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 Department of Health and Human Services Centers for Medicare & Medicaid Services 42 CFR Part 412
[CMS-1769-P]
RIN 0938-AU80
 AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
 ACTION: Proposed rule.
 SUMMARY: 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 (IPF), which include psychiatric hospitals and excluded psychiatric units of an acute care hospital or critical access hospital. This proposed rule would also establish a permanent mitigation policy to smooth the impact of year-to-year changes in IPF payments related to decreases in the IPF wage index. In addition, this proposed rule includes a request for comment on the results of the data analysis of the IPF Prospective Payment System adjustments. The proposed changes in this rule would be effective for IPF discharges occurring during the Fiscal Year (FY) beginning October 1, 2022 through September 30, 2023 (FY 2023). Lastly, this proposed rule requests information on Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs.
 DATES: To be assured consideration, comments must be received at one of the addresses provided below by May 31, 2022.
 ADDRESSES: In commenting, please refer to file code CMS-1769-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-1769-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-1769-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: The IPF Payment Policy mailbox at 
                        *IPFPaymentPolicy@cms.hhs.gov*
                         for general information. Mollie Knight (410) 786-7948 or Eric Laib (410) 786-9759, for information regarding the market basket update or the labor-related share. Nick Brock (410) 786-5148 or Theresa Bean (410) 786-2287, for information regarding the regulatory impact analysis. Lauren Lowenstein, (410) 786-4507, for information regarding the inpatient psychiatric facilities quality reporting program.


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 individual will take actions to harm the 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. Availability of Certain Tables Exclusively Through the Internet on the CMS Website Addendum A to this proposed rule summarizes the FY 2023 IPF PPS payment rates, outlier threshold, cost of living adjustment factors (COLA) for Alaska and Hawaii, national and upper limit cost-to-charge ratios, and adjustment factors. In addition, the B Addenda to this proposed rule shows 
                    ( print page 19416)
                    the complete listing of ICD-10 Clinical Modification (CM) and Procedure Coding System (PCS) codes, the FY 2023 IPF PPS comorbidity adjustment, and electroconvulsive therapy (ECT) procedure codes. The A and B Addenda are available online at: 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.* Tables setting forth the FY 2023 Wage Index for Urban Areas Based on Core-Based Statistical Area (CBSA) Labor Market Areas and the FY 2023 Wage Index Based on CBSA Labor Market Areas for Rural 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) 2023 beginning October 1, 2022 through September 30, 2023. This proposed rule would also establish a permanent mitigation policy to smooth the impact of year-to-year changes in IPF payments related to changes in the IPF wage index. In addition, this proposed rule includes a request for comment on the results of the data analysis of the IPF Prospective Payment System (PPS) adjustments. Lastly, this proposed rule requests information on Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs. B. Summary of the Major Provisions 1. Inpatient Psychiatric Facilities Prospective Payment System For the IPF PPS, we are proposing to— Establish a permanent mitigation policy in order to smooth the impact of year-to-year changes in IPF payments related to decreases to the IPF wage index.
                Solicit comments on the results of the data analysis of the IPF PPS adjustments, which have been summarized in a technical report posted to the Centers for Medicare & Medicaid Services (CMS) website at*https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS*.
                Update the IPF PPS base rate by the 2016-based IPF market basket update (3.1 percent) adjusted for economy-wide productivity (0.4 percentage point) as required by section 1886(s)(2)(A)(i) of the Social Security Act (the Act), resulting in a proposed IPF payment rate update of 2.7 percent for FY 2023.
                Make technical rate setting updates: The IPF PPS payment rates would be 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 $832.94 to $856.80. ++ The IPF PPS Federal per diem base rate for providers who failed to report quality data to $840.11. ++ The ECT payment per treatment from $358.60 to $368.87. ++ The ECT payment per treatment for providers who failed to report quality data to $361.69. ++ The labor-related share from 77.2 percent to 77.4 percent. ++ The wage index budget-neutrality factor to 1.0016. ++ The fixed dollar loss threshold amount from $16,040 to $24,270 to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF PPS payments. 2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program We are not proposing any changes to the IPFQR Program. However, we are including a request for information (RFI) on the Overarching Principles for Measuring Healthcare Quality Disparities Across CMS Quality Programs. Feedback provided will inform future efforts in all CMS Quality programs and, as applicable, may be introduced in the IPFQR as future RFIs or proposals. C. Summary of Impacts Provision description
Total transfers & cost reductionsFY 2023 IPF PPS payment update
The overall economic impact of this proposed rule is an estimated $50 million in increased payments to IPFs during FY 2023.
 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 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 IPF PPS 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; this was the final year 
                    ( print page 19417)
                    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) 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 Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program is available in the FY 2020 IPF PPS and Quality Reporting Updates for FY Beginning October 1, 2019 final rule (84 FR 38459 through 38468). To implement and periodically update these provisions, we have published various proposed and final rules and notices in the 
                    **Federal Register**
                    . For more information regarding these documents, see 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 IPF PPS final rule in the 
                    **Federal Register**
                     (69 FR 66922). The November 2004 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 November 2004 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 November 2004 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 electroconvulsive therapy (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 November 2004 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 November 2004 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 November 28, 2003 IPF proposed rule (68 FR 66923; 66928 through 66933) and our November 15, 2004 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 November 2004 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. The most recent IPF PPS annual update was published in a final rule on August 4, 2021 in the 
                    **Federal Register**
                     titled, “Medicare Program; FY 2022 Inpatient Psychiatric Facilities Prospective Payment System and Quality Reporting Updates for Fiscal Year Beginning October 1, 2021 (FY 2022)” (86 FR 42608), which updated the IPF PPS payment rates for FY 2022. That final rule updated the IPF PPS Federal per diem base rates that were 
                    ( print page 19418)
                    published in the FY 2021 IPF PPS Rate Update final rule (85 FR 47042) in accordance with our established policies. III. Provisions of the FY 2023 IPF PPS Proposed Rule A. Proposed FY 2023 Market Basket Update and Productivity Adjustment for the IPF PPS 1. Background Originally, the input price index that was 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 2020 IPF PPS rule, where we adopted a 2016-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 2020 IPF PPS final rule for a detailed discussion of the 2016-based IPF PPS market basket and its development (84 FR 38426 through 38447). 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 2023 IPF Market Basket Update For FY 2023 (beginning October 1, 2022 and ending September 30, 2023), 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 2021 forecast with historical data through the third quarter of 2021, the 2016-based IPF market basket increase factor for FY 2023 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 total factor productivity. 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/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.*
                     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 FY 2023 IPF PPS proposed rule, based on IGI's fourth quarter 2021 forecast, the proposed productivity adjustment for FY 2023 (the 10-year moving average of TFP for the period ending FY 2023) is projected to be 0.4 percent. Accordingly, we are proposing to reduce the 3.1 percent IPF market basket update by this 0.4 percentage point productivity adjustment, as mandated by the Act. This results in a proposed FY 2023 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 2023 IPF market basket update and productivity adjustment for the final rule. 3. Proposed FY 2023 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 2016-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 2016-based IPF market basket. For more details regarding the methodology for determining specific cost categories for inclusion in the 2016-based IPF labor-related share, see the FY 2020 IPF PPS final rule (84 FR 38445 through 38447). The relative importance reflects the different rates of price change for these cost categories between the base year (FY 2016) and FY 2023. Based on IGI's fourth quarter 2021 forecast of the 2016-based IPF market basket, the sum of the FY 2023 relative importance moving average of Wages and Salaries; Employee Benefits; Professional Fees: 
                    ( print page 19419)
                    Labor-related; Administrative and Facilities Support Services; Installation, Maintenance, and Repair Services; All Other: Labor-related Services is 74.4 percent. We also propose, 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 are 6.6 percent of the 2016-based IPF market basket for FY 2023, we propose to take 46 percent of 6.6 percent to determine a labor-related share of Capital-Related costs for FY 2023 of 3.0 percent. Therefore, we propose a total labor-related share for FY 2023 of 77.4 percent (the sum of 74.4 percent for the labor-related share of operating costs and 3.0 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 2023 labor-related share for the final rule. For more information on the labor-related share and its calculation, we refer readers to the FY 2020 IPF PPS final rule (84 FR 38445 through 38447). Table 1 shows the proposed FY 2023 labor-related share and the final FY 2022 labor-related share using the 2016-based IPF market basket relative importance. Table 1—FY 2023 Proposed IPF Labor-Related Share and FY 2022 IPF Labor-Related Share
Relative importance, 
                             
                                proposed labor-related share FY 2023 1
Relative importance, labor-related 
                             share  
                             
