Medicare Program; FY 2022 Inpatient Psychiatric Facilities Prospective Payment System and Quality Reporting Updates for Fiscal Year Beginning October 1, 2021 (FY 2022), 19480-19529 [2021-07433]

Download as PDF 19480 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Medicare & Medicaid Services 42 CFR Part 412 [CMS–1750–P] RIN 0938–AU40 Medicare Program; FY 2022 Inpatient Psychiatric Facilities Prospective Payment System and Quality Reporting Updates for Fiscal Year Beginning October 1, 2021 (FY 2022) Centers for Medicare & Medicaid Services (CMS), HHS. ACTION: Proposed rule. AGENCY: 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 Inpatient Prospective Payment System (IPPS) hospital or critical access hospital. This rule also proposes to update and clarify the IPF teaching policy with respect to IPF hospital closures and displaced residents and proposes a technical change to the 2016based IPF market basket price proxies. In addition, this proposed rule would update quality measures and reporting requirements under the Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program. These changes would be effective for IPF discharges occurring during the Fiscal Year (FY) beginning October 1, 2021 through September 30, 2022 (FY 2022). DATES: To be assured consideration, comments must be received at one of the addresses provided below by June 7, 2021. ADDRESSES: In commenting, please refer to file code CMS–1750–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 https://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–1750–P, P.O. Box 8010, Baltimore, MD 21244–8016. jbell on DSKJLSW7X2PROD with PROPOSALS2 SUMMARY: VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 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–1750–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: https:// www.regulations.gov. Follow the search instructions on that website to view public comments. Availability of Certain Tables Exclusively Through the Internet on the CMS Website Addendum A to this proposed rule summarizes the FY 2022 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 the complete listing of ICD–10 Clinical Modification (CM) and Procedure Coding System codes underlying the Code First table, the FY 2022 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-Feefor-Service-Payment/ InpatientPsychFacilPPS/tools.html. PO 00000 Frm 00002 Fmt 4701 Sfmt 4702 Tables setting forth the FY 2022 Wage Index for Urban Areas Based on CoreBased Statistical Area (CBSA) Labor Market Areas and the FY 2022 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-ServicePayment/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 the FY 2022 beginning October 1, 2021 through September 30, 2022. This rule also proposes to update and clarify the IPF teaching policy with respect to IPF hospital closures and displaced residents and proposes a technical change to the 2016-based IPF market basket price proxies. In addition, the proposed rule would update quality measures and reporting requirements under the Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program. B. Summary of the Major Provisions 1. Inpatient Psychiatric Facilities Prospective Payment System (IPF PPS) For the IPF PPS, we are proposing to— • Update IPF PPS teaching policy with respect to IPF hospital closures and displaced residents. • Replace one of the price proxies currently used for the For-profit Interest cost category in the 2016-based IPF market basket with a similar price proxy. • Adjust the 2016-based IPF market basket update (2.3 percent) for economy-wide productivity (0.2 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 2.1 percent for FY 2022. • Make technical rate setting changes: 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 $815.22 to $833.50. ++ The IPF PPS Federal per diem base rate for providers who failed to report quality data to $817.18. ++ The Electroconvulsive therapy (ECT) payment per treatment from $350.97 to $358.84. E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules ++ The ECT payment per treatment for providers who failed to report quality data to $351.81. ++ The labor-related share from 77.3 percent to 77.1 percent. ++ The wage index budget-neutrality factor to 1.0014. ++ The fixed dollar loss threshold amount from $14,630 to $14,030 to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF PPS payments. 2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program In this proposed rule, we are proposing to: • Adopt voluntary patient-level data reporting for data submitted for FY 2023 payment determination and mandatory patient-level data reporting for FY 2024 payment determination and subsequent years; • Adopt the Coronavirus disease 2019 (COVID–19) Healthcare Personnel (HCP) Vaccination measure for the FY 2023 payment determination and subsequent years; • Adopt the Follow-up After Psychiatric Hospitalization (FAPH) measure for the FY 2024 payment determination and subsequent years; and • Remove the following four measures for FY 2024 payment determination and subsequent years: ++ Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention Provided (SUB–2/2a) measure; ++ Tobacco Use Brief Intervention Provided or Offered and Tobacco Use Brief Intervention Provided (TOB–2/2a) measure; ++ Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure; and ++ Follow-up After Hospitalization for Mental Illness (FUH) measure. C. Summary of Impacts Provision description Total transfers & cost reductions FY 2022 IPF PPS payment update ............................. The overall economic impact of this proposed rule is an estimated $90 million in increased payments to IPFs during FY 2022. The overall economic impact of the IPFQR Program provisions of this proposed rule is an estimated $20,911,738 reduction in information collection burden. FY2023 IPFQR Program update ................................. II. Background A. Overview of the Legislative Requirements of the IPF PPS jbell on DSKJLSW7X2PROD with PROPOSALS2 19481 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 Prospective Payment System (PPS) for inpatient hospital services furnished in psychiatric hospitals and excluded psychiatric units including an adequate patient classification system that reflects the differences in patient resource use and costs among psychiatric hospitals and excluded psychiatric units. ‘‘Excluded psychiatric unit’’ means a psychiatric unit in an inpatient prospective payment system (IPPS) hospital that is excluded from the IPPS, or a psychiatric unit in a Critical Access Hospital (CAH) that is excluded from the CAH payment system. These excluded psychiatric units would 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 VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 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. As noted in our FY 2020 IPF PPS final rule with comment period, published in the Federal Register on August 6, 2019 (84 FR 38424 through 38482), for the RY beginning in 2019, the productivity adjustment currently in place was equal to 0.4 percentage point. 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 the statute required the application of this adjustment. Because FY 2021, was a RY beginning in 2020, FY 2021 was PO 00000 Frm 00003 Fmt 4701 Sfmt 4702 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 take into account such reduction in computing the payment amount for a subsequent RY. More 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 Fiscal Year 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 Center for Medicare & Medicaid (CMS) website at https://www.cms.gov/ Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ index.html?redirect=/ InpatientPsychFacilPPS/. E:\FR\FM\13APP2.SGM 13APP2 19482 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 B. Overview of the IPF PPS The November 2004 IPF PPS final rule (69 FR 66922) 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; additionally, there are 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-ofliving 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 VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 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 18month 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. In November 2004, we implemented the IPF PPS in a final rule that published on November 15, 2004 in the Federal Register (69 FR 66922). In developing the IPF PPS, and to ensure that the IPF PPS is able to 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 15, 2004 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 PO 00000 Frm 00004 Fmt 4701 Sfmt 4702 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 1. When proposing changes in IPF payment policy, a proposed rule would be issued in the spring, and the final rule in the summer to be effective on October 1. 