[31] However, this measure does not quantify the proportion of patients 18 and older with an ED visit, without subsequent admission, within 30 days of discharge from an IPF. Without collecting this information in a measure, we believe there is a gap in our understanding regarding patients' successful reintegration into their communities following their IPF discharge.

To further understand this gap, we analyzed post-discharge outcomes using claims data. In this analysis, we determined that, for patients discharged from IPFs, the risk-adjusted rate of ED visits after an IPF discharge between June 1, 2019 and July 31, 2021 (excluding the first two quarters of 2020 due to the COVID-19 public health emergency) was 20.7 percent. The rate of readmissions captured under the IPF Unplanned Readmission measure for this same period was 20.1 percent.^[32] This means that approximately 40 percent of patients discharged from an IPF had either an ED visit or an unplanned readmission within 30-days of IPF discharge, but only about half of those visits are being captured in the publicly reported IPF Unplanned Readmission measure. Visits to an ED within 30 days of discharge from an IPF (regardless of whether that visit results in a hospital readmission, observation stay, discharge, or patient leaving without being seen) often indicate deteriorating or heightened mental or physical health needs. That is, these visits often represent a patient seeking care for symptoms that were present during the patient's stay in the IPF, regardless of whether the symptom was the reason for the admission, that have become worse for the patient in the time since discharge. Therefore, we believe that IPFs and the public would benefit from having these data made publicly available to inform care decisions and quality improvement efforts. Specifically, members of the public could use these data to inform care decisions and IPFs could use these data to compare their performance to that of similar IPFs. For example, by having these data publicly reported IPFs could compare their performance with that of other IPFs with similar patient populations, a comparison which is not possible without this measure. If IPFs identified that other IPFs with similar patient populations had better rates of post-discharge ED visits (that is, other IPFs had fewer patients seek care in an ED within 30 days of discharge from the IPF), the IPF could identify a need to evaluate discharge planning and post-discharge care coordination to identify process changes which could improve outcomes.

To address this gap, we developed and are proposing the inclusion of the new, claims-based 30-Day Risk-Standardized All-Cause ED Visit Following an IPF Discharge measure (the IPF ED Visit measure) in the IPFQR program beginning with the CY 2025 performance period/FY 2027 payment determination. This proposed IPF ED Visit measure aims to provide information to patients, caregivers, other members of the public, and IPFs about the proportion of patients who seek care in ED in the 30 days following discharge from an IPF, but are not admitted as an inpatient to an acute care hospital or IPF. This proposed measure would assess the proportion of patients 18 and older with an ED visit, including observation stays, for any cause, within 30 days of discharge from an IPF, without subsequent admission.

We recognize that not all post-discharge ED visits are preventable, nor are all post-discharge ED visits associated with the initial IPF admission. However, we developed an all-cause ED visit rate, as opposed to a more narrowly focused measure of ED admissions for mental health or substance use concerns, for three primary reasons. First, such a measure aligns most closely with the IPF Unplanned Readmission measure as this measure is also an all-cause measure. Second, an all-cause measure emphasizes the importance of whole-person care for patients. Whole-person care, during the inpatient stay and through referral at discharge, includes addressing the conditions that may jeopardize a patient's health, but are not the reason for admission to the IPF, if the IPF has reason to identify these conditions during the course of treatment. For example, if an IPF were to identify through metabolic screening that a patient has diabetes, it would be appropriate for that IPF to recommend appropriate follow-up for that patient, such as with a primary care provider, endocrinologist, or dietician. Such post-discharge coordination of care could prevent the patient from seeking acute care after discharge from the IPF for complications of diabetes, such as diabetic ketoacidosis. Third, this measure includes ED visits for all conditions because patients visiting the ED may do so for physical symptoms associated with a mental health condition or substance use disorder. An example is a patient with anxiety that presents to the ED with chest pain and shortness of breath. If the clinician documents the primary diagnosis as chest pain (R07.9) or shortness of breath (R06.02), the patient would not be included in a mental health and substance use-specific IPF ED Visit measure, despite their history of anxiety (F41.9), a potential contributor to their presenting symptoms at the ED. We recognize that it is possible that such a visit may not be related to the patient's anxiety. However, while not all acute care visits after discharge from an IPF are preventable or necessarily related to the quality of care provided by the IPF, there is evidence that improvements in the quality of care for patients in the IPF setting can reduce rates of patients seeking acute care after discharge from an IPF, representing an improved outcome for patients.^[33]

Additionally, we considered whether 30 days was an appropriate timeframe for this measure. That is, we sought to identify whether a measure that assessed post-discharge ED visits over a period shorter or longer than 30 days would be more appropriate. Because IPFs are already familiar with interpreting data for the 30-day period in the IPF Unplanned Readmission measure, we determined that it would be appropriate to maintain the 30-day period for the IPF ED Visit measure. Additionally, by maintaining the same timeframe as the IPF Unplanned Readmission measure, we can provide IPFs and patients with a more complete picture of acute care among IPF patients after discharge from the IPF.

Pursuant to the Meaningful Measures 2.0 Framework (a CMS initiative that identifies priority domains for measures within CMS Programs ^[34] ), this measure addresses the “Seamless Care Coordination” and the “Person-Centered Care” quality domains by encouraging facilities to provide patient-centric discharge planning and support post-discharge care transitions. The IPF ED Visit measure also aligns with the CMS National Quality Strategy Goals ^[35] of “Engagement” and “Outcomes and Alignment.” It supports outcomes and alignment because this measure provides a quantified estimate of one post-discharge outcome that patients may experience, that is a post-discharge acute care visit that does not result in an admission. It also supports the Behavioral Health Strategy ^[36] domains of “Quality of Care” and “Equity and Engagement” because engaging patients to improve post-discharge outcomes is an element of providing quality care. Furthermore, similar to the Meaningful Measures domain of “Person-Centered Care,” this measure supports the Universal Foundation domain of “Person-Centered Care.”

b. Overview of Measure

The IPF ED Visit measure was developed with input from clinicians, patients, and policy experts; the measure was subject to the pre-rulemaking process required by section 1890A of the Act, as discussed further in section V.B.1 of this rule. Consistent with the CMS key elements of the CMS Measure Development Lifecycle,^[37] we began with measure conceptualization during which we performed a targeted literature review and solicited input from a behavioral health technical expert panel (TEP). This allowed us to ensure that this topic addresses a gap that is important to interested parties. After confirming this, we developed the measure specifications for the IPF ED Visit measure. With these specifications, we issued a 30-day call for public comment in the Federal Register and performed empirical testing using claims data, including modeling for risk-adjustment. After refining the measure specifications based on testing and public comment, we performed an equity analysis in which we tested the risk-adjustment methodology to ensure that the measure does not reflect access issues related to patient demographics instead of quality of care. By following steps in accordance with the Measure Development Lifecycle, we sought to ensure that this is a vetted, valid, reliable, and ready-to-implement claims-based measure which would assess the proportion of patients 18 and older with an ED visit, including observation stays, for any cause, within 30 days of discharge from an IPF, without subsequent admission. By using the same definitions of index admission and patient populations as those used in the IPF Unplanned Readmission measure, we have designed the IPF ED Visit measure to complement the IPF Unplanned Readmission measure to the extent possible. We have also sought to minimize administrative burden by developing this as a claims-based measure so that it adds no information collection burden to clinicians and staff working in the IPF setting.