                                FY 2022 2Wages and Salaries
53.3
52.8Employee Benefits
13.4
13.6Professional Fees: Labor-related
4.3
4.3Administrative and Facilities Support Services
0.6
0.6Installation, Maintenance and Repair
1.3
1.3All Other Labor-related
                             Services
1.5
1.5Subtotal
74.4
74.1Labor-related portion of Capital-Related (.46)
3.0
3.1Total Labor-Related Share
77.4
77.21
                         Based on the 4th quarter 2021 IHS Global Inc. forecast of the 2016-based IPF market basket.2
                         Based on the 2nd quarter 2021 IHS Global Inc. forecast of the 2016-based IPF market basket.
 We invite public comments on the proposed labor-related share for FY 2023. B. Proposed Updates to the IPF PPS Rates for FY Beginning October 1, 2022 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 November 2004 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 November 2004 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 November 2004 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 November 2004 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 § 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 electroconvulsive therapy (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.* IPFs must include a valid procedure code for ECT services provided to IPF beneficiaries in order to bill for ECT 
                    ( print page 19420)
                    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 as a result of the final update to the ICD-10-PCS code set for FY 2023. Addendum B to this proposed rule shows the ECT procedure codes for FY 2023 and is available on our website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.* 2. Proposed Update of the Federal per Diem Base Rate and Electroconvulsive Therapy Payment per Treatment The current (FY 2022) Federal per diem base rate is $832.94 and the ECT payment per treatment is $358.60. For the proposed FY 2023 Federal per diem base rate, we applied the payment rate update of 2.7 percent—that is, the proposed 2016-based IPF market basket increase for FY 2023 of 3.1 percent less the proposed productivity adjustment of 0.4 percentage point—and the proposed wage index budget-neutrality factor of 1.0016 (as discussed in section III.D.1 of this proposed rule) to the FY 2022 Federal per diem base rate of $832.94, yielding a proposed Federal per diem base rate of $856.80 for FY 2023. Similarly, we applied the proposed 2.7 percent payment rate update and the proposed 1.0016 wage index budget-neutrality factor to the FY 2022 ECT payment per treatment of $358.60, yielding a proposed ECT payment per treatment of $368.87 for FY 2023. 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 Federal per diem base rate and the ECT payment per treatment as follows: For IPFs that fail to report required data under the IPFQR Program, we applied a 0.7 percent payment rate update—that is, the proposed IPF market basket increase for FY 2023 of 3.1 percent less 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—and the proposed wage index budget-neutrality factor of 1.0016 to the FY 2022 Federal per diem base rate of $832.94, yielding a proposed Federal per diem base rate of $840.11 for FY 2023.
                For IPFs that fail to report required data under the IPFQR Program, we applied the proposed 0.7 percent annual payment rate update and the proposed 1.0016 wage index budget-neutrality factor to the FY 2022 ECT payment per treatment of $358.60, yielding a proposed ECT payment per treatment of $361.69 for FY 2023. Lastly, we are also proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2023 Federal per diem base rate and ECT payment per treatment for the final rule. C. Proposed Updates to the IPF PPS Patient-Level Adjustment Factors 1. Overview of the IPF PPS Adjustment Factors The IPF PPS payment adjustments 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, see the November 2004 IPF PPS final rule (69 FR 66935 through 66936). We are proposing to continue to use the existing regression-derived adjustment factors established in 2005 for FY 2023. However, we have used more recent claims data to simulate payments to finalize the outlier fixed dollar loss threshold amount and to assess the impact of the IPF PPS updates. 2. 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. a. Proposed Update to MS-DRG Assignment We believe it is important to maintain for IPFs the same diagnostic coding and Diagnosis Related Group (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' 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 November 28, 2003 IPF proposed rule (68 FR 66923; 66928 through 66933) and the November 15, 2004 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. For FY 2023, we are not proposing any changes to the IPF MS-DRG adjustment factors. Therefore, we are retaining the existing IPF MS-DRG adjustment factors. 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/​ICD10/​ICD-10-MS-DRG-Conversion-Project.html.* For FY 2023, we are proposing to continue to make the existing payment adjustment for psychiatric diagnoses that group to one of the existing 17 IPF MS-DRGs listed in Addendum A. Addendum A is available on our website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.*
                     Psychiatric principal diagnoses that do not group to one of the 17 designated MS-DRGs will still receive the Federal per diem base rate and all other applicable adjustments; 
                    ( print page 19421)
                    however, the payment will not include an MS-DRG adjustment. The diagnoses for each IPF MS-DRG will be updated as of October 1, 2022, using the final IPPS FY 2023 ICD-10-CM/PCS code sets. The FY 2023 IPPS/LTCH PPS final rule includes tables of the changes to the ICD-10-CM/PCS code sets, which underlie the FY 2023 IPF MS-DRGs. Both the FY 2023 IPPS final rule and the tables of final changes to the ICD-10-CM/PCS code sets, which underlie the FY 2023 MS-DRGs, are available on the CMS IPPS website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​AcuteInpatientPPS/​index.html.* 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, 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 November 2004 IPF PPS final rule (69 FR 66945) and see sections I.A.13 and I.B.7 of the FY 2020 ICD-10-CM Coding Guidelines, available at 
                    *https://www.cdc.gov/​nchs/​data/​icd/​10cmguidelines-FY2020_​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-9-CM (79 FR 46009). In FY 2022 there were 18 codes finalized for deletion from the ICD-10-CM codes in the IPF Code First table. For FY 2023, we are proposing to delete 2 ICD-10-PCS codes and proposing to add 48 ICD-10-PCS codes to the IPF Code First table. The proposed FY 2023 Code First table is shown in Addendum B on the CMS website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.* b. Proposed Payment for Comorbid Conditions 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. 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). 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, length of stay (LOS), or both treatment and LOS. 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. The 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 will identify the principal diagnosis code as non-psychiatric and search the secondary codes for a psychiatric code to assign an MS-DRG code for adjustment. The system will continue to search the secondary codes for those that are appropriate for comorbidity adjustment. As noted previously, 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 will 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 FY 2023, we are proposing to continue to use the same comorbidity adjustment factors in effect in FY 2022. The proposed FY 2023 comorbidity adjustment factors are found in Addendum A, available on the CMS website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.* For FY 2023, we are proposing to add 10 ICD-10-CM/PCS codes and remove 1 ICD-10-CM/PCS code from the Coagulation Factor category; proposing to add 3 ICD-10-CM/PCS codes and remove 11 ICD-10-CM/PCS codes from the Oncology Treatment comorbidity category; and proposing to add 4 ICD-10-CM/PCS codes to the Poisoning comorbidity category. The proposed FY 2023 comorbidity codes are shown in Addenda B, available on the CMS website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.* In accordance with the policy established in the FY 2015 IPF PPS final rule (79 FR 45949 through 45952), we reviewed all new FY 2023 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 
                    ( print page 19422)
                    specific diagnosis based on clinical assessment at the medical encounter. There were no proposed changes to the FY 2023 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 November 2004 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. For FY 2023, we are proposing to continue to use the patient age adjustments currently in effect in FY 2022, as shown in Addendum A of this rule (see 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html*). d. Proposed Variable Per Diem Adjustments We explained in the November 2004 IPF PPS final rule (69 FR 66946) that the regression analysis indicated that per diem cost declines as the length of stay (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 November 2004 IPF PPS final rule, 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 propose rule. For FY 2023, we are proposing to continue to use the variable per diem adjustment factors currently in effect, as shown in Addendum A to this rule, which is available on the CMS website at 
                    *https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientPsychFacilPPS/​tools.html.*
                     A complete discussion of the variable per diem adjustments appears in the November 2004 IPF PPS final rule (69 FR 66946). 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. 1. Wage Index Adjustment a. Background As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), RY 2009 IPF PPS (73 FR 25719) and the RY 2010 IPF PPS notices (74 FR 20373), in order 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 November 2004 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 so 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 (71 FR 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), requires us to 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 November 2004 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 the 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 to use 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.
                    ( print page 19423) 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 SNF PPS already used the concurrent IPPS hospital wage index data as the basis for the SNF PPS wage index. CMS 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 2023, we propose to continue to use the concurrent pre-floor, pre-reclassified IPPS hospital wage index as the basis for the IPF wage index. 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 on the basis of 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 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. In part due to the scope of changes involved in adopting the CBSA delineations for FY 2021, we finalized a 2-year transition policy in the FY 2021 IPF PPS final rule consistent with our past practice of using transition policies to help mitigate negative impacts on hospitals of certain wage index policy changes. We applied a 5-percent cap on wage index decreases to all IPF providers that had any decrease in their wage indexes, regardless of the circumstance causing the decline, so that an IPF's final wage index for FY 2021 would not be less than 95 percent of its final wage index for FY 2020, regardless of whether the IPF was part of an updated CBSA. We refer readers to the FY 2021 IPF PPS final rule (85 FR 47058 through 47059) for a more detailed discussion about the wage index transition policy for FY 2021. On March 6, 2020, OMB issued OMB Bulletin 20-01 (available on the web at 
                    *https://www.whitehouse.gov/​wp-content/​uploads/​2020/​03/​Bulletin-20-01.pdf*). In considering whether to adopt this bulletin, we analyzed whether the changes in this bulletin would have a material impact on the IPF PPS wage index. This bulletin creates only one Micropolitan statistical area. As discussed in further detail in section III.D.1.b.ii of this proposed rule since Micropolitan areas are considered rural for the IPF PPS wage index, this bulletin has no material impact on 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. Therefore, we did not propose to adopt OMB Bulletin 20-01 in the FY 2022 IPF PPS proposed rule. 2. 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. c. Proposed Permanent Cap on Wage Index Decreases As discussed in section III.D.1.b.(1) of this proposed rule, we have proposed and finalized temporary transition policies in the past to mitigate significant changes to payments due to changes to the IPF PPS wage index. Specifically, for FY 2016 (80 FR 46652), we implemented a 50/50 blend for all geographic areas consisting of the wage index values computed using the then-current OMB area delineations and the wage index values computed using new area delineations based on OMB Bulletin No. 13-01. In FY 2021 (85 FR 47059), we implemented a 2-year transition to mitigate any negative effects of wage index changes by applying a 5-percent cap on any decrease in an IPF's wage index from the IPF's final wage index from FY 2020. We explained that we believed the 5-percent cap would provide greater transparency and would be administratively less complex than the prior methodology of applying a 50/50 blended wage index. We indicated that no cap would be applied to the reduction in the wage index for the second year, that is, FY 2022, and that this transition approach struck an appropriate balance by providing a transition period to mitigate the resulting short-term instability and negative impacts on providers and time for them to adjust to their new labor 
                    ( print page 19424)
                    market area delineations and wage index values. In FY 2022 (86 FR 42616 through 42617), a couple of commenters recommended CMS extend the transition period adopted in the FY 2021 IPF PPS final rule. Because we did not propose to modify the transition policy that was finalized in the FY 2021 IPF PPS final rule, we did not extend the transition period for FY 2022. In the FY 2022 IPF PPS final rule, we stated that we continued to believe that applying the 5-percent cap transition policy in year one provided an adequate safeguard against any significant payment reductions associated with the adoption of the revised CBSA delineations in FY 2021, allowed for sufficient time to make operational changes for future FYs, and provided a reasonable balance between mitigating some short-term instability in IPF payments and improving the accuracy of the payment adjustment for differences in area wage levels. However, we acknowledged that certain changes to wage index policy may significantly affect Medicare payments. In addition, we reiterated that our policy principles with regard to the wage index include generally using the most current data and information available and providing that data and information, as well as any approaches to addressing any significant effects on Medicare payments resulting from these potential scenarios, in notice and comment rulemaking. With these policy principles in mind, we considered for this FY 2023 proposed rule how best to address the potential scenarios about which commenters raised concerns; that is, scenarios in which changes to wage index policy may significantly affect Medicare payments. In the past, we have established transition policies of limited duration to phase in significant changes to labor market areas. In taking this approach in the past, we sought to mitigate short-term instability and fluctuations that can negatively impact providers due to wage index changes. In accordance with the requirements of the IPF PPS wage index regulations at § 412.424(a)(2), we use an appropriate wage index based on the best available data, including the best available labor market area delineations, to adjust IPF PPS payments for wage differences. We have previously stated that, because the wage index is a relative measure of the value of labor in prescribed labor market areas, we believe it is important to implement new labor market area delineations with as minimal a transition as is reasonably possible. However, we recognize that changes to the wage index have the potential to create instability and significant negative impacts on certain providers even when labor market areas do not change. In addition, year-to-year fluctuations in an area's wage index can occur due to external factors beyond a provider's control, such as the COVID-19 PHE, and for an individual provider, these fluctuations can be difficult to predict. We also recognize that predictability in Medicare payments is important to enable providers to budget and plan their operations. In light of these considerations, we are proposing a permanent approach to smooth year-to-year changes in providers' wage indexes. We are proposing a policy that we believe increases the predictability of IPF PPS payments for providers and mitigates instability and significant negative impacts to providers resulting from changes to the wage index. As previously discussed, we believed applying a 5-percent cap on wage index decreases for FY 2021 provided greater transparency and was administratively less complex than prior transition methodologies. In addition, we believed this methodology mitigated short-term instability and fluctuations that can negatively impact providers due to wage index changes. Lastly, we believed the 5-percent cap applied to all wage index decreases for FY 2021 provided an adequate safeguard against significant payment reductions related to the adoption of the revised CBSAs. However, as discussed earlier in this section of the proposed rule, we recognize there are circumstances that a 1-year mitigation policy, like the one adopted for FY 2021, would not effectively address future years in which providers continue to be negatively affected by significant wage index decreases. Typical year-to-year variation in the IPF PPS wage index has historically been within 5 percent, and we expect this will continue to be the case in future years. Because providers are usually experienced with this level of wage index fluctuation, we believe applying a 5-percent cap on all wage index decreases each year, regardless of the reason for the decrease, would effectively mitigate instability in IPF PPS payments due to any significant wage index decreases that may affect providers in a year. Therefore, we believe this approach would address concerns about instability that commenters raised in the FY 2022 IPF PPS rule. In addition, we believe that applying a 5-percent cap on all wage index decreases would support increased predictability about IPF PPS payments for providers, enabling them to more effectively budget and plan their operations. Lastly, because applying a 5-percent cap on all wage index decreases would represent a small overall impact on the labor market area wage index system, we believe it would ensure the wage index is a relative measure of the value of labor in prescribed labor market areas. As discussed in further detail in section III.D.1.e of this proposed rule, we estimate that applying a 5-percent cap on all wage index decreases will have a very small effect on the wage index budget neutrality factor for FY 2023. Because the wage index is a measure of the value of labor (wage and wage-related costs) in a prescribed labor market area relative to the national average, we anticipate that in the absence of proposed policy changes most providers will not experience year-to-year wage index declines greater than 5 percent in any given year. Therefore, we anticipate that the impact to the wage index budget neutrality factor in future years would continue to be minimal. We also believe that when the 5-percent cap would be applied under this proposal, it is likely that it would be applied similarly to all IPFs in the same labor market area, as the hospital average hourly wage data in the CBSA (and any relative decreases compared to the national average hourly wage) would be similar. While this policy may result in IPFs in a CBSA receiving a higher wage index than others in the same area (such as situations when delineations change), we believe the impact would be temporary. The Secretary has broad authority to establish appropriate payment adjustments under the IPF PPS, including the wage index adjustment. As discussed earlier in this section, the IPF PPS regulations require us to use an appropriate wage index based on the best available data. For the reasons discussed in this section, we believe a 5-percent cap on wage index decreases would be appropriate for the IPF PPS. Therefore, for FY 2023 and subsequent years, we are proposing to apply a 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, regardless of the circumstances causing the decline. That is, we are proposing that an IPF's wage index for FY 2023 would not be less than 95 percent of its final wage index for FY 2022, regardless of whether the IPF is part of an updated CBSA, and that for subsequent years, a provider's wage index would not be less than 95 percent of its wage index calculated in the prior FY. This also means that if an IPF's 
                    ( print page 19425)
                    prior FY wage index is calculated with the application of the 5-percent cap, the following year's wage index would not be less than 95 percent of the IPF's capped wage index in the prior FY. For example, if an IPF's wage index for FY 2023 is calculated with the application of the 5-percent cap, then its wage index for FY 2024 would not be less than 95 percent of its capped wage index in FY 2023. Lastly, we propose 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 would reflect the proposed permanent cap on wage index decreases at § 412.424(d)(1)(i). As previously discussed, we believe this proposed methodology would maintain the IPF PPS wage index as a relative measure of the value of labor in prescribed labor market areas, increase predictability of IPF PPS payments for providers, and mitigate instability and significant negative impacts to providers resulting from significant changes to the wage index. In section VIII.C.2 of this proposed rule, we estimate the impact to payments for providers in FY 2023 based on this proposed policy. We also note that we would examine the effects of this policy on an ongoing basis in the future in order to assess its appropriateness. d. Proposed Adjustment for Rural Location In the November 2004 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. For FY 2023, we propose to continue to apply a 17 percent payment adjustment 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). e. Proposed 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 2023, 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 2023 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 use the following steps to ensure that the rates reflect the FY 2023 update to the wage indexes (based on the FY 2019 hospital cost report data) and the labor-related share in a budget-neutral manner: *Step 1:*