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, 2020 in the Federal Register titled, ‘‘Medicare Program; FY 2021 Inpatient Psychiatric Facilities Prospective Payment System and Special Requirements for Psychiatric Hospitals for Fiscal Year Beginning October 1, 2020 (FY 2021)’’ (85 FR 47042), which updated the IPF PPS payment rates for FY 2021. That final rule updated the IPF PPS Federal per diem base rates that were published in the FY 2020 IPF PPS Rate Update final rule (84 FR 38424) in accordance with our established policies. III. Provisions of the FY 2022 IPF PPS Proposed Rule A. Proposed Update to the FY 2021 Market Basket 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 2016based IPF market basket, using Medicare cost report data for both Medicare participating freestanding psychiatric hospitals and psychiatric units. We refer E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 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). jbell on DSKJLSW7X2PROD with PROPOSALS2 2. Proposed FY 2022 IPF Market Basket Update For FY 2022 (beginning October 1, 2021 and ending September 30, 2022), we are proposing to use an estimate of the 2016-based IPF market basket increase factor to update the IPF PPS base payment rate. Consistent with historical practice, we are proposing to estimate the market basket update for the IPF PPS based on IHS Global Inc.’s (IGI) forecast (see section III.A.3 of this proposed rule for a discussion of a proposed technical update to one price proxy that is part of the 2016-based IPF market basket). IGI is a nationally recognized economic and financial forecasting firm that contracts with the CMS to forecast the components of the market baskets and multifactor productivity (MFP). For the proposed rule, based on IGI’s fourth quarter 2020 forecast with historical data through the third quarter of 2020, the 2016-based IPF market basket increase factor for FY 2022 is 2.3 percent. Therefore, we are proposing that the 2016-based IPF market basket update for FY 2022 would be 2.3 percent. 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 2022 IPF PPS proposed rule, based on IGI’s fourth quarter 2020 forecast, the proposed MFP adjustment for FY 2022 (the 10-year moving average of MFP for the period ending FY 2022) is projected to be 0.2 percent. We are proposing to reduce the proposed 2.3 percent IPF market basket update by this 0.2 percentage point productivity adjustment, as mandated by the Act. This results in a proposed estimated FY 2022 IPF PPS payment rate update of 2.1 percent (2.3 ¥ 0.2 = 2.1). We are also proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2022 IPF market basket update and MFP adjustment for the final rule. For more information on the productivity adjustment, we refer readers to the discussion in the FY 2016 IPF PPS final rule (80 FR 46675). VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 3. Proposed Update to IPF Market Basket Price Proxies As discussed in section III.A.1. of this proposed rule, the IPF market basket is an input price index that consists of cost category weights and price proxies derived from the mix of goods and services used in providing health care. For FY 2022, for the For-profit Interest cost category of the 2016-based IPF market basket, we are proposing to use the iBoxx AAA Corporate Bond Yield index instead of the Moody’s AAA Corporate Bond Yield index. Effective for December 2020, the Moody’s AAA Corporate Bond series is no longer available for use under license to IGI, which is the nationally-recognized economic and financial forecasting firm with which we contract to forecast the components of the market baskets and MFP. We compared the iBoxx AAA Corporate Bond Yield index with the Moody’s AAA Corporate Bond Yield index and found that the average growth rates in the history of the two series are very similar. Over the historical time period of FY 2001 to FY 2020, the 4quarter percent change moving average growth in the iBoxx series was approximately 0.1 percentage point higher, on average, than the Moody’s series. However, given the relatively small weight for this cost category, replacing the Moody’s series with the iBoxx series would not impact the historical top-line market basket increases when rounded to the nearest tenth of a percentage point over the past 10 fiscal years (FY 2011 to FY 2020). Therefore, because the iBoxx AAA Corporate Bond Yield index captures the same technical concept as the current corporate bond proxy and tracks similarly to the current measure that is no longer available, we believe that using the iBoxx AAA Corporate Bond Yield index is technically appropriate to use in the 2016-based IPF market basket. 4. Proposed FY 2022 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- PO 00000 Frm 00005 Fmt 4701 Sfmt 4702 19483 intensive and vary with the local labor market. Based on our definition of the laborrelated 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; All Other: Labor-related Services; and a portion of the CapitalRelated cost weight (46 percent) from the 2016-based IPF market basket. The relative importance reflects the different rates of price change for these cost categories between the base year (FY 2016) and FY 2022. Using IGI’s fourth quarter 2020 forecast for the 2016-based IPF market basket, the proposed IPF labor-related share for FY 2022 is the sum of the FY 2022 relative importance of each labor-related cost category. 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). For FY 2022, the proposed labor-related share based on IGI’s fourth quarter 2020 forecast of the 2016-based IPF PPS market basket is 77.1 percent. We are also proposing that if more recent data become available, we would use such data, if appropriate, to determine the FY 2022 labor-related share for the final rule. B. Proposed Updates to the IPF PPS Rates for FY Beginning October 1, 2021 The IPF PPS is based on a standardized Federal per diem base rate calculated from the IPF average per diem costs and adjusted for budgetneutrality 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- E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 19484 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 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 budgetneutrality 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. In addition, 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-ServicePayment/InpatientPsychFacilPPS/ index.html. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 IPFs must include a valid procedure code for ECT services provided to IPF beneficiaries in order to bill for ECT services, as described in our Medicare Claims Processing Manual, Chapter 3, Section 190.7.3 (available at https:// www.cms.gov/Regulations-andGuidance/Guidance/Manuals/ Downloads/clm104c03.pdf.) There were no changes to the ECT procedure codes used on IPF claims as a result of the proposed update to the ICD–10–PCS code set for FY 2022. Addendum B to this proposed rule shows the ECT procedure codes for FY 2022 and is available on our website at https:// www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ InpatientPsychFacilPPS/tools.html. 2. Proposed Update of the Federal per Diem Base Rate and Electroconvulsive Therapy Payment per Treatment The current (FY 2021) Federal per diem base rate is $815.22 and the ECT payment per treatment is $350.97. For the proposed FY 2022 Federal per diem base rate, we applied the payment rate update of 2.1 percent—that is, the 2016based IPF market basket increase for FY 2022 of 2.3 percent less the productivity adjustment of 0.2 percentage point—and the wage index budget-neutrality factor of 1.0014 (as discussed in section III.D.1 of this proposed rule) to the FY 2021 Federal per diem base rate of $815.22, yielding a proposed Federal per diem base rate of $833.50 for FY 2022. Similarly, we applied the 2.1 percent payment rate update and the 1.0014 wage index budget-neutrality factor to the FY 2021 ECT payment per treatment of $350.97, yielding a proposed ECT payment per treatment of $358.84 for FY 2022. 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 requirements under the IPFQR Program, we applied a 0.1 percent payment rate update—that is, the IPF market basket increase for FY 2022 of 2.3 percent less the productivity adjustment of 0.2 percentage point for an update of 2.1 percent, and further reduced by 2 percentage points in accordance with section 1886(s)(4)(A)(i) of the Act—and the wage index budgetneutrality factor of 1.0014 to the FY 2021 Federal per diem base rate of PO 00000 Frm 00006 Fmt 4701 Sfmt 4702 $815.22, yielding a Federal per diem base rate of $817.18 for FY 2022. • For IPFs that fail to meet requirements under the IPFQR Program, we applied the 0.1 percent annual payment rate update and the 1.0014 wage index budget-neutrality factor to the FY 2021 ECT payment per treatment of $350.97, yielding an ECT payment per treatment of $351.81 for FY 2022. 