(1) Measure Calculation

The focus population for this measure is adult Medicare FFS patients with a discharge from an IPF. The measure is based on all eligible index admissions from the focus population. An eligible index admission is defined as any IPF admission for which the patient meets the following criteria: (1) age 18 or older at admission; (2) discharged alive from an IPF; (3) enrolled in Medicare FFS Parts A and B during the 12 months before the admission date, the month of admission, and at least one month after the month of discharge from the index admission (that is, the original stay in an IPF); and (4) discharged with a principal diagnosis that indicates a psychiatric disorder. Excluded from the measure are patients discharged against medical advice (AMA) from the IPF index admission (because the IPF may not have had the opportunity to conduct full discharge planning for these patients); patients with unreliable data regarding death demographics or a combination thereof in their claims record (because these data are unreliable, they may lead to inaccuracies in the measure calculation); patients who expired during the IPF stay (because post-discharge care is not applicable to these patients); patients with a discharge resulting in a transfer to another care facility (because the receiving care facility would be responsible for discharge planning for these patients); and patients discharged but readmitted within 3 days of discharge, also known as an interrupted stay (because interrupted stays are often reflective of patient needs outside of the IPF, such as treatment for another condition).

To calculate the measure, we would use the following data sources which are all available from Medicare administrative records and data submitted by providers through the claims process: (1) Medicare beneficiary and coverage files, which provide information on patient demographic, enrollment, and vital status information to identify the measure population and certain risk factors; (2) Medicare FFS Part A records, which contain final action claims submitted by acute care and critical access hospitals, IPFs, home health agencies, and skilled nursing facilities to identify the measure population, readmissions, and certain risk factors; and (3) Medicare FFS Part B records, which contain final action claims submitted by physicians, physician assistants, clinical social workers, nurse practitioners, and other outpatient providers to identify certain risk factors. To ensure that diagnoses result from encounters with providers trained to establish diagnoses, this measure would not use claims for services such as laboratory tests, medical supplies, or other ambulatory services. Index admissions and ED visits would be identified in the Medicare FFS Part A records. Comorbid conditions for risk-adjustment would be identified in the Medicare Part A and Part B records in the 12 months prior to admission, including the index admission. Demographic and FFS enrollment data would be identified in the Medicare beneficiary and coverage files.

To calculate the IPF ED Visit measure, CMS would: (1) identify all IPF admissions in the one-year performance period; (2) apply inclusion and exclusion criteria to identify index admissions; (3) identify ED visits and observation stays within 30 days of discharge from each index admission; (4) identify risk factors in the 12 months prior to index admission and during the index admission; and (5) run hierarchical logistic regression to compute the risk-standardized ED visit rate for each IPF.^[38] This hierarchical logistic regression would allow us to apply the risk-adjustment factors developed in measure testing to ensure that measure results are comparable across IPFs regardless of the clinical complexity of each IPF's patient population.

(2) Pre-Rulemaking Measure Review and Measure Endorsement

As required under section 1890A of the Act, the CBE established the Partnership for Quality Measurement (PQM) to convene clinicians, patients, measure experts, and health information technology specialists to participate in the pre-rulemaking process and the measure endorsement process. The pre-rulemaking process, also called the Pre-Rulemaking Measure Review (PRMR), includes a review of measures published on the publicly available list of Measures Under Consideration (MUC List) by one of several committees convened by the PQM for the purpose of providing multi-stakeholder input to the Secretary on the selection of quality and efficiency measures under consideration for use in certain Medicare quality programs, including the IPFQR Program. The PRMR process includes opportunities for public comment through a 21-day public comment period, as well as public listening sessions. The PQM posts the compiled comments and listening session inputs received during the public comment period and the listening sessions within five days of the close of the public comment period.^[39] More details regarding the PRMR process may be found in the CBE's Guidebook of Policies and Procedures for Pre-Rulemaking Measure Review and Measure Set Review, including details of the measure review process in Chapter 3.^[40]

The CBE-established PQM also conducts the measure endorsement and maintenance (E&M) process to ensure measures submitted for endorsement are evidence-based, reliable, valid, verifiable, relevant to enhanced health outcomes, actionable at the caregiver-level, feasible to collect and report, and responsive to variations in patient characteristics, such as health status, language capabilities, race or ethnicity, and income level, and are consistent across types of health care providers, including hospitals and physicians (see section 1890(b)(2) of the Act). The PQM convenes several E&M project groups twice yearly, formally called E&M Committees, each comprised of an E&M Advisory Group and an E&M Recommendations Group, to vote on whether a measure meets certain quality measure criteria. More details regarding the E&M process may be found in the E&M Guidebook, including details of the measure endorsement process in the section titled, “Endorsement and Review Process.” ^[41]

As part of the PRMR process, the IPF ED Visit measure was reviewed during the PRMR Hospital Recommendation Group meeting on January 18, 2024. For the voting procedures of the PRMR and E&M process, the PQM utilized the Novel Hybrid Delphi and Nominal Group (NHDNG) multi-step process, which is an iterative consensus-building approach aimed at a minimum of 75 percent agreement among voting members, rather than a simple majority vote, and supports maximizing the time spent to build consensus by focusing discussion on measures where there is disagreement. For example, the PRMR Hospital Recommendation Group can reach consensus and have the following voting results: (A) Recommend, (B) Recommend with conditions (with 75 percent of the votes cast as recommend with conditions or 75 percent between recommend and recommend with conditions), and (C) Do not recommend. If no voting category reaches 75 percent or greater (including the combined [A] Recommend and [B] Recommend with conditions) the PRMR Hospital Recommendation Group did not come to consensus and the voting result is “Consensus not reached.” Consensus not reached signals continued disagreement amongst the committee despite being presented with perspectives from public comment, committee member feedback and discussion, and highlights the multi-faceted assessments of quality measures. More details regarding the PRMR voting procedures may be found in Chapter 4 of the PQM Guidebook of Policies and Procedures for Pre-Rulemaking Measure Review and Measure Set Review.^[42] More details regarding the E&M voting procedures may be found in the PQM Endorsement and Maintenance (E&M) Guidebook.^[43] The PRMR Hospital Recommendation Group ^[44] reached consensus and recommended including this measure in the IPFQR Program with conditions.

Seven members of the group recommended adopting the measure into the IPFQR program without conditions; eleven members recommended adoption with conditions; and one committee member voted not to recommend the measure for adoption. Taken together, 94.73 percent of the votes were between recommend & recommend with conditions.

The conditions specified by the PRMR Hospital Recommendation Group were: (1) that the measure be considered for endorsement by a consensus-based entity; and (2) further consideration of how the measure addresses 72-hour transfers to the ED. We have taken those considerations into account and are proposing this measure for adoption because we believe we have adequately addressed the concerns raised by those considerations.

To address the first condition, we have submitted the measure to the CBE for consideration. For more information on submission to and consideration by the CBE we refer readers to section V.B.2.b.(3) of this rule.

The second voting condition requested that we further consider how the measure addresses 72-hour transfers to the ED because of concerns that IPFs may appear to have worse performance if “interrupted stays” are not excluded from the measure. An “interrupted stay” occurs when a patient is discharged from an IPF and readmitted to the same IPF within 72 hours. This frequently occurs when a patient needs medical treatment that is beyond the scope of the IPF, such as care in an ED for an emergent health issue. We believe that this concern is sufficiently addressed in the ED Visit measure's specifications because these “interrupted stays” are excluded from the measure, as described in section V.B.2.b.(1) of this rule. This exclusion is defined as an index admission with a readmission on Days 0, 1, or 2 post-discharge. In other words, patients transferred to the ED and subsequently readmitted to the IPF within 72 hours are excluded from the measure. Therefore “interrupted stays” are excluded from the measure as per the group's recommendation.

(3) CBE Endorsement

Section 1886(s)(4)(D)(i) of the Act generally requires that measures specified by the Secretary shall be endorsed by the entity with a contract under section 1890(a) of the Act (that is, the CBE). After a measure has been submitted to the CBE, the committee responsible for reviewing the measure evaluates the measure on five domains: (1) Importance; (2) Feasibility; (3) Scientific Acceptability (that is, reliability and validity); (4) Equity; and (5) Use and Usability. Committee members evaluate whether the measure the domain is “Met”, “Not Met but Addressable” or “Not Met” for each domain using a set of criteria provided by the CBE.^[45] When a measure is submitted it is assigned to one of the CBE's projects based on where in the patient's healthcare experience the measure has the most relevance. The five projects are (1) Primary Prevention; (2) Initial Recognition and Management; (3) Management of Acute Events, Chronic Disease, Surgery, Behavioral Health; (4) Advanced Illness and Post-Acute Care; and (5) Cost and Efficiency.