                     Simulate estimated IPF PPS payments, using the FY 2022 IPF wage index values (available on the CMS website) and labor-related share (as published in the FY 2022 IPF PPS final rule (86 FR 42608). *Step 2:*
                     Simulate estimated IPF PPS payments using the proposed FY 2023 IPF wage index values (available on the CMS website), the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, and the proposed FY 2023 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 2023 budget-neutral wage adjustment factor of 1.0016. *Step 4:*
                     Apply the FY 2023 budget-neutral wage adjustment factor from step 3 to the FY 2022 IPF PPS Federal per diem base rate after the application of the market basket update described in section III.A of this proposed rule, to determine the FY 2023 IPF PPS Federal per diem base rate. For this proposed rule, we also followed these steps to separately calculate the budget neutrality factor associated with the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year. First, we calculated the budget neutrality factor associated with the proposed FY 2023 IPF wage index and proposed FY 2023 labor-related share. We divided the amount of simulated payments using the FY 2022 IPF wage index and labor-related share by the amount of simulated payments using the proposed FY 2023 wage index and proposed FY 2023 labor-related share. The resulting quotient is 1.0017. Next, we calculated the budget neutrality factor associated with the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year. We divided the amount of simulated payments using the proposed FY 2023 wage index and proposed FY 2023 labor-related share by the amount of simulated payments using the proposed FY 2023 wage index, the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, and the proposed FY 2023 labor-related share. The resulting quotient is 0.9999. The combined budget neutrality factor, which is the proposed FY 2023 budget-neutral wage adjustment factor as discussed earlier in this section, is 1.0016. 2. Proposed Teaching Adjustment In the November 2004 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 full-time equivalent (FTE) interns and residents training in the IPF and the IPF's average daily census (ADC). Under the Inpatient Prospective Payment System (IPPS), 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. In addition, 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 November 2004 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/the IPF's ADC)). 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 the 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 
                    ( print page 19426)
                    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 (publication date of the IPF PPS final rule). 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, 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 November 2004 IPF PPS final rule (69 FR 66954 through 66957) and the RY 2009 IPF PPS notice (73 FR 25721). As with other adjustment factors derived through the regression analysis, we do not plan to rerun the teaching adjustment factors in the regression analysis until we more fully analyze IPF PPS data. Therefore, in this FY 2023 proposed rule, we are proposing to continue to retain the coefficient value of 0.5150 for the teaching adjustment to the Federal per diem base rate. 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 November 2004 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. Other Medicare prospective payment systems (for example, the IPPS and LTCH PPS) adopted a COLA to account for the cost differential of care furnished in Alaska and Hawaii. We analyzed the effect of applying a COLA to payments for IPFs located in Alaska and Hawaii. The results of our analysis demonstrated that a COLA for IPFs located in Alaska and Hawaii will improve payment equity for these facilities. As a result of this analysis, we provided a COLA in the November 2004 IPF PPS final rule. A COLA for IPFs located in Alaska and Hawaii is made by multiplying the non-labor-related portion of the Federal per diem base rate by the applicable COLA factor based on the COLA area in which the IPF is located. The COLA factors through 2009 were published by the Office of Personnel Management (OPM), and the OPM memo showing the 2009 COLA factors is available at 
                    *https://www.chcoc.gov/​content/​nonforeign-area-retirement-equity-assurance-act.* We note that the COLA areas for Alaska are not defined by county as are the COLA areas for Hawaii. In 5 CFR 591.207, the OPM established the following COLA areas: City of Anchorage, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse.
                City of Fairbanks, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse.
                City of Juneau, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse.
                Rest of the state of Alaska. As stated in the November 2004 IPF PPS final rule, we update the COLA factors according to updates established by the OPM. However, sections 1911 through 1919 of the Non-foreign Area Retirement Equity Assurance Act, as contained in subtitle B of title XIX of the National Defense Authorization Act (NDAA) for FY 2010 (Pub. L. 111-84, October 28, 2009), transitions the Alaska and Hawaii COLAs to locality pay. Under section 1914 of NDAA, locality pay was phased in over a 3-year period beginning in January 2010, with COLA rates frozen as of the date of enactment, October 28, 2009, and then proportionately reduced to reflect the phase-in of locality pay. When we published the proposed COLA factors in the RY 2012 IPF PPS proposed rule (76 FR 4998), we inadvertently selected the FY 2010 COLA rates, which had been reduced to account for the phase-in of locality pay. We did not intend to propose the reduced COLA rates because that would have understated the adjustment. Since the 2009 COLA rates did not reflect the phase-in of locality pay, we finalized the FY 2009 COLA rates for RY 2010 through RY 2014. In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), we established a new methodology to update the COLA factors for Alaska and Hawaii, and adopted this methodology for the IPF PPS in the FY 2015 IPF final rule (79 FR 45958 through 45960). We adopted this new COLA methodology for the IPF PPS because IPFs are hospitals with a similar mix of commodities and services. We believe it is appropriate to have a consistent policy approach with that of other hospitals in Alaska and Hawaii. Therefore, the IPF COLAs for FY 2015 through FY 2017 were the same as those applied under the IPPS in those years. As finalized in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53700 and 53701), the COLA updates are determined every 4 years, when the IPPS market basket labor-related share is updated. Because the labor-related share of the IPPS market basket was most recently updated for FY 2022, the COLA factors were updated in FY 2022 IPPS/LTCH rulemaking (86 FR 45547). As such, we also updated the IPF PPS COLA factors for FY 2022 (86 FR 42621 through 42622) to reflect the updated COLA factors finalized in the FY 2022 IPPS/LTCH rulemaking. Table 2 shows the proposed IPF PPS COLA factors effective for FY 2022 through FY 2025. Table 2—IPF PPS Cost-of-Living Adjustment Factors: IPFs Located in Alaska and Hawaii
Area
FY 2022
                             through 
                             FY 2025Alaska:City of Anchorage and 80-kilometer (50-mile) radius by road
1.22City of Fairbanks and 80-kilometer (50-mile) radius by road
1.22City of Juneau and 80-kilometer (50-mile) radius by road
1.22Rest of Alaska
1.24Hawaii:City and County of Honolulu
1.25( print page 19427)County of Hawaii
1.22County of Kauai
1.25County of Maui and County of Kalawao
1.25
 The proposed IPF PPS COLA factors for FY 2023 are also shown in Addendum A to this proposed rule, and 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 Emergency Department (ED) The IPF PPS includes a facility-level adjustment for IPFs with qualifying EDs. 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 CAH, for preadmission services otherwise payable under the Medicare Hospital Outpatient Prospective Payment System (OPPS), furnished to a beneficiary on the date of the beneficiary's admission to the hospital and during the day immediately preceding the date of admission to the IPF (see § 413.40(c)(2)), and the overhead cost of maintaining the ED. This payment is a facility-level adjustment that applies to all IPF admissions (with one exception which we described), regardless of whether a particular patient receives preadmission services in the hospital's ED. The ED adjustment is incorporated into the variable per diem adjustment for the first day of each stay for IPFs with a qualifying ED. Those IPFs with a qualifying ED receive an adjustment factor of 1.31 as the variable per diem adjustment for day 1 of each patient stay. If an IPF does not have a qualifying ED, it receives an adjustment factor of 1.19 as the variable per diem adjustment for day 1 of each patient stay. The ED adjustment is made on every qualifying claim except as described in this section of the proposed rule. As specified in § 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 November 2004 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. Therefore, when patients are discharged from an IPPS hospital or CAH and admitted to the same hospital's or CAH's excluded psychiatric unit, the IPF receives the 1.19 adjustment factor as the variable per diem adjustment for the first day of the patient's stay in the IPF. For FY 2023, we are proposing to continue to retain the 1.31 adjustment factor for IPFs with qualifying EDs. A complete discussion of the steps involved in the calculation of the ED adjustment factors are in the November 2004 IPF PPS final rule (69 FR 66959 through 66960) and the RY 2007 IPF PPS final rule (71 FR 27070 through 27072). E. Other Final 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 November 2004 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, and 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 in order 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. 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. Last year for the FY 2022 IPF PPS final rule, we finalized the use of FY 2019 claims rather than the more recent FY 2020 claims for updating the outlier fixed dollar loss threshold (86 FR 42623). We 
                    ( print page 19428)
                    noted that our use of the FY 2019 claims to set the final outlier fixed dollar loss threshold for FY 2022 deviated from our longstanding practice of using the most recent available year of claims, but remained otherwise consistent with the established outlier update methodology. We explained that we finalized our proposal to deviate from our longstanding practice of using the most recent available year of claims only because, and to the extent that, the “coronavirus disease 2019” (abbreviated “COVID-19”) Public Health Emergency (PHE) appeared to have significantly impacted the FY 2020 IPF claims. We further stated that we intended to continue to analyze further data in order to better understand both the short-term and long-term effects of the COVID-19 PHE on IPFs (86 FR 42624). For this FY 2023 IPF PPS proposed rulemaking, consistent with our longstanding practice, we analyzed the most recent available data for simulating IPF PPS payments in FY 2023. We observed a continuation of two main trends that we noted in our analysis of FY 2020 claims for FY 2022—that is, an overall increase in average cost per day and an overall decrease in the number of covered days. However, we also identified that some providers had significant increases in their charges, resulting in higher than normal estimated cost per day that would skew our estimate of outlier payments for FY 2022 and FY 2023. Historically, we have applied statistical trims under the IPF PPS in order to improve the statistical validity of the data used for ratesetting. In the November 2004 final rule, we explained that we applied a 3 standard deviation trim on cost per day prior to calculating the average per diem cost used to calculate the IPF PPS Federal per diem base rate (69 FR 66927). Furthermore, as discussed in section III.E.3 of this proposed rule, our longstanding policy applies a ceiling on a provider's cost-to-charge ratio when it exceeds 3 standard deviations from the mean cost-to-charge ratio for urban or rural providers. We are proposing a similar approach in order to address the skew in estimated cost per day that we observed in the FY 2021 claims. Specifically, we are proposing for FY 2023 to exclude providers from our simulation of IPF PPS payments for FY 2022 and FY 2023 if their change in estimated average cost per day is outside 3 standard deviations from the mean. Based on an analysis of the December 2021 update of FY 2021 IPF claims and the FY 2022 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. We are proposing to update the IPF outlier threshold amount for FY 2023 using FY 2021 claims data and the same methodology that we used to set the initial outlier threshold amount in the RY 2007 IPF PPS final rule (71 FR 27072 and 27073), which is also the same methodology that we used to update the outlier threshold amounts for years 2008 through 2022. However, as discussed earlier in this section, we also propose for FY 2023 to exclude providers from our impact simulations whose change in simulated cost per day is outside 3 standard deviations from the mean. Based on an analysis of these updated data, we estimate that IPF outlier payments as a percentage of total estimated payments are approximately 3.2 percent in FY 2022. Therefore, we are proposing to update the outlier threshold amount to $24,270 to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF payments for FY 2023. This proposed update is an increase from the FY 2022 threshold of $16,040. 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. In order 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 we indicated in the November 2004 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 November 2004 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 2023, we propose to continue to follow 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 upper threshold CCR for IPFs in FY 2023 is 2.0472 for rural IPFs, and 1.7279 for urban IPFs, based on 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 MAC obtains inaccurate or incomplete data with which to calculate a CCR. We are proposing to continue to update the FY 2023 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 2023, to be used in each of the three situations listed previously, using the most recent CCRs entered in the CY 2022 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 CBSA-based geographic designations. A complete discussion regarding the national median CCRs appears in the November 2004 IPF PPS final rule (69 FR 66961 through 66964). IV. Comment Solicitation on Analysis of IPF PPS Adjustments A. Background As discussed in section III.C.1 of this proposed rule, we are proposing to continue to use the existing regression-derived adjustment factors for FY 2023. In the November 15, 2004 final rule, we indicated that we did not intend to update the regression analysis and the patient-level and facility-level adjustments until we complete further 
                    ( print page 19429)
                    analysis of IPF costs using IPF PPS data that yields as much information as possible regarding the patient-level characteristics of the population that each IPF serves. Since that time, we undertook analysis to better understand IPF industry practices so that we may refine the IPF PPS in the future, as appropriate. For RY 2012, we identified several areas of concern for future refinement, and we invited comments on these issues in the RY 2012 IPF PPS proposed and final rules. For further discussion of these issues and to review the public comments, we refer readers to the RY 2012 IPF PPS proposed rule (76 FR 4998) and final rule (76 FR 26432). Our preliminary analysis, which we previously discussed in the FY 2016 IPF PPS final rule (80 FR 46693 through 46694), also revealed variation in cost and claim data, particularly related to labor costs, drugs costs, and laboratory services. We found that some providers have very low labor costs, or very low or missing drug or laboratory costs or charges, relative to other providers. As we noted in the FY 2016 IPF PPS final rule, our preliminary analysis of 2012 to 2013 IPF data found that over 20 percent of IPF stays reported no ancillary costs, such as laboratory and drug costs, in their cost reports, or laboratory or drug charges on their claims. In the past, we stated that we expect that most patients requiring hospitalization for active psychiatric treatment would need drugs and laboratory services, and we reminded providers that the IPF PPS Federal per diem base rate includes the cost of all ancillary services, including drugs and laboratory services. 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 the requirement 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. For details, we refer readers to see these Transmittals, which are available on the CMS website at 
                    *https://www.cms.gov/​Regulationsand-Guidance/​Guidance/​Transmittals/​index.html.*
                     CMS suspended the requirement that cost reports from psychiatric hospitals include certain ancillary costs effective April 27, 2018, in order to consider excluding all-inclusive rate providers from this requirement. CMS 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. B. Update and Comment Solicitation on Analysis of IPF PPS Adjustments Working in collaboration with a contractor, we have undertaken further analysis of more recent IPF cost and claim information. We have posted a report on the CMS website, which summarizes the results of the latest analysis. For public awareness, this report is available online at 
                    *https://www.cms.gov/​medicare/​medicare-fee-for-service-payment/​inpatientpsychfacilpps.*
                     This updated analysis finds that the existing IPF PPS model continues to be generally appropriate in terms of effectively aligning IPF PPS payments with the cost of providing IPF services, but suggests that certain updates to the codes, categories, adjustment factors, and ECT payment amount per treatment could improve payment accuracy. We are requesting comments on the results of our latest analysis as summarized in the report. In particular, we are interested in comments about the following topics, which are discussed in detail in the report: The report summarizes results of the analysis regarding patient-level characteristics, about which we are requesting comments: ++ The updated regression analysis suggests that certain technical changes to the DRG and comorbidity adjustment factors, consolidation of the age categories for the patient age adjustment, and changes to the adjustment factors for age and length of stay could be appropriate. ++ The analysis of ancillary costs for IPF stays with ECT suggests that a higher ECT payment amount per treatment could better align IPF PPS payments with the costs of furnishing ECT. ++ The analysis of the outlier percentage suggests that fewer IPF cases qualify for outliers under the current 2 percent outlier target than were estimated when the IPF PPS was established. We estimate that increasing the outlier percentage would increase the number of IPF cases that qualify for outliers, but would have distributional effects due to budget neutrality. The report summarizes the results of analysis regarding facility-level characteristics, about which we are requesting comments: ++ The updated regression analysis suggests that updating the adjustment factors for teaching facilities, rural facilities, and facilities with an ED could improve payment accuracy; however, we estimate such changes could have positive and negative effects on payments for different types of IPFs. ++ The analysis of occupancy-related control variables included in the regression model indicates that these control variables are correlated with the rural adjustment factor, and that removal of these control variables from the model could result in an increase to the rural adjustment factor in the regression model. The report summarizes certain areas where we believe additional research is needed. We are requesting comments about the results summarized in the report. We are also requesting comments about additional analyses that we should undertake to better understand how these issues affect the cost of providing IPF services, and how the IPF PPS could better account for these costs: ++ We analyzed the costs associated with social determinants of health, but found that our analysis was confounded by a low frequency of IPF claims reporting the applicable ICD-10 diagnosis codes. We are soliciting public comments about the results of this analysis, and whether there are additional patient characteristics that affect the cost of providing IPF services that may not be consistently reported on claims. Additionally, we are soliciting public comments about how we could better identify such patient characteristics and their effects on costs. ++ We analyzed the costs associated with the percentage of low-income patients that IPFs treat, based on a construction of the Disproportionate Share Hospitals (DSH) percentage that is used in other payment systems using the data currently available for IPFs. We are soliciting public comments about the results of this analysis, which suggest that the addition of an adjustment factor for disproportionate share intensity could improve the accuracy of IPF PPS payments. V. Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program A. Overarching Principles for Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs—Request for Information Significant and persistent disparities in healthcare outcomes exist in the United States. Belonging to an underserved community is often associated with worse health 
                    ( print page 19430)
                    outcomes.[1 2 3 4 5 6 7 8 9]
                     With this in mind, CMS aims to advance health equity, by which we mean the attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes. CMS is working to advance health equity by designing, implementing, and operationalizing policies and programs that support health for all the people served by our programs, eliminating avoidable differences in health outcomes experienced by people who are disadvantaged or underserved, and providing the care and support that our beneficiaries need to thrive.[10] We are committed to achieving equity in healthcare outcomes for our enrollees by supporting healthcare providers' quality improvement activities to reduce health disparities, enabling them to make more informed decisions, and promoting healthcare provider accountability for healthcare disparities.[11]
                    