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 continue to use the existing regression-derived adjustment factors established in 2005 for FY 2022. 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 patientlevel 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 E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 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 2022, we are not proposing any changes to the 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-ConversionProject.html. For FY 2022, 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-ServicePayment/InpatientPsychFacilPPS/ tools.html. Psychiatric principal diagnoses that do not group to one of the 17 designated MS–DRGs would still receive the Federal per diem base rate and all other applicable adjustments, but the payment would not include an MS–DRG adjustment. The diagnoses for each IPF MS–DRG would be updated as of October 1, 2021, using the final IPPS FY 2022 ICD–10– CM/PCS code sets. The FY 2022 IPPS proposed rule includes tables of the proposed changes to the ICD–10–CM/ PCS code sets, which underlie the FY 2022 IPF MS–DRGs. Both the FY 2022 IPPS proposed rule and the tables of VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 proposed changes to the ICD–10–CM/ PCS code sets, which underlie the FY 2022 MS–DRGs are available on the IPPS website at https://www.cms.gov/ Medicare/Medicare-Fee-for-ServicePayment/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, the ICD–10–CM has a coding convention that requires the underlying condition be sequenced first followed by the manifestation. Wherever such a combination exists, there is a ‘‘use additional code’’ note at the etiology code, and a ‘‘code first’’ note at the manifestation code. These instructional notes indicate the proper sequencing order of the codes (etiology followed by manifestation). In accordance with the ICD–10–CM Official Guidelines for Coding and Reporting, when a primary (psychiatric) diagnosis code has a ‘‘code first’’ note, the provider would follow the instructions in the ICD–10–CM text. The submitted claim goes through the CMS processing system, which will identify the primary diagnosis code as nonpsychiatric 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 our 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 2018, FY 2019 and FY 2020, there were no changes to the final ICD–10–CM/PCS codes in the IPF Code First table. For FY 2021, there were 18 ICD–10–PCS codes deleted from the final IPF Code First table. For FY 2022 there are 18 codes proposed for deletion from the ICD–10–CM/PCS codes in the IPF Code First table. The proposed FY 2022 Code First table is shown in Addendum B on our website at https:// www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ InpatientPsychFacilPPS/tools.html. PO 00000 Frm 00007 Fmt 4701 Sfmt 4702 19485 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 E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 19486 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules converted to ICD–10–CM/PCS in our FY 2015 IPF PPS final rule (79 FR 45947 through 45955). The goal for converting the comorbidity categories is referred to as replication, meaning that the payment adjustment for a given patient encounter is the same after ICD–10–CM implementation as it would be if the same record had been coded in ICD–9– CM and submitted prior to ICD–10–CM/ PCS implementation on October 1, 2015. All conversion efforts were made with the intent of achieving this goal. For FY 2022, we are proposing to continue to use the same comorbidity adjustment factors in effect in FY 2021, which are found in Addendum A, available on our website at https:// www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/InpatientPsych FacilPPS/tools.html. We have updated the ICD–10–CM/ PCS codes, which are associated with the existing IPF PPS comorbidity categories, based upon the proposed FY 2022 update to the ICD–10–CM/PCS code set. The proposed FY 2022 ICD– 10–CM/PCS updates include: 8 ICD–10– CM diagnosis codes added to the Poisoning comorbidity category, 4 codes deleted, and 4 changes to Poisoning comorbidity long descriptions; 2 ICD– 10–CM diagnosis codes added to the Developmental Disabilities comorbidity category and 1 code deleted; and 3 ICD– 10–PCS codes added to the Oncology Procedures comorbidity category. In addition, we are proposing to delete 18 ICD–10–PCS codes from the Code First Table. These updates are detailed in Addenda B of this proposed rule, which are available on our website at https:// www.cms.gov/Medicare/Medicare-Feefor-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 2022 ICD–10–CM codes to remove codes that were site ‘‘unspecified’’ in terms of laterality from the FY 2022 ICD–10–CM/PCS codes in instances where more specific codes are available. As we stated in the FY 2015 IPF PPS final rule, we believe that specific diagnosis codes that narrowly identify anatomical sites where disease, injury, or a condition exists should be used when coding patients’ diagnoses whenever these codes are available. We finalized in the FY 2015 IPF PPS rule, that we would remove site ‘‘unspecified’’ codes from the IPF PPS ICD–10–CM/PCS codes in instances when laterality codes (site specified codes) are available, as the clinician should be able to identify a more specific diagnosis based on clinical assessment at the medical encounter. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 None of the proposed additions to the FY 2022 ICD–10–CM/PCS codes were site ‘‘unspecified’’ by laterality, therefore, we are not removing any of the new codes. appears in the November 2004 IPF PPS final rule (69 FR 66946). 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 2022, we are proposing to continue to use the patient age adjustments currently in effect in FY 2021, as shown in Addendum A of this rule (see https://www.cms.gov/ Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ tools.html). 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. 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 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 rule. For FY 2022, we are proposing to continue to use the variable per diem adjustment factors currently in effect, as shown in Addendum A of this rule (available at https://www.cms.gov/ Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ tools.html). A complete discussion of the variable per diem adjustments PO 00000 Frm 00008 Fmt 4701 Sfmt 4702 D. Proposed Updates to the IPF PPS Facility-Level Adjustments 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 15, 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, prereclassified 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 IPFspecific 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 taking into account 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. E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules When the IPF PPS was implemented in the November 15, 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 prefloor, 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, prereclassified 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 prefloor, 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, prereclassified 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 would be based on the FY 2020 prefloor, pre-reclassified IPPS hospital wage index rather than on the FY 2019 pre-floor, pre-reclassified IPPS hospital wage index. We explained in the FY 2020 proposed rule (84 FR 16973), that using the concurrent pre-floor, pre-reclassified VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 IPPS hospital wage index would result in the most up-to-date wage data being the basis for the IPF wage index. It would also result in more consistency and parity in the wage index methodology used by other Medicare payment systems. The Medicare SNF PPS already used the concurrent IPPS hospital wage index data as the basis for the SNF PPS wage index. Thus, the wage adjusted Medicare payments of various provider types would be based upon wage index data from the same timeframe. CMS proposed 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. For FY 2022, we are proposing to continue to use the concurrent pre-floor, pre-reclassified IPPS hospital wage index as the basis for the IPF wage index. We would apply the IPF wage index adjustment to the labor-related share of the national base rate and ECT payment per treatment. The labor-related