The measure developer submitted the measure for CBE endorsement consideration in the Fall 2023 review cycle. The measure was assigned to the Cost and Efficiency Project. The CBE Cost and Efficiency Endorsement committee met on January 31, 2024 and did not reach consensus regarding the IPF ED Visit measure, with 60.6 percent voting in favor of endorsement or endorsement with conditions and the remaining members voting to not endorse, which is below the 75 percent threshold necessary for the endorsement of the measure, as described in V.B.2.b. During the Cost and Efficiency Endorsement committee's meeting, members of the committee discussed whether an all-cause measure was appropriate and whether IPFs are able to implement interventions to reduce post-discharge acute care.^[46]

As discussed in section V.B.2.a of this proposed rule, an all-cause measure would complement the IPF Unplanned Readmission measure, would emphasize whole-person care, and would capture visits to the ED for patients with physical symptoms associated with mental health conditions. Additionally, evidence shows that there are interventions that reduce post-discharge acute care. These include adopted care transition models, proactively connecting patients with post-discharge providers, identifying and addressing patients' barriers to post-discharge care, and focusing on providing patient-centered care and improving patient experience of care.

Although section 1886(s)(4)(D)(i) of the Act generally requires that measures specified by the Secretary shall be endorsed by the entity with a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) of the Act states that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to a measure that has been endorsed or adopted by a consensus organization identified by the Secretary.

We have determined that this is an appropriate topic for the adoption of a measure absent CBE endorsement because where possible we focus on measures that assess patient outcomes. Unplanned use of acute care after discharge from an IPF is often associated with worsening condition, potentially due to insufficient discharge planning and post-discharge care coordination. While the IPFQR Program currently has a measure that assesses unplanned readmissions after discharge from an IPF, there is a gap in the measure set with respect to unplanned ED visits without a subsequent admission to an acute care hospital or IPF. The IPF ED Visit measure fills that gap. We also reviewed CBE-endorsed measures and were unable to identify any other CBE-endorsed measures that assess outcomes that solely result in a patient's ED visit after the patient's discharge from an IPF. The only endorsed measure that we identified that addresses an IPF patient seeking acute care after discharge is the IPF Unplanned Readmission measure. As we discussed previously, the IPF Unplanned Readmission measure does not assess ED visits that do not result in an admission. Therefore, we believe that the IPF ED Visit measure is an important complement to the IPF Unplanned Readmission measure. We did not find any other measures that assess post-discharge ED visits without a subsequent admission, and therefore the exception in section 1886(s)(4)(D)(ii) of the Act applies.

c. Data Collection, Submission, and Reporting

Because all files used to calculate the IPF ED Visit measure are available on Medicare claims, this measure requires no additional data collection or submission by IPFs. We are proposing a reporting period beginning with data from CY 2025 performance period/FY 2027 payment determination year.

C. Summary of IPFQR Program Measures for the FY IPFQR Program

We are proposing one new measure for the FY 2027 IPFQR Program. If we finalize adoption of this measure, the FY 2027 IPFQR Program measure set would include 16 mandatory and one voluntary measure. Table 22 sets forth the measures in the FY 2027 IPFQR Program.

D. Proposal To Modify Data Submission Requirements for the FY 2027 Payment Determination and Subsequent Years

Section 1886(s)(4)(C) of the Act requires the submission of quality data in a form and manner, and at a time, specified by the Secretary. In the Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and fiscal year 2013 Rates; Hospitals' Resident Caps for Graduate Medical Education Payment Purposes; Quality Reporting Requirements for Specific Providers and for Ambulatory Surgical Centers (FY 2013 IPPS/LTCH PPS) final rule (77 FR 53655), we specified that data must be submitted between July 1 and August 15 of the calendar year preceding a given payment determination year (for example, data were required to be submitted between July 1, 2015 and August 15, 2015 for the FY 2016 payment determination). In the Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and fiscal year 2014 Rates; Quality Reporting Requirements for Specific Providers; Hospital Conditions of Participation; Payment Policies Related to Patient Status (FY 2014 IPPS/LTCH PPS) final rule (78 FR 50899), we clarified that this policy applied to all future years of data submission for the IPFQR Program unless we changed the policy through future rulemaking.

In the FY 2018 IPF PPS final rule (82 FR 38472 through 38473) we updated this policy by stating that the data submission period will be a 45-day period beginning at least 30 days following the end of the data collection period and that we will provide notification of the exact dates through subregulatory means.

In the FY 2022 IPF PPS Final Rule (86 FR 42658 through 42661), we finalized voluntary patient-level data reporting for the FY 2023 payment determination and mandatory patient-level data reporting for chart-abstracted measures within the IPFQR Program beginning with FY 2024 payment determination and subsequent years. The measures currently in the IPFQR Program affected by this requirement are set forth in Table 23.

As we have gained experience with patient-level data submission for the IPFQR program, during the voluntary data submission period for FY 2023 (which occurred in CY 2022) and the first mandatory data submission period for FY 2024 (which occurred in CY 2023), we have observed that annual data submission periods require IPFs to store large volumes of patient data to prepare for transmission to CMS. Furthermore, the volume of data associated with all IPFs reporting a full year of patient-level data during one data submission period creates the risk that systems will be unable to handle the volume of data.

We have reviewed how other quality reporting programs that require patient-level data submission address these concerns and determined that the Hospital Inpatient Quality Reporting (IQR) Program (78 FR 50811) and the Hospital Outpatient Quality Reporting (OQR) Program (72 FR 66872) both require quarterly submission of patient-level data. As we considered requiring quarterly reporting for the IPFQR Program, we also determined that increasing the frequency of data submission would allow additional analysis of measure trends over time. We believe that having additional data points (from additional quarters of data) could allow for more nuanced analyses of the IPFQR Program's measures. Specifically, we would be able to better identify quarterly highs or lows that may be less apparent when data are combined over a full year. We recognize that, if we update data reporting requirements to require reporting four times per year instead of once per year, then IPFs would need to meet four incremental deadlines instead of one deadline, and that this increases the risk that an individual IPF may fail to submit data specified for the measures and not receive its full market basket update. However, we believe that this risk is low because IPFs already have experience submitting some data required by the IPFQR Program on a more frequent basis. Specifically, the COVID-19 Healthcare Personnel (HCP) Vaccination Measure is currently reported into the CDC's National Healthcare Safety Network (NHSN) for one week per month resulting in a quarterly measure result (as originally adopted in the FY 2022 IPF PPS final rule (86 FR 42636) and restated in the FY 2024 IPF PPS final rule (88 FR 51131 through 51132). In addition, if this proposal for quarterly data submission is finalized, data submission for each calendar quarter would be required during a period of at least 45 days beginning three months after the end of the calendar quarter. Table 24 summarizes these proposed deadlines for the CY 2025 and CY 2026 performance periods:

Furthermore, we are proposing that all data which continue to be reported on an annual basis (that is, non-measure data, aggregate measures, and attestations) would be required to be reported concurrently with the data from the fourth quarter of the applicable year. For example, data reflecting the entirety of CY 2025 (that is, non-measure data, aggregate measures, and attestations) would be required by the Q4 2025 submission deadline (that is, May 15, 2026).

We welcome comments on this proposal.

VI. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et seq.), we are required to provide 60-day notice in the Federal Register and solicit public comment before a “collection of information” requirement is submitted to the Office of Management and Budget (OMB) for review and approval. For the purposes of the PRA and this section of the preamble, collection of information is defined under 5 CFR 1320.3(c) of the PRA's implementing regulations.

To fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the 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.

We are soliciting public comment (see section VI.C of this proposed rule) on each of these issues for the following sections of this document that contain information collection requirements. Comments, if received, will be responded to within the subsequent final rule.

The following changes will be submitted to OMB for review under control number 0938-1171 (CMS-10432). We are not proposing any changes that would change any of the data collection instruments that are currently approved under that control number.

In section VI.2 of this proposed rule, we restate our currently approved burden estimates. In section VI.3 of this proposed rule, we estimate the changes in burden associated with update more recent wage rates. Then in section VI.4 of this proposed rule, we estimate the changes in burden associated with the policies proposed in this proposed rule.

A. Wage Estimates

In the FY 2024 IPF PPS final rule, we utilized the median hourly wage rate for Medical Records Specialists, in accordance with the Bureau of Labor Statistics (BLS), to calculate our burden estimates for the IPFQR Program (88 FR 51145). While the most recent data from the BLS reflects a mean hourly wage of $24.56 per hour for all medical records specialists, $26.06 is the mean hourly wage for “general medical and surgical hospitals,” which is an industry within medical records specialists.^[47] We believe the industry of “general medical and surgical hospitals” is more specific to the IPF setting for use in our calculations than other industries that fall under medical records specialists, such as “office of physicians” or “nursing care facilities (skilled nursing facilities).” We calculated the cost of indirect costs, including fringe benefits, at 100 percent of the median hourly wage, consistent with previous years. This is necessarily a rough adjustment, both because fringe benefits and other indirect costs vary significantly by employer and methods of estimating these costs vary widely in the literature. Nonetheless, we believe that doubling the hourly wage rate ($26.06 × 2 = $52.12) to estimate total cost is a reasonably accurate estimation method. Accordingly, unless otherwise specified, we will calculate cost burden to IPFs using a wage plus benefits estimate of $52.12 per hour throughout the discussion in this section of this rule for the IPFQR Program.

Some of the activities previously finalized for the IPFQR Program require beneficiaries to undertake tasks such as responding to survey questions on their own time. In the FY 2024 IPF PPS final rule, we estimated the hourly wage rate for these activities to be $20.71/hr (88 FR 51145). We are updating that estimate to a post-tax wage of $24.04/hr. The Valuing Time in U.S. Department of Health and Human Services Regulatory Impact Analyses: Conceptual Framework and Best Practices identifies the approach for valuing time when individuals undertake activities on their own time.^[48] To derive the costs for beneficiaries, we used a measurement of the usual weekly earnings of wage and salary workers of $1,118, divided by 40 hours to calculate an hourly pre-tax wage rate of $27.95/hr.^[49] This rate is adjusted downwards by an estimate of the effective tax rate for median income households of about 14 percent calculated by comparing pre- and post-tax income,^[50] resulting in the post-tax hourly wage rate of $24.04/hr. Unlike our State and private sector wage adjustments, we are not adjusting beneficiary wages for fringe benefits and other indirect costs since the individuals' activities, if any, would occur outside the scope of their employment.

B. Previously Finalized IPFQR Estimates

We are finalizing provisions that impact policies beginning with the FY 2027 payment determination. For the purposes of calculating burden, we attribute the costs to the year in which the costs begin. Under our previously finalized policies, data submission for the measures that affect the FY 2027 payment determination occurs during CY 2026 and generally reflects care provided during CY 2025. If we finalize our proposal to switch to quarterly reporting in section XX.X of this proposed rule, data submission for the FY 2027 payment determination would begin during CY 2025. Our currently approved burden for CY 2025 is set forth in Table 25.

C. Updates Due to More Recent Information

In section VI.A of this proposed rule, we described our updated wage rates which increase from $44.86/hr to $52.12/hr (an increase of $7.26/hr) for activities performed by Medical Records Specialists and from $20.71/hr to $24.04/hr (an increase of $3.33/hr) for activities performed by individuals. The effects of these updates are set forth in Table 26.

D. Updates Due to Proposals in This Proposed Rule

In section V.B.2 of this proposed rule, we are proposing to adopt the 30-Day Risk-Standardized All-Cause ED Visit Following an IPF Discharge measure beginning with the CY 2025 performance period/FY 2027 payment determination. As described in section V.B.2.c. of this preamble, we will calculate the 30-Day Risk-Standardized All-Cause ED Visit Following an Inpatient Psychiatric Facility Discharge measure using Medicare claims that IPFs and other providers submit for payment. Since this is a claims-based measure there is no additional burden outside of submitting a claim. The claim submission is approved by OMB under control number 0938-0050 (CMS-2552-10). This rule does not warrant any changes under that control number.

In Section V.D. of this proposed rule, we are proposing to require IPFs to submit data on chart-abstracted measures quarterly. In CY 2025, this would equate to one additional data submission period (that is, the reporting period which would close on November 15, 2025 as set forth in Table 27). In CY 2026, there would be an additional two data submission periods (for a total of four annually). We estimate that the increase in burden associated with the increase in data submission periods is approximately equal to the burden of reporting one attestation measure because both of these activities require logging into and interacting with user interfaces within the CMS data reporting system (that is, the Hospital Quality System—HQS). The effects of this increase on the IPFQR Program for CY 2025 are set forth in Table 27. The effects of this increase on the IPFQR Program for CY 2026 are set forth in Table 28.

E. Consideration of Burden Related to Clarification of Eligibility Criteria for the Option To Elect To File an All-Inclusive Cost Report

As discussed in section III.E.4 of this proposed rule, we are clarifying the eligibility criteria to be approved to file all-inclusive cost reports. Only government-owned and tribally owned facilities are able to satisfy these criteria, and thus only these facilities will be permitted to file an all-inclusive cost report for cost reporting periods beginning on or after October 1, 2024.

We do not estimate any change in the burden associated with the hospital cost report (CMS-2552-10) OMB control number 0938-0050. We anticipate that IPFs which are currently filing all-inclusive cost reports, but are not government-owned or tribally owned, would not incur additional burden related to the submission of the cost report. The approved burden estimate associated with the submission of the hospital cost report includes the same amount of burden for the submission of an all-inclusive cost report as for the submission of a cost report with a charge structure.

We recognize that these IPFs would be required to track ancillary costs and charges using a charge structure; however, we expect that any burden associated with this tracking would be part of the normal course of a hospital's activities.

F. Submission of PRA-Related Comments

We have submitted a copy of this proposed rule's information collection requirements to OMB for their review. The requirements are not effective until they have been approved by OMB.

To obtain copies of the supporting statement and any related forms for the proposed collections discussed above, please visit the CMS website at https://www.cms.gov/​regulationsand-guidance/​legislation/​paperworkreductionactof1995/​pra-listing, or call the Reports Clearance Office at 410-786-1326.

We invite public comments on these potential information collection requirements. If you wish to comment, please submit your comments electronically as specified in the DATES and ADDRESSES sections of this proposed rule and identify the rule (CMS-1806-P), the ICR's CFR citation, and OMB control number.

VII. Response to Comments

Because of the large number of public comments we normally receive on Federal Register documents, we are not able to acknowledge or respond to them individually. We will consider all comments we receive by the date and time specified in the DATES section of this preamble, and, when we proceed with a subsequent document, we will respond to the comments in the preamble to that document.