                     Measuring healthcare disparities in quality measures is a cornerstone of our approach to advancing healthcare equity. Hospital performance results that illustrate differences in outcomes between patient populations have been reported to hospitals confidentially since 2018. This RFI consists of three sections. The first section discusses a general framework that could be utilized across CMS quality programs to assess disparities in healthcare quality. The next section outlines approaches that could be used in the IPFQR Program to assess drivers of healthcare quality disparities in the IPFQR Program. Additionally, this section discusses measures of health equity that could be adapted for use in the IPFQR Program. Finally, the third section solicits public comment on the principles and approaches listed in the first two sections as well as seeking other thoughts about disparity measurement guidelines for the IPFQR Program. 1. Cross-Setting Framework To Assess Healthcare Quality Disparities CMS has identified five key considerations that we could apply consistently across CMS programs when advancing the use of measurement and stratification as tools to address health care disparities and advance health equity. The remainder of this section describes each of these considerations. a. Identification of Goals and Approaches for Measuring Healthcare Disparities and Using Measures Stratification Across CMS Quality Programs By quantifying healthcare disparities through measure stratification (that is, measuring performance differences among subgroups of beneficiaries), we aim to provide useful tools for healthcare providers to drive improvement based on data. We hope that these results support healthcare providers efforts in examining the underlying drivers of disparities in their patients' care and to develop their own innovative and targeted quality improvement interventions. Quantification of health disparities can also support communities in prioritizing and engaging with healthcare providers to execute such interventions, as well as providing additional tools for accountability and decision-making. There are several different conceptual approaches to reporting health disparities in the acute care setting, including two complementary approaches that are already used to confidentially provide disparity information to hospitals for a subset of existing measures. The first approach, referred to as the “within-hospital disparity method,” compares measure performance results for a single measure between subgroups of patients with and without a given factor. This type of comparison directly estimates disparities in outcomes between subgroups and can be helpful to identify potential disparities in care. This type of approach can be used with most measures that include patient-level data. The second approach, referred to as the “between-hospital disparity methodology,” provides performance on measures for only the subgroup of patients with a particular social risk factor. These approaches can be used by a healthcare provider to compare their own measure performance on a particular subgroup of patients against subgroup-specific state and national benchmarks. Alone, each approach may provide an incomplete picture of disparities in care for a particular measure, but when reported together with overall quality performance, these approaches may provide detailed information about where differences in care may exist or where additional scrutiny may be appropriate. For example, the between-provider disparity method may indicate that an IPF underperformed (when compared to other facilities on average) for patients with a given social risk factor, which would signal the need to improve care for this population. However, if the IPF also underperformed for patients without that social risk factor, the measured difference, or disparity in care, (the “within-hospital” disparity, as described above) could be negligible even though performance for the group that has been historically marginalized remains poor. We refer readers to the technical report describing the CMS Disparity Methods in detail as well as the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through 38407) and the posted Disparity methods Updates and Specifications Report posted on the QualityNet website.[12] 
 