share of the national rate and ECT payment per treatment would change from 77.3 percent in FY 2021 to 77.1 percent in FY 2022. This percentage reflects the labor-related share of the 2016-based IPF market basket for FY 2022 (see section III.A.4 of this rule). b. Office of Management and Budget (OMB) Bulletins i. Background The wage index used for the IPF PPS is calculated using the unadjusted, prereclassified 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/informationfor-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. PO 00000 Frm 00009 Fmt 4701 Sfmt 4702 19487 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). On February 28, 2013, OMB issued OMB Bulletin No. 13–01 which established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas in the United States (U.S.) and Puerto Rico based on the 2010 Census, and provided guidance on the use of the delineations of these statistical areas using standards published in the June 28, 2010 Federal Register (75 FR 37246 through 37252). These OMB Bulletin changes were reflected in the FY 2015 pre-floor, prereclassified IPPS hospital wage index, upon which the FY 2016 IPF wage index was based. We adopted these new OMB CBSA delineations in the FY 2016 IPF wage index and subsequent IPF wage indexes. We refer readers to the FY 2016 IPF PPS final rule (80 FR 46682 through 46689) for a full discussion of our implementation of the OMB labor market area delineations beginning with the FY 2016 wage index. On July 15, 2015, OMB issued OMB Bulletin No. 15–01, which provided updates to and superseded OMB Bulletin No. 13–01 that was issued on February 28, 2013. The attachment to OMB Bulletin No. 15–01 provided detailed information on the update to statistical areas since February 28, 2013. The updates provided in OMB Bulletin No. 15–01 were based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2012 and July 1, 2013. The complete list of statistical areas incorporating these changes is provided in OMB Bulletin No. 15–01. A copy of this bulletin may be obtained at https:// E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 19488 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules www.whitehouse.gov/omb/informationfor-agencies/bulletins/. OMB Bulletin No. 15–01 established revised delineations for the Nation’s Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas. The bulletin also provided delineations of Metropolitan Divisions as well as delineations of New England City and Town Areas. As discussed in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56913), the updated labor market area definitions from OMB Bulletin 15–01 were implemented under the IPPS beginning on October 1, 2016 (FY 2017). Therefore, we implemented these revisions for the IPF PPS beginning October 1, 2017 (FY 2018), consistent with our historical practice of modeling IPF PPS adoption of the labor market area delineations after IPPS adoption of these delineations (historically the IPF wage index has been based upon the pre-floor, pre-reclassified IPPS hospital wage index from the prior year). On August 15, 2017, OMB issued OMB Bulletin No. 17–01, which provided updates to and superseded OMB Bulletin No. 15–01 that was issued on July 15, 2015. The attachments to OMB Bulletin No. 17–01 provide detailed information on the update to statistical areas since July 15, 2015, and are based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2014 and July 1, 2015. In the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), we adopted the updates set forth in OMB Bulletin No. 17–01 effective October 1, 2019, beginning with the FY 2020 IPF wage index. Given that the loss of the rural adjustment was mitigated in part by the increase in wage index value, and that only a single IPF was affected by this change, we did not believe it was necessary to transition this provider from its rural to newly urban status. We refer readers to the FY 2020 IPF PPS final rule (84 FR 38453 through 38454) for a more detailed discussion about the decision to forego a transition plan in FY 2020. On April 10, 2018, OMB issued OMB Bulletin No. 18–03, which superseded the August 15, 2017 OMB Bulletin No. 17–01, and on September 14, 2018, OMB issued, OMB Bulletin No. 18–04, which superseded the April 10, 2018 OMB Bulletin No. 18–03. These bulletins established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas, and provided guidance on the use of the delineations of these statistical areas. A copy of OMB Bulletin No. 18–04 may be VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 obtained at https:// www.whitehouse.gov/wp-content/ uploads/2018/09/Bulletin-18-04.pdf. In the FY 2021 IPF PPS final rule (85 FR 47051 through 47059), we adopted the updates set forth in OMB Bulletin No. 18–04 effective October 1, 2020, beginning with the FY 2021 IPF wage index. These updates included material changes to the OMB statistical area delineations which included 34 urban counties that became rural, 47 rural counties that became urban, and 19 counties that moved to a new or modified CBSA. Given the scope of changes involved in adopting the CBSA delineations for FY 2021, we finalized a 2-year transition policy 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/wpcontent/uploads/2020/03/Bulletin-2001.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, 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 are not proposing to adopt OMB Bulletin 20–01. ii. 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 PO 00000 Frm 00010 Fmt 4701 Sfmt 4702 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 the reader 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 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 2022, we are proposing 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). d. 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 2022, we are proposing to continue to apply a budgetneutrality 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 2022 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 2022 update to the wage indexes (based on the FY 2018 hospital cost report data) and the labor-related share in a budget-neutral manner: Step 1: Simulate estimated IPF PPS payments, using the FY 2021 IPF wage index values (available on the CMS website) and labor-related share (as published in the FY 2021 IPF PPS final rule (85 FR 47043). Step 2: Simulate estimated IPF PPS payments using the proposed FY 2022 IPF wage index values (available on the CMS website) and proposed FY 2022 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 FY E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 2022 budget-neutral wage adjustment factor of 1.0014. Step 4: Apply the FY 2022 budgetneutral wage adjustment factor from step 3 to the FY 2021 IPF PPS Federal per diem base rate after the application of the market basket update described in section III.A of this rule, to determine the FY 2022 IPF PPS Federal per diem base rate. 2. Proposed Teaching Adjustment jbell on DSKJLSW7X2PROD with PROPOSALS2 a. Background In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(1)(iii) to establish a facilitylevel 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). Medicare makes direct GME payments (for direct costs such as resident and teaching physician salaries, and other direct teaching costs) to all teaching hospitals including those paid under a PPS, and those paid under the TEFRA rate-of-increase limits. These direct GME payments are made separately from payments for hospital operating costs and are not part of the IPF PPS. The direct GME payments do not address the estimated higher indirect operating costs teaching hospitals may face. The results of the regression analysis of FY 2002 IPF data established the basis for the payment adjustments included in the 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 0.5150 power to result in the teaching adjustment. This formula is subject to the limitations on the number of FTE residents, which are described in this section of this 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 VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 that teaching IPFs may count for the purpose of calculating the IPF PPS teaching adjustment, not the number of residents teaching institutions can hire or train. We calculated the number of FTE residents that trained in the IPF during a ‘‘base year’’ and used that FTE resident number as the cap. An IPF’s FTE resident cap is ultimately determined based on the final settlement of the IPF’s most recent cost report filed before November 15, 2004 (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 section III.D.2.b of this proposed rule, we discuss proposed updates to the IPF policy on temporary adjustment to the FTE cap. 