VIII. Regulatory Impact Analysis

A. Statement of Need

This rule proposes updates to the prospective payment rates for Medicare inpatient hospital services provided by IPFs for discharges occurring during FY 2025 (October 1, 2024 through September 30, 2025). We are proposing to apply the 2021-based IPF market basket increase of 3.1 percent, reduced by the productivity adjustment of 0.4 percentage point as required by 1886(s)(2)(A)(i) of the Act for a proposed total FY 2025 payment rate update of 2.7 percent. In this proposed rule, we are proposing to update the outlier fixed dollar loss threshold amount, update the IPF labor-related share, adopt new CBSA delineations based on OMB Bulletin 23-01, and update the IPF wage index to reflect the FY 2025 hospital inpatient wage index. Section 1886(s)(4) of the Act requires IPFs to report data in accordance with the requirements of the IPFQR Program for purposes of measuring and making publicly available information on health care quality; and links the quality data submission to the annual applicable percentage increase.

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), Executive Order 14094 on Modernizing Regulatory Review (April 6, 2023), 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), and Executive Order 13132 on Federalism (August 4, 1999).

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, as amended by Executive Order 14094, defines a “significant regulatory action” as an action that is likely to result in a rule that may: (1) have an annual effect on the economy of $200 million or more (adjusted every 3 years by the Administrator of OIRA for changes in gross domestic product); or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, territorial, or tribal governments or communities; (2) create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; (3) materially alter the budgetary impacts of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or (4) raise legal or policy issues for which centralized review would meaningfully further the President's priorities or the principles set forth in Executive Order 12866. In accordance with the provisions of Executive Order 12866, this regulation was reviewed by the Office of Management and Budget.

A regulatory impact analysis (RIA) must be prepared for regulatory actions that are significant under section 3(f)(1) of Executive Order 12866. We estimate that the total impact of these changes for FY 2025 payments compared to FY 2024 payments will be a net increase of approximately $70 million. This reflects a $75 million increase from the update to the payment rates (+$85 million from the 4th quarter 2023 IGI forecast of the 2021-based IPF market basket of 3.1 percent, and -$10 million for the productivity adjustment of 0.4 percentage point), as well as a $5 million decrease as a result of the update to the outlier threshold amount. Outlier payments are estimated to change from 2.1 percent in FY 2024 to 2.0 percent of total estimated IPF payments in FY 2025.

Based on our estimates, OMB's Office of Information and Regulatory Affairs has determined that this rulemaking is “significant,” though not significant under section 3(f)(1) of Executive Order 12866. Nevertheless, because of the potentially substantial impact to IPF providers, we have prepared a Regulatory Impact Analysis that to the best of our ability presents the costs and benefits of the rulemaking. OMB has reviewed these proposed regulations, and the Departments have provided the following assessment of their impact.

Nevertheless, because of the potentially substantial impact to IPF providers, we have prepared a Regulatory Impact Analysis that to the best of our ability presents the costs and benefits of the rulemaking. Based on our estimates, OMB's Office of Information and Regulatory Affairs has determined that this rulemaking is “significant.” Therefore, OMB has reviewed these proposed regulations, and the Departments have provided the following assessment of their impact.

C. Detailed Economic Analysis

In this section, we discuss the historical background of the IPF PPS and the impact of this proposed rule on the Federal Medicare budget and on IPFs.

1. Budgetary Impact

As discussed in the RY 2005 and RY 2007 IPF PPS final rules, we applied a budget neutrality factor to the Federal per diem base rate and ECT payment per treatment to ensure that total estimated payments under the IPF PPS in the implementation period would equal the amount that would have been paid if the IPF PPS had not been implemented. This budget neutrality factor included the following components: outlier adjustment, stop-loss adjustment, and the behavioral offset. As discussed in the RY 2009 IPF PPS notice (73 FR 25711), the stop-loss adjustment is no longer applicable under the IPF PPS.

As discussed in section III.D.1.d of this proposed rule, we are proposing to update the wage index and labor-related share, as well as update the CBSA delineations based on OMB Bulletin 23-01, in a budget neutral manner by applying a wage index budget neutrality factor to the Federal per diem base rate and ECT payment per treatment. In addition, as discussed in section III.F of this proposed rule, we are proposing to apply a refinement standardization factor to the Federal per diem base rate and ECT payment per treatment to account for the proposed revisions to the ECT per treatment amount, ED adjustment, and patient-level adjustment factors (as previously discussed in sections III.B, III.C, and III.D of this proposed rule, and summarized in Addendum A), which must be made budget-neutrally. Therefore, the budgetary impact to the Medicare program of this proposed rule would be due to the proposed market basket update for FY 2025 of 3.1 percent (see section III.A.2 of this proposed rule) reduced by the productivity adjustment of 0.4 percentage point required by section 1886(s)(2)(A)(i) of the Act and the update to the outlier fixed dollar loss threshold amount.

We estimate that the FY 2025 impact would be a net increase of $70 million in payments to IPF providers. This reflects an estimated $75 million increase from the update to the payment rates and a $5 million decrease due to the update to the outlier threshold amount to set total estimated outlier payments at 2.0 percent of total estimated payments in FY 2025. This estimate does not include the implementation of the required 2.0 percentage point reduction of the productivity-adjusted market basket update factor for any IPF that fails to meet the IPF quality reporting requirements (as discussed in section III.B.2. of this proposed rule).

2. Impact on Providers

To show the impact on providers of the changes to the IPF PPS discussed in this proposed rule, we compare estimated payments under the proposed IPF PPS rates and factors for FY 2025 versus those under FY 2024. We determined the percent change in the estimated FY 2025 IPF PPS payments compared to the estimated FY 2024 IPF PPS payments for each category of IPFs. In addition, for each category of IPFs, we have included the estimated percent change in payments resulting from the proposed update to the outlier fixed dollar loss threshold amount; the proposed revisions to the patient-level adjustment factors, ED adjustment, and ECT per treatment amount; the updated wage index data including the proposed labor-related share and the proposed changes to the CBSA delineations; and the proposed market basket increase for FY 2025, as reduced by the proposed productivity adjustment according to section 1886(s)(2)(A)(i) of the Act.

To illustrate the impacts of the proposed FY 2025 changes in this proposed rule, our analysis begins with FY 2023 IPF PPS claims (based on the 2023 MedPAR claims, December 2023 update). We estimate FY 2024 IPF PPS payments using these 2023 claims, the finalized FY 2024 IPF PPS Federal per diem base rate and ECT per treatment amount, and the finalized FY 2024 IPF PPS patient and facility level adjustment factors (as published in the FY 2024 IPF PPS final rule (88 FR 51054)). We then estimate the FY 2024 outlier payments based on these simulated FY 2024 IPF PPS payments using the same methodology as finalized in the FY 2024 IPF PPS final rule (88 FR 51090 through 51092) where total outlier payments are maintained at 2 percent of total estimated FY 2024 IPF PPS payments.

Each of the following changes is added incrementally to this baseline model in order for us to isolate the effects of each change:

• The proposed update to the outlier fixed dollar loss threshold amount.
• The proposed revisions to patient-level adjustment factors, ED adjustment, and the ECT per treatment amount.
• The proposed FY 2025 IPF wage index, the proposed changes to the CBSA delineations, and the proposed FY 2025 labor-related share (LRS).
• The proposed market basket increase for FY 2025 of 3.1 percent reduced by the proposed productivity adjustment of 0.4 percentage point in accordance with section 1886(s)(2)(A)(i) of the Act for a payment rate update of 2.7 percent.

Our proposed column comparison in Table 29 illustrates the percent change in payments from FY 2024 (that is, October 1, 2023, to September 30, 2024) to FY 2025 (that is, October 1, 2024, to September 30, 2025) including all the proposed payment policy changes.

3. Impact Results

Table 30 displays the results of our analysis. The table groups IPFs into the categories listed here based on characteristics provided in the Provider of Services file, the IPF PSF, and cost report data from the Healthcare Cost Report Information System:

• Facility Type.
• Location.
• Teaching Status Adjustment.
• Census Region.
• Size.

The top row of the table shows the overall impact on the 1,430 IPFs included in the analysis. In column 2, we present the number of facilities of each type that had information available in the PSF, had claims in the MedPAR dataset for FY 2023. We note that providers are assigned urban or rural status in Table 30 based on the current CBSA delineations for FY 2024.