 CMS is interested in whether similar approaches to the two discussed in the previous paragraph could be used to produce confidential stratified measure results for selected IPF QRP measures, as appropriate and feasible. However, final decisions regarding disparity reporting will be made at the program-level, as CMS intends to tailor the approach used in each setting to achieve the greatest benefit and avoid unintentional consequences or biases in measurement that may exacerbate disparities in care. b. Guiding Principles for Selecting and Prioritizing Measures for Disparity Reporting We intend to expand our efforts to provide stratified reporting for additional clinical quality measures, provided they offer meaningful, actionable, and valid feedback to healthcare providers on their care for populations that may face social disadvantage or other forms of discrimination or bias. We are mindful, however, that it may not be possible to calculate stratified results for all quality measures, and that there may be situations where stratified reporting is not desired. To help inform prioritization of the next generation of candidate measures for stratified reporting, we aim to receive feedback on several systematic principles under consideration that we believe will help us prioritize measures for disparity reporting across programs: (1) Programs may consider stratification among existing 
                    *clinical quality measures for further disparity reporting,*
                     prioritizing recognized measures which have met industry standards for measure reliability and validity. (2) Programs may consider measures for prioritization that show 
                    *evidence that a treatment or outcome being measured is affected by underlying healthcare disparities*
                     for a specific social or demographic factor. Literature related to the measure or outcome should be reviewed to identify disparities related to the treatment or outcome, and should carefully consider both social risk factors and patient demographics. In addition, analysis of Medicare-specific data should be done in order to demonstrate evidence of disparity in care for some or most healthcare providers that treat Medicare patients. (3) Programs may consider establishing 
                    *statistical reliability and representation standards*
                     (for example, the percent of patients with a social risk factor included in reporting facilities) prior to reporting results. They may also consider prioritizing measures that reflect performance on greater numbers of patients to ensure that the reported results of the disparity calculation are reliable and representative. (4) After completing stratification, programs may consider prioritizing the 
                    *reporting of measures that show differences in measure performance*
                     between subgroups across healthcare providers. c. Principles for Social Risk Factor and Demographic Data Selection and Use Social risk factors are the wide array of non-clinical drivers of health known to negatively impact patient outcomes. These include factors such as socioeconomic status, housing availability, and nutrition (among others), often inequitably affecting historically marginalized communities on the basis of race and ethnicity, rurality, sexual orientation and gender identity, religion, and disability.[13 14 15 16 17 18 19 20] Identifying and prioritizing social risk or demographic variables to consider for disparity reporting can be challenging. This is due to the high number of variables that have been identified in the literature as risk factors for poorer health outcomes and the limited availability of many self-reported social risk factors and demographic factors across the healthcare sector. Several proxy data sources, such as area-based indicators of social risk and imputation methods, may be used if individual patient-level data is not available. Each source of data has advantages and disadvantages for disparity reporting: *Patient-reported data*
                     are considered to be the gold standard for evaluating quality of care for patients with social risk factors.[21]
                    