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 2022 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. b. Proposed Update to IPF Teaching Policy on IPF Program Closures and Displaced Residents For FY 2022, we are proposing to change the IPF policy regarding displaced residents from IPF closures and closures of IPF teaching programs. Specifically, we are proposing to adopt conforming changes to the IPF PPS teaching policy to align with the policy changes that the IPPS finalized in the FY 2021 IPPS final rule (85 FR 58865 through 58870). We believe that the IPF IME policy relating to hospital closure and displaced students is susceptible to the same vulnerabilities as IPPS GME policy. Hence, if an IPF with a large PO 00000 Frm 00011 Fmt 4701 Sfmt 4702 19489 number of residents training in its residency program announces it is closing, these residents will become displaced and will need to find alternative positions at other IPF hospitals or risk being unable to become Board certified. Although we propose to adopt a policy under the IPF PPS that is consistent with an applicable policy under the IPPS, the actual caps under the two payment systems may not be commingled. In other words, the resident cap applicable under the IPPS is separate from the resident cap applicable under the IPF PPS; moreover, a provider cannot add its IPF resident cap to its IPPS resident cap in order to increase the number of residents it receives payment for under either payment system. Section 124 of the BBRA gives the Secretary broad discretion to determine the appropriate adjustment factors for the IPF PPS. We are proposing to implement the policy discussed in this section to remain consistent with the way that the IPPS teaching policy calculates FTE resident caps in the case of a receiving hospital that obtains a temporary IME and direct GME cap adjustment for assuming the training of displaced residents due to another hospital or residency program’s closure. We are also proposing that in the future, we would deviate from IPPS teaching policy as it pertains to counting displaced residents for the purposes of the IPF teaching adjustment only when it is necessary and appropriate for the IPF PPS. As stated in the November 2004 IPF PPS final rule (69 FR 66922), we implemented regulations at § 412.424(d)(1)(iii) to establish a facilitylevel adjustment for IPFs that are, or are part of, teaching hospitals. The facilitylevel adjustment we are providing for teaching hospitals under IPF PPS parallels the IME payments paid under the IPPS. Both payments are add on adjustments to the amount per case and both are based in part on the number of full-time equivalent (FTE) residents training at the facility. The regulation at 42 CFR 412.424(d)(1)(iii)(F) permits an IPF to temporarily adjust its FTE cap to reflect residents added because of another hospital or program’s closure. We first implemented regulations regarding residents displaced by teaching hospital and program closures in the May 6, 2011 IPF PPS final rule (76 FR 26431). In that final rule, we adopted the IPPS definition of ‘‘closure of a hospital’’ at 42 CFR 413.79(h)(1)(i) to apply to IPF closures as well, and to mean that the IPF terminates its Medicare provider agreement as specified in 42 CFR E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 19490 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 489.52. In this proposed rule, we are proposing to codify this definition, as well as the definition of an IPF program closure, at § 412.402. Although not explicitly stated in regulations text, our current policy is that a displaced resident is one that is physically present at the hospital training on the day prior to or the day of hospital or program closure. This longstanding policy derived from the fact that in the regulations text, there are requirements that the receiving hospital identifies the residents’ ‘‘who have come from the closed IPF’’ (§ 412.424(d)(1)(iii)(F)(1)(ii)) or ‘identifies the residents ‘‘who have come from another IPF’s closed program’’ (§ 412.424(d)(1)(iii)(F)(2)(i)), and that the IPF that closed its program identifies ’’ the residents who were in training at the time of the program’s closure’’ (§ 412.424(d)(1)(iii)(F)(2)(ii)). We considered the residents who were physically present at the IPF to be those residents who were ‘‘training at the time of the program’s closure,’’ thereby granting them the status of ‘‘displaced residents.’’ Although we did not want to limit the ‘‘displaced residents’’ to only those physically present at the time of closure, it becomes much more administratively challenging for the following groups of residents at closing IPFs/programs to continue their training: (1) Residents who leave the program after the closure is publicly announced to continue training at another IPF, but before the actual closure; (2) residents assigned to and training at planned rotations at other IPFs who will be unable to return to their rotations at the closing IPF or program; and (3) individuals (such as medical students or would-be fellows) who matched into resident programs at the closing IPF or program but have not yet started training at the closing IPF or program. Other groups of residents who, under current policy, are already considered ‘‘displaced residents’’ include—(1) residents who are physically training in the IPF on the day prior to or day of program or IPF closure; and (2) residents who would have been at the closing IPF or IPF program on the day prior to or of closure but were on approved leave at that time, and are unable to return to their training at the closing IPF or IPF program. We are proposing to amend the IPF policy with regard to closing teaching IPFs and closing residency programs to address the needs of residents attempting to find alternative IPFs in which to complete their training. Additionally, this proposal addresses the incentives of originating and receiving IPFs with regard to ensuring VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 we appropriately account for their indirect teaching costs by way of an appropriate IPF teaching adjustment based on each program’s resident FTEs. We are proposing to change two aspects of the current IPF policy, which are discussed in the following section. First, rather than link the status of displaced residents for the purpose of the receiving IPF’s request to increase their FTE cap to the resident’s presence at the closing IPF or program on the day prior to or the day of program or IPF closure, we propose that the ideal day would be the day that the closure was publicly announced, (for example, via a press release or a formal notice to the Accreditation Council on Graduate Medical Education (ACGME)). This would provide greater flexibility for the residents to transfer while the IPF operations or residency programs were winding down, rather than waiting until the last day of IPF or program operation. This would address the needs of the first group of residents as previously described: Residents who would leave the IPF program after the closure was publicly announced to continue training at another IPF, but before the day of actual closure. Second, by removing the link between the status of displaced residents and their presence at the closing IPF or program on the day prior to or the day of program or IPF closure, we propose to also allow the second and third group of residents who are not physically at the closing IPF/closing program, but had intended to train at (or return to training at, in the case of residents on rotation) to be considered a displaced resident. Thus, we are proposing to revise our teaching policy with regard to which residents can be considered ‘‘displaced’’ for the purpose of the receiving IPF’s request to increase their FTE cap in the situation where an IPF announces publicly that it is closing, and/or that it is closing an IPF residency program(s). Specifically, we are proposing to adopt the definitions of ‘‘closure of a hospital’’, ‘‘closure of a hospital residency training program’’, and ‘‘displaced resident’’ as defined at 42 CFR 413.79(h) but with respect to IPFs and for the purposes of accounting for indirect teaching costs. In addition, we are proposing to change another detail of the IPF teaching policy specific to the requirements for the receiving IPF. To apply for the temporary increase in the FTE resident cap, the receiving IPF would have to submit a letter to its Medicare Administrative Contractor (MAC) within 60 days of beginning the training of the displaced residents. As established under existing regulation at PO 00000 Frm 00012 Fmt 4701 Sfmt 4702 § 412.424(d)(1)(iii)(F)(1)(ii) and § 412.424(d)(1)(iii)(F)(2)(i), this letter must identify