In column 3, we present the effects of the update to the outlier fixed dollar loss threshold amount. We estimate that IPF outlier payments as a percentage of total IPF payments are 2.1 percent in FY 2024. Therefore, we are proposing to adjust the outlier threshold amount to set total estimated outlier payments equal to 2.0 percent of total payments in FY 2025. The estimated change in total IPF payments for FY 2025, therefore, includes an approximate 0.1 percent decrease in payments because we would expect the outlier portion of total payments to decrease from approximately 2.1 percent to 2.0 percent.

The overall impact of the estimated decrease to payments due to updating the outlier fixed dollar loss threshold (as shown in column 3 of Table 30), across all hospital groups, is a 0.1 percent decrease. The largest decrease in payments due to this change is estimated to be 0.2 percent for urban government IPF units, IPFs with more than 30 percent interns and residents to beds, and IPF units with 76+ beds.

In column 4, we present the effects of the proposed revisions to the patient-level adjustment factors, ED adjustment, and ECT per treatment amount and the application of the refinement standardization factor that is discussed in section III.F of this proposed rule. We estimate the largest payment increases would be for rural freestanding government-owned IPFs. Conversely, we estimate that for-profit IPF hospitals in rural areas would experience the largest payment decrease. Payments to IPF units in urban areas would increase by 0.4 percent, and payments to IPF units in rural areas would increase by 0.3 percent.

In column 5, we present the effects of the proposed budget-neutral update to the IPF wage index, the proposed LRS, and the proposed changes to the CBSA delineations for FY 2025. In addition, this column includes the application of the 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year as finalized in the FY 2023 IPF PPS final rule (87 FR 46856 through 46859). The change in this column represents the effect of using the concurrent hospital wage data as discussed in section III.D.1.a of this proposed rule. That is, the impact represented in this column reflects the proposed update from the FY 2024 IPF wage index to the proposed FY 2025 IPF wage index, which includes basing the FY 2025 IPF wage index on the FY 2025 pre-floor, pre-reclassified IPPS hospital wage index data, applying a 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, and updating the LRS from 78.7 percent in FY 2024 to 78.8 percent in FY 2025. We note that there is no projected change in aggregate payments to IPFs, as indicated in the first row of column 5; however, there would be distributional effects among different categories of IPFs. For example, we estimate the largest increase in payments to be 2.9 percent for freestanding rural for-profit IPFs, and the largest decrease in payments to be 1.6 percent for IPFs located in the Pacific region.

Overall, IPFs are estimated to experience a net increase in payments of 2.6 percent as a result of the updates in this proposed rule. IPF payments are therefore estimated to increase by 2.4 percent in urban areas and 4.0 percent in rural areas. The largest payment increase is estimated at 5.0 percent for IPFs located in the East South Central region.

4. Effect on Beneficiaries

Under the FY 2025 IPF PPS, IPFs will continue to receive payment based on the average resources consumed by patients for each day. Our longstanding payment methodology reflects the differences in patient resource use and costs among IPFs, as required under section 124 of the BBRA. We expect that updating IPF PPS rates in this rule will improve or maintain beneficiary access to high quality care by ensuring that payment rates reflect the best available data on the resources involved in inpatient psychiatric care and the costs of these resources. We continue to expect that paying prospectively for IPF services under the FY 2025 IPF PPS will enhance the efficiency of the Medicare program.

As discussed in sections V.B.2 of this proposed rule, we expect that the proposed additional IPFQR Program measure will support improving discharge planning and care coordination to decrease the likelihood that a patient will need to seek emergency care within 30 days of discharge from an IPF.

5. Effects of the Updates to the IPFQR Program

In section V.B.2. of this rule, we are proposing the 30-Day Risk-Standardized All-Cause ED Visit Following an Inpatient Psychiatric Facility Discharge measure beginning with data from the CY 2025 performance period for the FY 2027 payment determination. We do not believe this update would impact providers' workflows or information systems to collect or report the data because this measure is calculated by CMS using information that IPFs already submit as part of the claims process. There may be some effects of this measure on IPF workflows and clinical processes to improve care coordination and discharge planning to improve performance on the measure.

We are also proposing to adopt a quarterly data submission requirement for measures for which we require patient-level data. We believe there may be some non-recurrent costs associated with training staff and updating processes to submit these data more frequently. We believe that the recurring costs of these updates will be an increase of 800 hours across all IPFs, equating to change of $41,696.

In accordance with section 1886(s)(4)(A) of the Act, we will apply a 2-percentage point reduction to the FY 2025 market basket update for IPFs that have failed to comply with the IPFQR Program requirements for FY 2025, including reporting on the mandatory measures. For the FY 2024 payment determination, of the 1,568 IPFs eligible for the IPFQR Program, 194 IPFs did not receive the full market basket update because of the IPFQR Program; 42 of these IPFs chose not to participate and 152 did not meet the requirements of the program.

We intend to closely monitor the effects of the IPFQR Program on IPFs and help facilitate successful reporting outcomes through ongoing education, national trainings, and a technical help desk.

6. Regulatory Review Costs

If regulations impose administrative costs on private entities, such as the time needed to read and interpret this proposed rule, we should estimate the cost associated with regulatory review. Due to the uncertainty involved with accurately quantifying the number of entities that will be directly impacted and will review this proposed rule, we assume that the total number of unique commenters on the most recent IPF proposed rule will be the number of reviewers of this proposed rule. For this FY 2025 IPF PPS proposed rule, the most recent IPF proposed rule was the FY 2024 IPF PPS proposed rule, and we received 2,506 unique comments on this proposed rule. We acknowledge that this assumption may understate or overstate the costs of reviewing this proposed rule. It is possible that not all commenters reviewed the FY 2024 IPF proposed rule in detail, and it is also possible that some reviewers chose not to comment on that proposed rule. For these reasons, we thought that the number of commenters would be a fair estimate of the number of reviewers who are directly impacted by this proposed rule. We are soliciting comments on this assumption.

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

Using the May, 2022 mean (average) wage information from the BLS for medical and health service managers (Code 11-9111), we estimate that the cost of reviewing this proposed rule is $123.06 per hour, including other indirect costs https://www.bls.gov/​oes/​current/​oes119111.htm. Assuming an average reading speed of 250 words per minute, we estimate that it would take approximately 112 minutes (1.87 hours) for the staff to review half of this proposed rule, which contains a total of approximately 56,000 words. For each IPF that reviews the proposed rule, the estimated cost is (1.87 × $123.06) or $230.12. Therefore, we estimate that the total cost of reviewing this proposed rule is $576,680.72 ($230.12 × 2,506 reviewers).

D. Alternatives Considered

The statute gives the Secretary discretion in establishing an update methodology to the IPF PPS. We continue to believe it is appropriate to routinely update the IPF PPS so that it reflects the best available data about differences in patient resource use and costs among IPFs, as required by the statute. Therefore, we are proposing to: update the IPF PPS using the methodology published in the RY 2005 IPF PPS final rule (our “standard methodology”) pre-floor, pre-reclassified IPPS hospital wage index as its basis, along with the proposed changes to the CBSA delineations. Additionally, we apply a 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year. Lastly, we are proposing to revise the patient-level adjustment factors, ED adjustment, and to increase the ECT per treatment amount for FY 2025 (reflecting the pre-scaled and pre-adjusted CY 2024 OPPS geometric mean cost).

E. Accounting Statement

As required by OMB Circular A-4 (available at www.whitehouse.gov/​sites/​whitehouse.gov/​files/​omb/​circulars/​A4/​a-4.pdf), in Table 30, we have prepared an accounting statement showing the classification of the expenditures associated with the updates to the IPF wage index and payment rates in this proposed rule. Table 30 provides our best estimate of the increase in Medicare payments under the IPF PPS as a result of the changes presented in this proposed rule and based on the data for 1,430 IPFs with data available in the PSF, with claims in our FY 2023 MedPAR claims dataset. Lastly, Table 30 also includes our best estimate of the costs of reviewing and understanding this proposed rule.