                     While data sources for many social risk factors and demographic variables are still developing among several CMS settings, the IPFQR Program will begin collecting mandatory patient-level data for certain chart-abstracted measures the FY 2024 payment determination and subsequent years (86 FR 42608). *CMS Administrative Claims data*
                     have long been used for quality measurement due to their availability and will continue to be evaluated for usability in measure development and or stratification. Using these existing data allows for high impact analyses with negligible healthcare provider burden. For example, dual eligibility for Medicare and Medicaid has been found to be an effective indicator of social risk in beneficiary populations.[22]
                    
                     There are, however, limitations in these data's usability for stratification analysis. *Area-based indicators of social risk*
                     create approximations of patient risk based on the neighborhood or context that a patient resides in. Several indexes, such as Agency for Healthcare Research and Quality (AHRQ) Socioeconomic Status (SES) Index,
                    [23]( print page 19432)
                    Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI),[24]
                    
                     and Health Resources and Services Administration (HRSA) Area Deprivation Index (ADI),[25]
                    
                     provide multifaceted contextual information about an area and may be considered as an efficient way to stratify measures that include many social risk factors. *Imputed data sources*
                     use statistical techniques to estimate patient-reported factors, including race and ethnicity. One such tool is the Medicare Bayesian Improved Surname Geocoding (MBISG) method (currently in version 2.1), which combines information from administrative data, surname, and residential location to estimate patient race and ethnicity.[26] d. Identifying Meaningful Performance Differences While we aim to use standardized approaches where possible, identifying differences in performance on stratified results will be made at the program level due to contextual variations across programs and settings. We look forward to feedback on the benefits and limitations of the possible reporting approaches described below: *Statistical approaches*
                     could be used to reliably group results, such as using confidence intervals, creating cut points based on standard deviations, or using a clustering algorithm. **
                     Programs could use a 
                    *ranked ordering and percentile approach,*
                     ordering healthcare providers in a ranked system based on their performance on disparity measures to quickly allow them to compare their performance to other similar healthcare providers. **
                     Healthcare providers could be categorized into groups based on their performance using 
                    *defined thresholds,*
                     such as fixed intervals of results of disparity measures, indicating different levels of performance. *Benchmarking,*
                     or comparing individual results to state or national average, is another potential reporting strategy.
                Finally, a ranking system may not be appropriate for all programs and care settings, and some programs may*only report disparity results.* e. Guiding Principles for Reporting Disparity Measures Reporting of the results discussed above can be employed in several ways to drive improvements in quality. Confidential reporting, or reporting results privately to healthcare providers, is generally used for new programs or new measures recently adopted for programs through notice and comment rulemaking to give healthcare providers an opportunity to become more familiar with calculation methods and to improve before other forms of reporting are used. In addition, many results are reported publicly, in accordance with the statute. This method provides all stakeholders with important information on healthcare provider quality, and in turn, relies on market forces to incentivize healthcare providers to improve and become more competitive in their markets without directly influencing payment from CMS. One important consideration is to assess differential impact on IPFs, such as those located in rural, or critical access areas, to ensure that reporting does not disadvantage already resource-limited settings. The type of reporting chosen by programs will depend on the program context. Regardless of the methods used to report results, it is important to report stratified measure data alongside overall measure results. Review of both measures results along with stratified results can illuminate greater levels of detail about quality of care for subgroups of patients, providing important information to drive quality improvement. Unstratified quality measure results address general differences in quality of care between healthcare providers and promote improvement for all patients, but unless stratified results are available, it is unclear if there are subgroups of patients that benefit most from initiatives. Notably, even if overall quality measure scores improve, without identifying and measuring differences in outcomes between groups of patients, it is impossible to track progress in reducing disparity for patients with heightened risk of poor outcomes. 2. Approaches to Assessing Drivers of Healthcare Quality Disparities and Developing Measures of Healthcare Equity in the IPFQR Program This section presents information on two approaches for the IPFQR Program. The first section presents information about a method that could be used to assist IPFs in identifying potential drivers of healthcare quality disparities. The second section describes measures of healthcare equity that might be appropriate for inclusion in the IPFQR Program. a. Performance Disparity Decomposition In response to the FY 2022 IPF PPS proposed rule's RFI (86 FR 19494 through 19500), “Closing the Health Equity Gap in CMS Quality Programs”, some stakeholders noted that identifying which factors are contributing to the performance gaps may not always be straightforward, especially if the IPF has limited information or resources to determine the extent to which a patient's social determinants of health (SDOH) or other mediating factors (for example: Health histories) explain a given disparity. An additional complicating factor is the reality that there are likely multiple SDOH and other mediating factors responsible for a given disparity, and it may not be obvious to the IPF which of these factors are the primary drivers. Consequently, CMS may consider methods to use the data already available in enrollment, claims, and assessment data to estimate the extent to which various SDOH (for example, transportation, health literacy) and other mediating factors drive disparities in an effort to provide more actionable information. Researchers have utilized decomposition techniques to examine inequality in health care and, specifically, as a way to understand and explain the underlying causes of inequality.[27]
                    
                     At a high level, regression decomposition is a method that allows one to estimate the extent to which disparities (that is, differences) in measure performance between subgroups of patient populations are due to specific factors. These factors can be either non-clinical (for example, SDOH) or clinical. Similarly, CMS may utilize regression decomposition to 
                    ( print page 19433)
                    identify and calculate the specific contribution of SDOHs and other mediating factors to observed disparities. This approach may better inform our understanding of the extent to which providers and policy-makers may be able to narrow the gap in healthcare outcomes. Additionally, provider-specific decomposition results could be shared through confidential results so that IPFs can see the disparities within their facility with more granularity, allowing them to set priority targets in some performance areas while knowing which areas of their care are already relatively equitable. Importantly, these results could help IPFs identify reasons for disparities that might not be obvious without having access to additional data sources (for example: The ability to link data across providers). To more explicitly demonstrate the types of information that could be provided through decomposition of a measure disparity, consider the following example for a given IPF. Figures 1 through 3 depict an example (using hypothetical data) of how a disparity in a measure of Medicare Spending Per Beneficiary (MSPB) between dual eligible beneficiaries (that is, those enrolled in Medicare and Medicaid) and non-dual eligible beneficiaries (that is, those with Medicare only) could be decomposed among two mediating factors, one SDOH and one clinical factor: (1) Low health literacy and (2) high volume of emergency department (ED) use. These examples were selected because they are factors the healthcare provider could mitigate the effects of, if they were shown to be drivers of disparity in their IPF. Additionally, high volume ED use is used as a potential mediating factor that could be difficult for IPFs to determine on their own, as it would require having longitudinal data for patients across multiple facilities. In Figure 1, the overall Medicare spending disparity is $1,000: Spending, on average, is $5,000 per non-dual beneficiary and $6,000 per dual beneficiary. We can also see from Figure 2 that in this IPF, the dual population has twice the prevalence of beneficiaries with low health literacy and high ED use compared to the non-dual population. Using regression techniques, the difference in overall spending between non-dual and dual beneficiaries can be divided into three causes: (1) A difference in the prevalence of mediating factors (for example: Low health literacy and high ED use) between the two groups, (2) a difference in how much spending is observed for beneficiaries with these mediating factors between the two groups, and (3) differences in baseline spending that are not due to either (1) or (2). In Figure 3, the `Non-Dual Beneficiaries' column breaks down the overall spending per non-dual beneficiary, $5,000, into a baseline spending of $4,600 plus the effects of the higher spending for the 10 percent of non-dual beneficiaries with low health literacy ($300) and the 5 percent with high ED use ($100). The `Dual Beneficiaries' column similarly decomposes the overall spending per dual beneficiary ($6,000) into a baseline spending of $5,000, plus the amounts due to dual beneficiaries' 20 percent prevalence of low health literacy ($600, twice as large as the figure for non-dual beneficiaries because the prevalence is twice as high), and dual beneficiaries' 10 percent prevalence of high-volume ED use ($200, similarly twice as high as for non-duals beneficiaries due to higher prevalence). This column also includes an additional $100 per risk factor because dual beneficiaries experience a higher cost than non-dual beneficiaries within the low health literacy risk factor, and similarly within the high ED use risk factor. Based on this information, an IPF can determine that the overall $1,000 disparity can be divided into differences simply due to risk factor prevalence ($300 + $100 = $400 or 40 percent of the total disparity), disparities in costs for beneficiaries with risk factors ($100 + $100 = $200 or 20 percent) and disparities that remain unexplained (differences in baseline costs: $400 or 40 percent). In particular, the IPF can see that simply having more patients with low health literacy and high ED use accounts for a disparity of $400. In addition, there is still a $200 disparity stemming from differences in costs between non-dual and dual patients for a given risk factor, and another $400 that is not explained by either low health literacy or high ED use. These differences may instead be explained by other SDOH that have not yet been included in this breakdown, or by the distinctive pattern of care decisions made by providers for dual and non-dual beneficiaries. These cost estimates would provide additional information that facilities could use when determining where to devote resources aimed at achieving equitable health outcomes (for example, facilities may choose to focus efforts on the largest drivers of a disparity). 
 
  
 
  b. Measures Related to Health Equity Beyond identifying disparities in individual health outcomes and by individual risk factors, there is interest in developing more comprehensive measures of health equity that reflect organizational performance. When determining which equity measures could be prioritized for development for the IPFQRP Program, CMS may consider the following: Measures should be actionable in terms of quality improvement;
                Measures should help beneficiaries and their caregivers make informed healthcare decisions;
                Measures should not create incentives to lower the quality of care; and
                Measures should adhere to high scientific acceptability standards. CMS has developed measures assessing health equity, or designed to promote health equity, in other settings outside of the IPF. As a result, there may be measures that could be adapted for use in the IPFQR Program. The remainder of this section discusses two such measures, beginning with the Health Equity Summary Score (HESS), and then a structural measure assessing the degree of hospital leadership engagement in health equity performance data.
                    ( print page 19436) (1) Health Equity Summary Score The HESS measure was developed by the CMS OMH [28]
                     [29]
                    
                     to identify and to reward healthcare providers (that is, Medicare Advantage [MA] plans) that perform relatively well on measures of care provided to beneficiaries with social risk factors (SRFs), as well as to discourage the non-treatment of patients who are potentially high-risk, in the context of value-based purchasing. Additionally, a version of the HESS is under consideration for the Hospital Inpatient Quality Reporting (HIQR) program.[30]
                    
                     The HESS composite measure provides a summary of equity of care delivery by combining performance and improvement across multiple measures and multiple at-risk groups. The HESS was developed with the following goals: Allow for “multiple grouping variables, not all of which will be measurable for all plans,” allow for “disaggregation by grouping variable for nuanced insights,” and allow for the future usage of additional and different SRFs for grouping.[31] The HESS computes across-provider disparity in performance, as well as within-provider and across-provider disparity improvement in performance. Calculation starts with a cross-sectional score and an overall improvement score for each SRF of race/ethnicity and dual eligibility, for each plan. The overall improvement score is based on two separate improvement metrics: Within-plan improvement and nationally benchmarked improvement. Within-plan improvement is defined as how that plan improves the care of patients with SRFs relative to higher-performing patients between the baseline period and performance period, and is targeted at eliminating within-plan disparities. Nationally benchmarked improvement is improvement of care for beneficiaries with SRFs served by that MA plan, relative to the improvement of care for similar beneficiaries across all MA plans, and is targeted at improving the overall care of populations with SRFs. Within-plan improvement and nationally benchmarked improvement are then combined into an overall improvement score. Meanwhile, the cross-sectional score measures overall measure performance among beneficiaries with SRFs during the performance period, regardless of improvement. To calculate a provider's overall score, the HESS uses a composite of five clinical quality measures based on HEDIS data and seven MA Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experience measures. A provider's overall HESS score is calculated once using only CAHPS-based measures and once using only HEDIS-based measures, due to incompatibility between the two data sources. The HESS uses a composite of these measures to form a cross-sectional score, a nationally benchmarked improvement score, and a within-plan improvement score, one for each SRF. These scores are combined to produce an SRF-specific blended score, which is then combined with the blended score for another SRF to produce the overall HESS. (2) Degree of Hospital Leadership Engagement in Health Equity Performance Data CMS has developed a structural measure for use in acute care hospitals assessing the degree to which hospital leadership is engaged in the collection of health equity performance data, with the motivation that that organizational leadership and culture can play an essential role in advancing equity goals. This structural measure, entitled the Hospital Commitment to Health Equity measure (MUC2021-106) was included on the 2021 CMS List of Measures Under Consideration (MUC List) [32]
                    
                     and assesses hospital commitment to health equity using a suite of equity-focused organizational competencies aimed at achieving health equity for racial and ethnic minorities, people with disabilities, sexual and gender minorities, individuals with limited English proficiency, rural populations, religious minorities, and people facing socioeconomic challenges. The measure will include five attestation-based questions, each representing a separate domain of commitment. A hospital will receive a point for each domain where they attest to the corresponding statement (for a total of 5 points). At a high level, the five domains cover the following areas: (1) Strategic plan to reduce health disparities; (2) approach to collecting valid and reliable demographic and SDOH data; (3) analyses performed to assess disparities; (4) engagement in quality improvement activities; [33]
                    
                     and (5) leadership involvement in activities designed to reduce disparities. The specific questions asked within each domain, as well as the detailed measure specification are found in the CMS List of MUC for December 2021 at 
                    *https://www.cms.gov/​files/​document/​measures-under-consideration-list-2021-report.pdf.*
                     An IPF could receive a point for each domain where data are submitted through a CMS portal to reflect actions taken by the IPF for each corresponding domain (for a point total). CMS believes this type of organizational commitment structural measure may complement the health disparities approach described in previous sections, and support IPFs in quality improvement, efficient, effective use of resources, and leveraging available data. As defined by AHRQ, structural measures aim to “give consumers a sense of a healthcare provider's capacity, systems, and processes to provide high-quality care.” [34]
                    