F. Regulatory Flexibility Act

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. The great majority of hospitals and most other health care providers and suppliers are small entities, either by being nonprofit organizations or by meeting the Small Business Administration (SBA) definition of a small business (having revenues of less than $47 million in any 1 year).

According to the SBA's website at http://www.sba.gov/​content/​small-business-size-standards, IPFs falls into the North American Industrial Classification System (NAICS) code 622210, Psychiatric and Substance Abuse hospitals. The SBA defines small Psychiatric and Substance Abuse hospitals as businesses having less than $47 million.

Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IPFs or the proportion of IPFs' revenue derived from Medicare payments. Therefore, we assume that all IPFs are considered small entities.

The Department of Health and Human Services generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA. As shown in Table 30, we estimate that the overall revenue impact of this proposed rule on all IPFs is to increase estimated Medicare payments by approximately 2.6 percent. As a result, since the estimated impact of this proposed rule is a net increase in revenue across almost all categories of IPFs, the Secretary has determined that this proposed rule will have a positive revenue impact on a substantial number of small entities.

In addition, section 1102(b) of the Act requires us to prepare a regulatory impact analysis 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 603 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 discussed in section VIII.C.2 of this proposed rule, the rates and policies set forth in this proposed rule will not have an adverse impact on the rural hospitals based on the data of the 199 rural excluded psychiatric units and 60 rural psychiatric hospitals in our database of 1,430 IPFs for which data were available. Therefore, the Secretary has determined that this proposed rule will not have a significant impact on the operations of a substantial number of small rural hospitals.

G. Unfunded Mandate Reform Act (UMRA)

Section 202 of the Unfunded Mandates Reform Act of 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 2023, that threshold is approximately $183 million. This proposed rule does not mandate any requirements for state, local, or tribal governments, or for the private sector. This proposed rule would not impose a mandate that will result in the expenditure by state, local, and tribal governments, in the aggregate, or by the private sector, of more than $183 million in any 1 year.

H. Federalism

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a proposed rule that imposes substantial direct requirement costs on state and local governments, preempts state law, or otherwise has Federalism implications. This proposed rule does not impose substantial direct costs on state or local governments or preempt state law.

In accordance with the provisions of Executive Order 12866, this proposed regulation was reviewed by the Office of Management and Budget.

Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & Medicaid Services, approved this document on March 22, 2024.

Xavier Becerra,

Secretary, Department of Health and Human Services.

Footnotes

1.   https://www.reginfo.gov/​public/​do/​PRAViewICR?​ref_​nbr=​202206-0938-017.

2.   https://www.cms.gov/​files/​document/​technical-report-medicare-program-inpatient-psychiatric-facilities-prospective-payment-system.pdf.

3.  IPFs are subject to all hospital conditions of participation, including 42 CFR 482.25, which specifies that “The hospital must have pharmaceutical services that meet the needs of the patients,” and 482.27, which specifies that “The hospital must maintain, or have available, adequate laboratory services to meet the needs of its patients.”

4.  IPFs are subject to all hospital conditions of participation, including 42 CFR 482.25, which specifies that “The hospital must have pharmaceutical services that meet the needs of the patients,” and 482.27, which specifies that “The hospital must maintain, or have available, adequate laboratory services to meet the needs of its patients.”

5.  PRM 15-1, chapter 22, § 2208.1.

6.   https://www.whitehouse.gov/​briefing-room/​presidential-actions/​2021/​07/​09/​executive-order-on-promoting-competition-in-the-american-economy/​.

7.  Medicare Payment Advisory Commission. (2023). Report to the Congress: Medicare Payment Policy. Available at: https://www.medpac.gov/​wp-content/​uploads/​2023/​03/​Ch3_​Mar23_​MedPAC_​Report_​To_​Congress_​SEC_​v2.pdf. Accessed on January 22, 2024.

8.  Medicare Payment Advisory Commission. (2023). Report to the Congress: Medicare Payment Policy. Available at: https://www.medpac.gov/​wp-content/​uploads/​2023/​03/​Ch3_​Mar23_​MedPAC_​Report_​To_​Congress_​SEC_​v2.pdf. Accessed on January 22, 2024.

9.  For more information on our strategic goals to improve health equity by expanding the collection, reporting, and analysis of standardized data, we refer readers to Priority 1 of our Framework for Health Equity at https://www.cms.gov/​priorities/​health-equity/​minority-health/​equity-programs/​framework.

10.  We refer readers to the Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities; Updates to the Quality Reporting Program and Value-Based Purchasing Program for Federal fiscal year 2020 final rule (84 FR 38767); the Medicare Program; Inpatient Rehabilitation Facility (IRF) Prospective Payment System for Federal fiscal year 2020 and Updates to the IRF Quality Reporting Program final rule (84 FR 39110), the Medicare and Medicaid Programs; CY 2020 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; Home Health Quality Reporting Requirements; and Home Infusion Therapy Requirements CY 2020 final rule (84 FR 60567), and the Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Policy Changes and fiscal year 2020 Rates; Quality Reporting Requirements for Specific Providers; Medicare and Medicaid Promoting Interoperability Programs Requirements for Eligible Hospitals and Critical Access Hospitals final rule (84 FR 42537).

11.  For more information on other PAIs, we refer readers to https://www.cms.gov/​medicare/​payment/​prospective-payment-systems/​inpatient-rehabilitation/​pai (for the IRF-PAI), to https://www.cms.gov/​medicare/​quality/​home-health/​oasis-data-sets (for the OASIS data set for HHAs), to https://www.cms.gov/​medicare/​quality/​long-term-care-hospital/​ltch-care-data-set-ltch-qrp-manual (for the CARE data set for LTCHs), and to https://www.cms.gov/​medicare/​quality/​nursing-home-improvement/​resident-assessment-instrument-manual (for the Minimum Data Set (MDS) Resident Assessment Instrument (RAI)).

12.   https://mmshub.cms.gov/​blueprint-measure-lifecycle-overview.

13.   https://www.cms.gov/​files/​document/​irf-pai-version-42-effective-10-01-24.pdf.

14.  The CMS Strategic Plan. Available at https://www.cms.gov/​about-cms/​what-we-do/​cms-strategic-plan. Accessed February 20, 2024.

15.  For further information detailing the rationale for adopting SDOH Standardized Patient Assessment Data Elements in these settings, we refer readers to the Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities; Updates to the Quality Reporting Program and Value-Based Purchasing Program for Federal fiscal year 2020 final rule (84 FR 38805 through 38817); the Medicare Program; Inpatient Rehabilitation Facility (IRF) Prospective Payment System for Federal fiscal year 2020 and Updates to the IRF Quality Reporting Program final rule (84 FR 39149 through 38161), the Medicare and Medicaid Programs; CY 2020 Home Health Prospective Payment System Rate Update; Home Health Value-Based Purchasing Model; Home Health Quality Reporting Requirements; and Home Infusion Therapy Requirements CY 2020 final rule (84 FR 60597 through 60608), and the Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Policy Changes and fiscal year 2020 Rates; Quality Reporting Requirements for Specific Providers; Medicare and Medicaid Promoting Interoperability Programs Requirements for Eligible Hospitals and Critical Access Hospitals final rule (84 FR 42577 through 42588).