                     We acknowledge that collection of this structural measure may impose administrative and/or reporting requirements for IPFs. We are interested in obtaining feedback from stakeholders on conceptual and measurement priorities for the IPFQR Program to better illuminate organizational commitment to health equity.
                    ( print page 19437) 3. Solicitation of Public Comment The goal of this request for information is to describe key principles and approaches that we will consider when advancing the use of quality measure development and stratification to address healthcare disparities and advance health equity across our programs. We invite general comments on the principles and approaches described previously in this section of the rule, as well as additional thoughts about disparity measurement or stratification guidelines suitable for overarching consideration across CMS' QRP programs. Specifically, we invite comment on: • Identification of Goals and Approaches for Measuring Healthcare Disparities and Using Measure Stratification Across CMS Quality Reporting Programs ++ The use of the within- and between-provider disparity methods in IPFs to present stratified measure results ++ The use of decomposition approaches to explain possible causes of measure performance disparities ++ Alternative methods to identify disparities and the drivers of disparities Guiding Principles for Selecting and Prioritizing Measures for Disparity Reporting ++ Principles to consider for prioritization of health equity measures and measures for disparity reporting, including prioritizing stratification for validated clinical quality measures, those measures with established disparities in care, measures that have adequate sample size and representation among healthcare providers and outcomes, and measures of appropriate access and care. Principles for Social Risk Factor and Demographic Data Selection and Use ++ Principles to be considered for the selection of social risk factors and demographic data for use in collecting disparity data including the importance of expanding variables used in measure stratification to consider a wide range of social risk factors, demographic variables and other markers of historic disadvantage. In the absence of patient-reported data we will consider use of administrative data, area-based indicators and imputed variables as appropriate Identification of Meaningful Performance Differences ++ Ways that meaningful difference in disparity results should be considered. Guiding Principles for Reporting Disparity Measures ++ Guiding principles for the use and application of the results of disparity measurement. Measures Related to Health Equity ++ The usefulness of a HESS score for IPFs, both in terms of provider actionability to improve health equity, and in terms of whether this information would support Care Compare website users in making informed healthcare decisions. ++ The potential for a structural measure assessing an IPF's commitment to health equity, the specific domains that should be captured, and options for reporting this data in a manner that would minimize burden. ++ Options to collect facility-level information that could be used to support the calculation of a structural measure of health equity. ++ Other options for measures that address health equity. While we will not be responding to specific comments submitted in response to this RFI in the FY 2023 IPF PPS final rule, we will actively consider all input as we develop future regulatory proposals or future subregulatory policy guidance. Any updates to specific program requirements related to quality measurement and reporting provisions would be addressed through separate and future notice-and-comment rulemaking, as necessary. VI. Collection of Information Requirements This rule proposes updates to the prospective payment rates, outlier threshold, and wage index for Medicare inpatient hospital services provided by IPFs. It also proposes to establish a default mitigation policy for providers negatively affected by changes to the IPF PPS wage index. While discussed in section IV (Comment Solicitation on Analysis of IPF PPS Adjustments) of this preamble, the active requirements and burden associated with our hospital cost report form CMS-2552-10 (OMB control number 0938-0050) are unaffected by this rule. Overall, this rule's proposed changes would not impose any new or revised “collection of information” requirements or burden as defined under 5 CFR 1320.3(c).). Consequently, this rule is not subject to the requirements of the Paperwork Reduction Act of 1995 (44 U.S.C. 3501 
                    *et seq.*). 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 2023 (October 1, 2022 through September 30, 2023). We are proposing to apply the 2016-based IPF market basket increase of 3.1 percent, less the productivity adjustment of 0.4 percentage point as required by 1886(s)(2)(A)(i) of the Act for a proposed total FY 2023 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, and update the IPF wage index to reflect the FY 2023 hospital inpatient wage index. Lastly, for FY 2023 and subsequent years, we are proposing to apply a 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, regardless of the circumstances causing the decline. B. Overall Impact We have examined the impacts of this rule as required by Executive Order 12866 on Regulatory Planning and Review (September 30, 1993), Executive Order 13563 on Improving Regulation and Regulatory Review (January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, section 202 of the Unfunded Mandates Reform Act of 1995 (March 22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4, 1999), and the Congressional Review Act (5 U.S.C. 804(2)) Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). Section 3(f) of Executive Order 12866 defines a “significant regulatory action” as an action that is likely to 
                    ( print page 19438)
                    result in a rule: (1) Having an annual effect on the economy of $100 million or more in any 1 year, or adversely and materially affecting a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or state, local or tribal governments or communities (also referred to as “economically significant”); (2) creating a serious inconsistency or otherwise interfering with an action taken or planned by another agency; (3) materially altering the budgetary impacts of entitlement grants, user fees, or loan programs or the rights and obligations of recipients thereof; or (4) raising novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in the Executive Order. 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 major rules with significant regulatory action/s and/or with economically significant effects ($100 million or more in any 1 year). We estimate that the total impact of these changes for FY 2023 payments compared to FY 2022 payments will be a net increase of approximately $50 million. This reflects a $90 million increase from the update to the payment rates (+$105 million from the 4th quarter 2021 IGI forecast of the 2016-based IPF market basket of 3.1 percent, and -$15 million for the productivity adjustment of 0.4 percentage point), as well as a $40 million decrease as a result of the update to the outlier threshold amount. Outlier payments are estimated to change from 3.2 percent in FY 2022 to 2.0 percent of total estimated IPF payments in FY 2023. Based on our estimates, OMB's Office of Information and Regulatory Affairs has determined this rulemaking is “economically significant” as measured by the $100 million threshold. Accordingly, 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 November 2004 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 of this proposed rule, we are proposing to update the wage index and labor-related share, as well as apply the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, 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. Therefore, the budgetary impact to the Medicare program of this proposed rule will be due to the market basket update for FY 2023 of 3.1 percent (see section III.A.2 of this proposed rule) less 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 2023 impact will be a net increase of $50 million in payments to IPF providers. This reflects an estimated $90 million increase from the update to the payment rates and a $40 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 2023. 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 2023 versus those under FY 2022. We determined the percent change in the estimated FY 2023 IPF PPS payments compared to the estimated FY 2022 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 updated wage index data including the proposed labor-related share and the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year; and the proposed market basket update for FY 2023, 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 2023 changes in this proposed rule, our analysis begins with FY 2021 IPF PPS claims (based on the 2021 MedPAR claims, December 2021 update). As discussed in section III.E.2 of this proposed rule, we also proposed to exclude providers from our impact simulations whose change in estimated cost per day is outside 3 standard deviations from the mean. We estimate FY 2022 IPF PPS payments using these 2021 claims, the finalized FY 2022 IPF PPS Federal per diem base rates, and the finalized FY 2022 IPF PPS patient and facility level adjustment factors (as published in the FY 2022 IPF PPS final rule (86 FR 42608)). We then estimate the FY 2022 outlier payments based on these simulated FY 2022 IPF PPS payments using the same methodology as finalized in the FY 2022 IPF PPS final rule (86 FR 42623 through 42624) where total outlier payments are maintained at 2 percent of total estimated FY 2022 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 FY 2023 IPF wage index, the proposed 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year, and the proposed FY 2023 labor-related share.
                The proposed market basket update for FY 2023 of 3.1 percent less 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 3 illustrates the percent change in payments from FY 2022 (that is, October 1, 2022, to September 30, 2022) to FY 2023 (that is, October 1, 2022, to September 30, 2023) including all the proposed payment policy changes.
                    ( print page 19439) Table 3—FY 2023 IPF PPS Proposed Payment Impacts
Facility by type
Number of 
                             facilities
Outlier
FY 2023 
                             wage index  
                             (with cap)  
                             and LRS
Total percent change 1(1)
(2)
(3)
(4)
(5)All Facilities
1,418
−1.2
0.0
1.5Total Urban
1,148
−1.3
0.0
1.4Urban unit
677
−1.9
0.0
0.7Urban hospital
471
−0.4
0.1
2.4Total Rural
270
−0.8
−0.2
1.7Rural unit
213
−0.9
−0.2
1.6Rural hospital
57
−0.4
−0.3
2.0By Type of Ownership:Freestanding IPFs:Urban Psychiatric Hospitals:Government
119
−1.8
0.1
0.9Non-Profit
88
−0.7
0.3
2.3For-Profit
264
−0.1
0.0
2.7Rural Psychiatric Hospitals:Government
30
−0.7
−0.3
1.7Non-Profit
12
−1.5
−0.1
1.1For-Profit
15
−0.1
−0.3
2.3IPF Units:Urban:Government
92
−2.4
0.0
0.3Non-Profit
450
−2.2
−0.1
0.4For-Profit
135
−1.0
0.1
1.8Rural:Government
48
−0.8
0.0
1.9Non-Profit
123
−0.9
−0.2
1.5For-Profit
42
−1.0
−0.2
1.4By Teaching Status:Non-teaching
1,234
−0.9
0.1
1.8Less than 10% interns and residents to beds
99
−1.6
−0.2
0.810% to 30% interns and residents to beds
61
−2.9
−0.4
−0.7More than 30% interns and residents to beds
24
−3.7
0.2
−0.9By Region:New England
102
−1.8
−0.5
0.4Mid-Atlantic
181
−1.6
−0.1
1.0South Atlantic
219
−0.7
−0.1
1.9East North Central
233
−1.0
−0.2
1.4East South Central
143
−1.0
−0.3
1.4West North Central
102
−1.7
−0.3
0.7West South Central
211
−0.5
0.3
2.5Mountain
99
−0.7
0.1
2.0Pacific
128
−1.7
0.9
1.8By Bed Size:Psychiatric Hospitals:Beds: 0-24
82
−0.5
0.2
2.4Beds: 25-49
73
−0.1
0.1
2.7Beds: 50-75
78
−0.1
−0.1
2.5Beds: 76 +
295
−0.5
0.1
2.2Psychiatric Units:Beds: 0-24
486
−1.5
0.0
1.2Beds: 25-49
240
−1.7
−0.1
0.9Beds: 50-75
100
−2.2
−0.1
0.3Beds: 76 +
64
−2.1
−0.1
0.51
                         This column includes the impact of the updates in columns (3) through (5) above, and of the proposed IPF market basket update factor for FY 2023 (3.1 percent), reduced by 0.4 percentage point for the proposed productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act.
 3. Impact Results Table 3 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 1,418 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 2021, and were not excluded due to the proposed trim on providers whose change in estimated cost per day is outside 3 standard deviations from the mean.
                    ( print page 19440) 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 3.2 percent in FY 2022. Therefore, we propose to adjust the outlier threshold amount to set total estimated outlier payments equal to 2.0 percent of total payments in FY 2023. The estimated change in total IPF payments for FY 2023, therefore, includes an approximate 1.2 percent decrease in payments because we would expect the outlier portion of total payments to decrease from approximately 3.2 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 3), across all hospital groups, is a 1.2 percent decrease. The largest decrease in payments due to this change is estimated to be 3.7 percent for teaching IPFs with more than 30 percent interns and residents to beds. In column 4, we present the effects of the proposed budget-neutral update to the IPF wage index, the proposed Labor-Related Share (LRS), and the 5-percent cap on any decrease to a provider's wage index from its wage index in the prior year discussed in section III.D.2 of this proposed rule. This 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 2022 IPF wage index to the proposed FY 2023 IPF wage index, which includes basing the FY 2023 IPF wage index on the FY 2023 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 77.2 percent in FY 2022 to 77.4 percent in FY 2023. We note that there is no projected change in aggregate payments to IPFs, as indicated in the first row of column 4; however, there would be distributional effects among different categories of IPFs. For example, we estimate the largest increase in payments to be 0.9 percent for Pacific IPFs, and the largest decrease in payments to be 0.5 percent for New England IPFs. IPF payments are therefore estimated to increase by 1.4 percent in urban areas and 1.7 percent in rural areas. Overall, IPFs are estimated to experience a net increase in payments as a result of the updates in this proposed rule. The largest payment increases are estimated at 2.7 percent for freestanding urban for-profit IPFs and IPF hospitals with 25-49 beds. 4. Effect on Beneficiaries Under the FY 2023 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 proposed 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 2023 IPF PPS will enhance the efficiency of the Medicare program. 5. 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 2023 IPF PPS proposed rule, the most recent IPF proposed rule was the FY 2022 IPF PPS proposed rule, and we received 898 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 2022 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, 2020 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 $114.24 per hour, including overhead and fringe benefits 
                    *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 50 minutes (0.833 hours) for the staff to review half of this proposed rule, which contains a total of approximately 25,000 words. For each IPF that reviews the proposed rule, the estimated cost is (0.833 × $114.24) or $95.16. Therefore, we estimate that the total cost of reviewing this proposed rule is $85,453.68 ($95.16 × 898 reviewers). D. Alternatives Considered The statute does not specify an update strategy for the IPF PPS and is broadly written to give the Secretary discretion in establishing an update methodology. 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 November 2004 IPF PPS final rule; apply the proposed 2016-based IPF PPS market basket update for FY 2023 of 3.1 percent, reduced by the statutorily required proposed productivity adjustment of 0.4 percentage point along with the proposed wage index budget neutrality adjustment to update the payment rates; and use a FY 2023 IPF wage index which uses the FY 2023 pre-floor, pre-reclassified IPPS hospital wage index as its basis. Additionally, we are proposing to 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 for FY 2023 to exclude providers from our simulation of IPF PPS payments for FY 2022 and FY 2023 if their change in estimated cost per day is outside 3 standard deviations from the mean. 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 4, 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 4 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 1,418 IPFs with data available in the PSF, with claims in our FY 2021 MedPAR claims dataset, and which were not excluded due to the proposed trim on providers whose change in 
                    ( print page 19441)
                    estimated cost per day is outside 3 standard deviations from the mean. Lastly, Table 4 also includes our best estimate of the costs of reviewing and understanding this proposed rule. Table 4—Accounting Statement: Classification of Estimated Costs, Savings, and Transfers
Category
Primary 
                             estimate  
                             ($million/year)
Low 
                             estimate
High 
                             estimate
UnitsYear 
                             dollars
Discount 
                             rate
Period 
                             coveredRegulatory Review Costs
0.07


2020

FY 2023Annualized Monetized Transfers from Federal Government to IPF Medicare Providers
50


FY 2023

FY 2023
 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. Most IPFs and most other providers and suppliers are small entities, either by nonprofit status or having revenues of $8 million to $41.5 million or less in any 1 year. Individuals and states are not included in the definition of a small entity. 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 3, we estimate that the overall revenue impact of this proposed rule on all IPFs is to increase estimated Medicare payments by approximately 1.5 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 213 rural excluded psychiatric units and 57 rural psychiatric hospitals in our database of 1,418 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 2022, that threshold is approximately $165 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 $165 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. Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & Medicaid Services, approved this document on March 24, 2022. List of Subjects in 42 CFR Part 412 Administrative practice and procedure
Health facilities
Medicare
Puerto Rico
Reporting and recordkeeping requirements
 For the reasons set forth in the preamble, the Centers for Medicare & Medicaid Services proposes to amend 42 CFR part 412 as set forth below: PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES
 1.The authority citation for part 412 continues to read as follows: Authority:
                    42 U.S.C. 1302 and 1395hh. 2.Section 412.424 is amended by revising paragraph (d)(1)(i) to read as follows: § 412.424
  
 (d) * * * (1) * * * (i) 
                        *Adjustment for wages.*
                         CMS adjusts the labor portion of the Federal per diem base rate to account for geographic differences in the area wage levels using an appropriate wage index. (A) The application of the wage index is made on the basis of the location of the inpatient psychiatric facility in an urban or rural area as defined in § 412.402. (B) Beginning October 1, 2022, CMS applies a cap on decreases to the wage index, such that the wage index applied to an inpatient psychiatric facility is not less than 95 percent of the wage index applied to that inpatient psychiatric facility in the prior fiscal year.
 Dated: March 29, 2022. Xavier Becerra, Secretary, Department of Health and Human Services.


# Footnotes

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BILLING CODE 4120-01-P BILLING CODE 4120-01-C [FR Doc. 2022-06906 Filed 3-31-22; 4:15 pm]