16.  We note that the statute uses the term “rate year” (RY). However, beginning with the annual update of the inpatient psychiatric facility prospective payment system (IPF PPS) that took effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with the annual update of the ICD codes, effective on October 1 of each year. This change allowed for annual payment updates and the ICD coding update to occur on the same schedule and appear in the same Federal Register document, promoting administrative efficiency. To reflect the change to the annual payment rate update cycle, we revised the regulations at 42 CFR 412.402 to specify that, beginning October 1, 2012, the IPF PPS RY means the 12-month period from October 1 through September 30, which we refer to as a “fiscal year” (FY) (76 FR 26435). Therefore, with respect to the IPFQR Program, the terms “rate year,” as used in the statute, and “fiscal year” as used in the regulation, both refer to the period from October 1 through September 30. For more information regarding this terminology change, we refer readers to section III of the RY 2012 IPF PPS final rule (76 FR 26434 through 26435).

17.  Schreiber, M, Richards, A, et al. (2022). The CMS National Quality Strategy: A Person-Centered Approach to Improving Quality. Available at: https://www.cms.gov/​blog/​cms-national-quality-strategy-person-centered-approach-improving-quality.

18.  CMS. (2022). CMS Behavioral Health Strategy. Available at https://www.cms.gov/​cms-behavioral-health-strategy.

19.  CMS. (2022). CMS Framework for Health Equity 2022-2032. Available at https://www.cms.gov/​files/​document/​cms-framework-health-equity-2022.pdf.

20.  CMS. (2023). Meaningful Measures 2.0: Moving from Measure Reduction to Modernization. Available at https://www.cms.gov/​medicare/​quality/​meaningful-measures-initiative/​meaningful-measures-20. Accessed on March 20, 2024.

21.  Nelson, E.A. Maruish, M.E., Axler, J.L. Effects of Discharge Planning with Outpatient Appointments on Readmission Rates. https://ps.psychiatryonline.org/​doi/​10.1176/​appi.ps.51.7.885.

22.  Steffen S, Kösters M, Becker T, Puschner B. Discharge planning in mental health care: a systematic review of the recent literature. Acta Psychiatr Scand. 2009 Jul;120(1):1-9. doi: 10.1111/j.1600-0447.2009.01373.x. Epub 2009 Apr 8. PMID: 19486329.

23.  Haselden, M., Corbeil, T., Tang, F., Olfson, M., Dixon, L.B., Essock, S.M., Wall, M.M., Radigan, M., Frimpong, E., Wang, R., Lamberti, S., Schneider, M., & Smith, T.E. (2019). Family Involvement in Psychiatric Hospitalizations: Associations With Discharge Planning and Prompt Follow-Up Care. Psychiatric Services, 70(10), 860-866. https://doi.org/​10.1176/​appi.ps.201900028.

24.  Pincus, Harold, Care Transition Interventions to Reduce Psychiatric Re-Hospitalizations. National Association of State Mental Health Program Directors. 2015. Available at https://nasmhpd.org/​sites/​default/​files/​Assessment%20%233_​Care%20Transitions%20Interventions%20toReduce%20Psychiatric%20Rehospitalization.pdf. Accessed on January 23, 2024.

25.  Allen, E.M., Call, K.T., Beebe, T.J., McAlpine, D.D., & Johnson, P.J. (2017). Barriers to Care and Healthcare Utilization among the Publicly Insured. Medical Care, 55(3), 207-214. doi:10.1097/MLR.0000000000000644.

26.  Mutschler, C., Lichtenstein, S., Kidd, S.A., & Davidson, L. (2019). Transition experiences following psychiatric hospitalization: A systematic review of the literature. Community Mental Health Journal, 55(8), 1255-1274. doi:10.1007/s10597-019-00413-9.

27.  Allen, E.M., Call, K.T., Beebe, T.J., McAlpine, D.D., & Johnson, P.J. (2017). Barriers to Care and Healthcare Utilization among the Publicly Insured. Medical Care, 55(3), 207-214. doi:10.1097/MLR.0000000000000644.

28.  Mutschler, C., Lichtenstein, S., Kidd, S.A., & Davidson, L. (2019). Transition experiences following psychiatric hospitalization: A systematic review of the literature. Community Mental Health Journal, 55(8), 1255-1274. doi:10.1007/s10597-019-00413-9.

29.  Donisi V, Tedeschi F, Wahlbeck K, Haaramo P, Amaddeo F. Pre-discharge factors predicting readmissions of psychiatric patients: a systematic review of the literature. BMC Psychiatry. 2016 Dec 16;16(1):449. doi: 10.1186/s12888-016-1114-0. PMID: 27986079; PMCID: PMC5162092.

30.  Morgan C Shields, Mara A G Hollander, Alisa B Busch, Zohra Kantawala, Meredith B Rosenthal, Patient-centered inpatient psychiatry is associated with outcomes, ownership, and national quality measures, Health Affairs Scholar, Volume 1, Issue 1, July 2023, qxad017, https://doi.org/​10.1093/​haschl/​qxad017.

31.   https://p4qm.org/​measures/​2860.

32.  As depicted in the April 2023 file available at https://data.cms.gov/​provider-data/​archived-data/​hospitals.

33.  See for instance Chung, D.T., Ryan, C.J., Hadzi-Pavlovic, D., Singh, S.P., Stanton, C., & Large, M.M. (2017). Suicide rates after discharge from psychiatric facilities: A systematic review and meta-analysis. JAMA Psychiatry, 74(7), 694-702. https://doi.org/​10.1001/​jamapsychiatry.2017.1044 or Durbin, J., Lin, E., Layne, C., et al. (2007). Is readmission a valid indicator of the quality of inpatient psychiatric care? Journal of Behavioral Health Services Research, 34, 137-150. doi:10.1007/s11414- 007-9055-5.

34.   https://www.cms.gov/​medicare/​quality/​meaningful-measures-initiative/​meaningful-measures-20.

35.  Schreiber, M, Richards, A, et al. (2022). The CMS National Quality Strategy: A Person-Centered Approach to Improving Quality. Available at: https://www.cms.gov/​blog/​cms-national-quality-strategy-person-centered-approach-improving-quality.

36.  CMS. (2022). CMS Behavioral Health Strategy. Available at https://www.cms.gov/​cms-behavioral-health-strategy.

37.   https://mmshub.cms.gov/​blueprint-measure-lifecycle-overview.

38.  For an example of the hierarchal logistic risk-adjustment algorithm, we refer readers to the algorithm for the IPF Unplanned Readmission measure at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​hospitalqualityinits/​downloads/​inpatient-psychiatric-facility-readmission-measure.zip.

39.  These materials are available at the PRMR section of the PQM website: https://p4qm.org/​PRMR.

40.   https://p4qm.org/​sites/​default/​files/​2023-09/​Guidebook-of-Policies-and-Procedures-for-Pre-Rulemaking-Measure-Review-%28PRMR%29-and-Measure-Set-Review-%28MSR%29-Final_​0.pdf.

41.  The Partnership for Quality Measurement. (October 2023). Endorsement and Maintenance (E&M) Guidebook. Available at: https://p4qm.org/​sites/​default/​files/​2023-12/​Del-3-6-Endorsement-and-Maintenance-Guidebook-Final_​_​0.pdf.

44.  We note that the PRMR Hospital Recommendation Group was previously the Measure Applications Partnership (MAP) Hospital Workgroup under the pre-rulemaking process followed by the previous CBE.

45.   https://p4qm.org/​EM.

46.  For information about the Cost and Efficiency endorsement review we refer readers to the meeting summary, available at https://p4qm.org/​sites/​default/​files/​Cost%20and%20Efficiency/​material/​EM-Cost-and-Efficiency-Fall2023-Endorsement-Meeting-Summary.pdf.

47.  Medical Records Specialists ( bls.gov).

48.   https://aspe.hhs.gov/​reports/​valuing-time-us-department-health-human-services-regulatory-impact-analyses-conceptual-framework.

49.   https://www.bls.gov/​news.release/​pdf/​wkyeng.pdf. Accessed January 1, 2024.

50.   https://www.census.gov/​library/​stories/​2023/​09/​median-household-income.html. Accessed January 2, 2024.