the residents who have come from the closed IPF or program and have caused the receiving IPF to exceed its cap, and must specify the length of time the adjustment is needed. Moreover, we want to propose clarifications on how the information would be delivered in this letter. Consistent with IPPS teaching policy, we are proposing that the letter from the receiving IPF would have to include: (1) The name of each displaced resident; (2) the last four digits of each displaced resident’s social security number; (3) the IPF and program in which each resident was training previously; and (4) the amount of the cap increase needed for each resident (based on how much the receiving IPF is in excess of its cap and the length of time for which the adjustments are needed). We are proposing to require the receiving hospital to only supply the last four digits of each displaced resident’s social security number to reduce the amount of personally identifiable information (PII) included in these agreements. We are also clarifying that, as we previously discussed in the May 6, 2011 IPF PPS final rule (76 FR 26455), the maximum number of FTE resident cap slots that could be transferred to all receiving IPFs is the number of FTE resident cap slots belonging to the IPF that has the closed program or that is closing. Therefore, if the originating IPF is training residents in excess of its cap, then being a displaced resident does not guarantee that a cap slot will be transferred along with that resident. Therefore, we are proposing that if there are more IPF displaced residents than available cap slots, the slots may be apportioned according to the closing IPF’s discretion. The decision to transfer a cap slot if one is available would be voluntary and made at the sole discretion of the originating IPF. However, if the originating IPF decides to do so, then it would be the originating IPF’s responsibility to determine how much of an available cap slot would go with a particular resident (if any). We also note that, as we previously discussed in the May 6, 2011 IPF PPS final rule (76 FR 25455), only to the extent a receiving IPF would exceed its FTE cap by training displaced residents would it be eligible for a temporary adjustment to its resident FTE cap. Displaced residents are factored into the receiving IPF’s ratio of resident FTEs to the facility’s average daily census. E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules October 28, 2009, and then proportionately reduced to reflect the phase-in of locality pay. The IPF PPS includes a payment When we published the proposed adjustment for IPFs located in Alaska COLA factors in the RY 2012 IPF PPS and Hawaii based upon the area in proposed rule (76 FR 4998), we which the IPF is located. As we inadvertently selected the FY 2010 explained in the November 2004 IPF COLA rates, which had been reduced to PPS final rule, the FY 2002 data account for the phase-in of locality pay. demonstrated that IPFs in Alaska and We did not intend to propose the Hawaii had per diem costs that were reduced COLA rates because that would disproportionately higher than other have understated the adjustment. Since IPFs. Other Medicare prospective the 2009 COLA rates did not reflect the payment systems (for example: The phase-in of locality pay, we finalized IPPS and LTCH PPS) adopted a COLA the FY 2009 COLA rates for RY 2010 to account for the cost differential of through RY 2014. care furnished in Alaska and Hawaii. In the FY 2013 IPPS/LTCH final rule We analyzed the effect of applying a (77 FR 53700 through 53701), we COLA to payments for IPFs located in established a new methodology to Alaska and Hawaii. The results of our update the COLA factors for Alaska and analysis demonstrated that a COLA for Hawaii, and adopted this methodology IPFs located in Alaska and Hawaii for the IPF PPS in the FY 2015 IPF final would improve payment equity for rule (79 FR 45958 through 45960). We these facilities. As a result of this adopted this new COLA methodology analysis, we provided a COLA in the for the IPF PPS because IPFs are November 2004 IPF PPS final rule. hospitals with a similar mix of A COLA for IPFs located in Alaska commodities and services. We think it and Hawaii is made by multiplying the is appropriate to have a consistent non-labor-related portion of the Federal policy approach with that of other per diem base rate by the applicable hospitals in Alaska and Hawaii. COLA factor based on the COLA area in Therefore, the IPF COLAs for FY 2015 which the IPF is located. through FY 2017 were the same as those The COLA factors through 2009 were applied under the IPPS in those years. published by the Office of Personnel As finalized in the FY 2013 IPPS/LTCH Management (OPM), and the OPM PPS final rule (77 FR 53700 and 53701), memo showing the 2009 COLA factors the COLA updates are determined every is available at https://www.chcoc.gov/ 4 years, when the IPPS market basket content/nonforeign-area-retirementlabor-related share is updated. Because equity-assurance-act. the labor-related share of the IPPS We note that the COLA areas for market basket was updated for FY 2018, Alaska are not defined by county as are the COLA factors were updated in FY the COLA areas for Hawaii. In 5 CFR 2018 IPPS/LTCH rulemaking (82 FR 591.207, the OPM established the 38529). As such, we also updated the following COLA areas: IPF PPS COLA factors for FY 2018 (82 • City of Anchorage, and 80-kilometer FR 36780 through 36782) to reflect the (50-mile) radius by road, as measured updated COLA factors finalized in the from the Federal courthouse. FY 2018 IPPS/LTCH rulemaking. • City of Fairbanks, and 80-kilometer For FY 2022, we are proposing to (50-mile) radius by road, as measured update the COLA factors published by from the Federal courthouse. OPM for 2009 (as these are the last • City of Juneau, and 80-kilometer COLA factors OPM published prior to (50-mile) radius by road, as measured transitioning from COLAs to locality from the Federal courthouse. pay) using the methodology that we • Rest of the state of Alaska. finalized in the FY 2013 IPPS/LTCH As stated in the November 2004 IPF PPS final rule and adopted for the IPF PPS final rule, we update the COLA PPS in the FY 2015 IPF final rule. factors according to updates established Specifically, we are proposing to update by the OPM. However, sections 1911 the 2009 OPM COLA factors by a through 1919 of the Non-foreign Area comparison of the growth in the Consumer Price Indices (CPIs) for the Retirement Equity Assurance Act, as contained in subtitle B of title XIX of the areas of Urban Alaska and Urban Hawaii, relative to the growth in the CPI National Defense Authorization Act for the average U.S. city as published by (NDAA) for FY 2010 (Pub. L. 111–84, October 28, 2009), transitions the Alaska the Bureau of Labor Statistics (BLS). We note that for the prior update to the and Hawaii COLAs to locality pay. COLA factors, we used the growth in the Under section 1914 of NDAA, locality CPI for Anchorage and the CPI for pay was phased in over a 3-year period Honolulu. Beginning in 2018, these beginning in January 2010, with COLA indexes were renamed to the CPI for rates frozen as of the date of enactment, jbell on DSKJLSW7X2PROD with PROPOSALS2 3. Proposed Cost of Living Adjustment for IPFs Located in Alaska and Hawaii VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 PO 00000 Frm 00013 Fmt 4701 Sfmt 4702 19491 Urban Alaska and the CPI for Urban Hawaii due to the BLS updating its sample to reflect the data from the 2010 Decennial Census on the distribution of the urban population (https:// www.bls.gov/regions/west/factsheet/ 2018cpirevisionwest.pdf, accessed January 22, 2021). The CPI for Urban Alaska area covers Anchorage and Matanuska-Susitna Borough in the State of Alaska and the CPI for Urban Hawaii covers Honolulu in the State of Hawaii. BLS notes that the indexes are considered continuous over time, regardless of name or composition changes. Because BLS publishes CPI data for only Urban Alaska and Urban Hawaii, using the methodology we finalized in the FY 2013 IPPS/LTCH PPS final rule and adopted for the IPF PPS in the FY 2015 IPF final rule, we are proposing to use the comparison of the growth in the overall CPI relative to the growth in the CPI for those areas to update the COLA factors for all areas in Alaska and Hawaii, respectively. We believe that the relative price differences between these urban areas and the U.S. (as measured by the CPIs mentioned above) are appropriate proxies for the relative price differences between the ‘‘other areas’’ of Alaska and Hawaii and the U.S. BLS publishes the CPI for All Items for Urban Alaska, Urban Hawaii, and for the average U.S. city. However, consistent with our methodology finalized in the FY 2013 IPPS/LTCH PPS final rule and adopted for the IPF PPS in the FY 2015 IPF final rule, we are proposing to create reweighted CPIs for each of the respective areas to reflect the underlying composition of the IPPS market basket nonlabor-related share. The current composition of the CPI for All Items for all of the respective areas is approximately 40 percent commodities and 60 percent services. However, the IPPS nonlabor-related share is comprised of a different mix of commodities and services. Therefore, we are proposing to create reweighted indexes for Urban Alaska, Urban Hawaii, and the average U.S. city using the respective CPI commodities index and CPI services index and proposed shares of 57 percent commodities/43 percent. We created reweighted indexes using BLS data for 2009 through 2020— the most recent data available at the time of this proposed rulemaking. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38530), we created reweighted indexes based on the 2014-based IPPS market basket (which was adopted for the FY 2018 IPPS update) and BLS data for 2009 through 2016 (the most recent BLS data at the time of the FY 2018 E:\FR\FM\13APP2.SGM 13APP2 19492 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules IPPS/LTCH PPS rulemaking), and we updated the IPF PPS COLA factors accordingly for FY 2018. We continue to believe this methodology is appropriate because we continue to make a COLA for hospitals located in Alaska and Hawaii by multiplying the nonlabor-related portion of the standardized amount by a COLA factor. We note that OPM’s COLA factors were calculated with a statutorily mandated cap of 25 percent. As stated in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38530), under the COLA update methodology we finalized in the FY 2013 IPPS/LTCH PPS final rule, we exercised our discretionary authority to adjust payments to hospitals in Alaska and Hawaii by incorporating this cap. In applying this finalized methodology for updating the COLA factors, for FY 2022, we are proposing to continue to use such a cap, as our policy is based on OPM’s COLA factors (updated by the methodology described above). Applying this methodology, the COLA factors that we are proposing to establish for FY 2022 to adjust the nonlabor-related portion of the standardized amount for IPFs located in Alaska and Hawaii are shown in the Table 1 below. For comparison purposes, we also are showing the COLA factors effective for FY 2018 through FY 2021. TABLE 1—COMPARISON OF IPF PPS COST-OF-LIVING ADJUSTMENT FACTORS: IPFS LOCATED IN ALASKA AND HAWAII FY 2018 through FY 2021 Area Alaska: City of Anchorage and 80-kilometer (50-mile) radius by road ......................................................................... City of Fairbanks and 80-kilometer (50-mile) radius by road .......................................................................... City of Juneau and 80-kilometer (50-mile) radius by road .............................................................................. Rest of Alaska .................................................................................................................................................. Hawaii: City and County of Honolulu ............................................................................................................................ County of Hawaii .............................................................................................................................................. County of Kauai ................................................................................................................................................ County of Maui and County of Kalawao .......................................................................................................... The proposed IPF PPS COLA factors for FY 2022 are also shown in Addendum A to this proposed rule, and is available at https://www.cms.gov/ Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ tools.html. jbell on DSKJLSW7X2PROD with PROPOSALS2 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 VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 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 2022, 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 PO 00000 Frm 00014 Fmt 4701 Sfmt 4702 FY 2022 through FY 2025 (proposed) 1.25 1.25 1.25 1.25 1.22 1.22 1.22 1.24 1.25 1.21 1.25 1.25 1.25 1.22 1.25 1.25 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). F. Other Proposed Payment Adjustments and Policies 1. Outlier Payment Overview The IPF PPS includes an outlier adjustment to promote access to IPF care for those patients who require expensive care and to limit the financial risk of IPFs treating unusually costly patients. In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(3)(i) to provide a percase 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 E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 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. For this proposed rulemaking, the most recent available data would be the FY 2020 claims. However, during FY 2020, the U.S. healthcare system undertook an unprecedented response to the Public Health Emergency (PHE) declared by the Health and Human Services Secretary on January 31, 2020 in response to the outbreak of respiratory disease caused by a novel (new) coronavirus that has been named ‘‘SARS CoV 2’’ and the disease it causes, which has been named ‘‘coronavirus disease 2019’’ (abbreviated ‘‘COVID–19’’). Therefore, as discussed VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 in section VI.C.3 of this proposed rule, we considered whether the most recent available year of claims, FY 2020, or the prior year, FY 2019, would be the best for estimating IPF PPS payments in FY 2021 and FY 2022. We compared the two years’ claims distributions as well as the impact results, and based on that analysis determined that the FY 2019 claims appear to be the best available data at this time. We refer the reader to section VI.C.3 of this proposed rule for a detailed discussion of that analysis. Based on an analysis of the June 2020 update of FY 2019 IPF claims and the FY 2021 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 2022 using FY 2019 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 2021. Based on an analysis of these updated data, we estimate that IPF outlier payments as a percentage of total estimated payments are approximately 1.8 percent in FY 2021. Therefore, we are proposing to update the outlier threshold amount to $14,030 to maintain estimated outlier payments at 2 percent of total estimated aggregate IPF payments for FY 2022. This proposed update is a decrease from the FY 2021 threshold of $14,630. In contrast, using the FY 2020 claims to estimate payments, the proposed outlier fixed dollar loss threshold for FY 2022 would be $19,840, an increase from the FY 2021 threshold of $14,630. We refer the reader to section VI.C.3 of this proposed rule for a detailed discussion of the estimated impacts of the proposed update to the outlier fixed dollar loss threshold, and we invite comments on this analysis. We note that our proposed use of the FY 2019 claims to set the proposed outlier fixed dollar loss threshold for FY 2022 would deviate from what has been our longstanding practice of using the most recent available year of claims, which is FY 2020 data. However, this proposal remains consistent with the established outlier update methodology. As discussed in this section and in section VI.C.3 of this proposed rule, we are proposing to update the outlier fixed dollar loss threshold based on FY 2019 IPF claims in order to maintain the appropriate outlier percentage in FY 2022. We are proposing to deviate from our longstanding practice of using the PO 00000 Frm 00015 Fmt 4701 Sfmt 4702 19493 most recent available year of claims only because and only to the extent that the COVID–19 PHE appears to have significantly impacted the FY 2020 IPF claims. As we are able to analyze more recent available IPF claims data and better understand both the short-term and long-term effects of the COVID–19 PHE on IPFs, we intend to re-assess the appropriateness of using FY 2019 IPF claims rather than FY 2020 IPF claims for the FY 2022 update. 3. Proposed Update to IPF Cost-toCharge 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-tocharge 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 2022, we are proposing 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 2022 is 2.0398 for rural IPFs, and 1.6126 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, E:\FR\FM\13APP2.SGM 13APP2 19494 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 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 2022 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 2022, to be used in each of the three situations listed previously, using the most recent CCRs entered in the CY 2021 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. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program jbell on DSKJLSW7X2PROD with PROPOSALS2 A. Background and Statutory Authority We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589) for a discussion of the background and statutory authority 1 of the IPFQR Program. 1 We note that the statute uses the term ‘‘rate year’’ (RY). However, beginning with the annual update of the inpatient psychiatric facility prospective payment system (IPF PPS) that took effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with the annual update of the ICD codes, effective on October 1 of each year. This change allowed for annual payment updates and the ICD coding update to occur on the same schedule and appear in the same Federal Register document, promoting administrative efficiency. To reflect the change to the annual payment rate update cycle, we revised the regulations at 42 CFR 412.402 to specify that, beginning October 1, 2012, the RY update period would be the 12-month period from October 1 through September 30, which we refer to as a ‘‘fiscal year’’ (FY) (76 FR 26435). Therefore, with respect to the IPFQR Program, the terms ‘‘rate year,’’ as used in the statute, and ‘‘fiscal year’’ as used in the regulation, both refer to the period from October 1 through September 30. For more information regarding this terminology change, we refer readers to section III. of the RY 2012 IPF PPS final rule (76 FR 26434 through 26435). VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 B. Covered Entities In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we established that the IPFQR Program’s quality reporting requirements cover those psychiatric hospitals and psychiatric units paid under Medicare’s IPF PPS (§ 412.404(b)). Generally, psychiatric hospitals and psychiatric units within acute care and critical access hospitals that treat Medicare patients are paid under the IPF PPS. Consistent with previous regulations, we continue to use the terms ‘‘facility’’ or IPF to refer to both inpatient psychiatric hospitals and psychiatric units. This usage follows the terminology in our IPF PPS regulations at § 412.402. For more information on covered entities, we refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645). C. Previously Finalized Measures and Administrative Procedures The current IPFQR Program includes 14 measures. For more information on these measures, we refer readers to Table 4 of this proposed rule and the following final rules: • The FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through 53652); • The FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through 50897); • The FY 2015 IPF PPS final rule (79 FR 45963 through 45975); • The FY 2016 IPF PPS final rule (80 FR 46695 through 46714); • The FY 2017 IPPS/LTCH PPS final rule (81 FR 57238 through 57247); • The FY 2019 IPF PPS final rule (83 FR 38590 through 38606); and • The FY 2020 IPF PPS final rule (84 FR 38459 through 38467). For more information on previously adopted procedural requirements, we refer readers to the following rules: • The FY 2013 IPPS/LTCH PPS final rule (77 FR 53653 through 53660); • The FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through 50903); • The FY 2015 IPF PPS final rule (79 FR 45975 through 45978); • The FY 2016 IPF PPS final rule (80 FR 46715 through 46719); • The FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 through 57249); • The FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 through 38474); • The FY 2019 IPF PPS final rule (83 FR 38606 through 38608); and • The FY 2020 IPF PPS final rule (84 FR 38467 through 38468). D. Closing the Health Equity Gap in CMS Quality Programs—Request for Information (RFI) Persistent inequities in health care outcomes exist in the U.S., including PO 00000 Frm 00016 Fmt 4701 Sfmt 4702 among Medicare patients. In recognition of persistent health disparities and the importance of closing the health equity gap, we request information on revising several CMS programs to make reporting of health disparities based on social risk factors and race and ethnicity more comprehensive and actionable for facilities, providers, and patients. The following is part of an ongoing effort across CMS to evaluate appropriate initiatives to reduce health disparities. Feedback will be used to inform the creation of a future, comprehensive, RFI focused on closing the health equity gap in CMS programs and policies. This RFI contains four parts: • Background: This section provides information describing our commitment to health equity, and existing initiatives with an emphasis on reducing health disparities. • Current CMS Disparity Methods: This section describes the methods, measures, and indicators of social risk currently used with the CMS Disparity Methods. • Future potential stratification of quality measure results: This section describes four potential future expansions of the CMS Disparity Methods, including (1) Stratification of Quality Measure Results—Dual Eligibility; (2) Stratification of Quality Measure Results—Race and Ethnicity; (3) Improving Demographic Data Collection; and (4) Potential Creation of a Facility Equity Score to Synthesize Results Across Multiple Social Risk Factors. • Solicitation of public comment: This section specifies 12 requests for feedback on the above topics. We look forward to receiving feedback on these topics, and note our intention for an additional RFI or rulemaking on this topic in the future. 1. Background Significant and persistent inequities in health care outcomes exist in the U.S. Belonging to a racial or ethnic minority group; living with a disability; being a member of the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community; living in a rural area; or being near or below the poverty level, is often associated with worse health outcomes.2 3 4 5 6 7 8 9 Such disparities in 2 Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for Medicare Beneficiaries by Race and Site of Care. JAMA. 2011;305(7):675–681. 3 Lindenauer PK, Lagu T, Rothberg MB, et al. Income Inequality and 30 Day Outcomes After Acute Myocardial Infarction, Heart Failure, and Pneumonia: Retrospective Cohort Study. British Medical Journal. 2013;346. 4 Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity of Care in U.S. Hospitals. New E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 health outcomes are the result of number of factors, but importantly for CMS programs, although not the sole determinant, poor access and provision of lower quality health care contribute to health disparities. For instance, numerous studies have shown that among Medicare beneficiaries, racial and ethnic minority individuals often receive lower quality of care, report lower experiences of care, and experience more frequent hospital readmissions and operative complications.10 11 12 13 14 15 Readmission rates for common conditions in the Hospital Readmissions Reduction Program are higher for Black Medicare beneficiaries and higher for Hispanic Medicare beneficiaries with Congestive Heart Failure and Acute Myocardial Infarction.16 17 18 19 20 Studies have also England Journal of Medicine. 2014;371(24):2298– 2308. 5 Polyakova, M., et al. Racial Disparities In Excess All-Cause Mortality During The Early COVID–19 Pandemic Varied Substantially Across States. Health Affairs. 2021; 40(2): 307–316. 6 Rural Health Research Gateway. Rural Communities: Age, Income, and Health Status. Rural Health Research Recap. November 2018. 7 https://www.minorityhealth.hhs.gov/assets/ PDF/Update_HHS_Disparities_Dept-FY2020.pdf. 8 www.cdc.gov/mmwr/volumes/70/wr/ mm7005a1.htm. 9 Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID–19 Vulnerability of Transgender Women With and Without HIV Infection in the Eastern and Southern U.S. Preprint. medRxiv. 2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/2020.07.21.20159327. 10 Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K, Burkhart, Q, Klein, DJ, Gildner, J, and Haviland, AM. Racial, Ethnic, and Gender Disparities in Health Care in Medicare Advantage. Baltimore, MD: CMS Office of Minority Health. 2020. 11 Guide to Reducing Disparities in Readmissions. CMS Office of Minority Health. Revised August 2018. Available at: https://www.cms.gov/AboutCMS/Agency-Information/OMH/Downloads/OMH_ Readmissions_Guide.pdf. 12 Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. Racial disparities in knee and hip total joint arthroplasty: An 18-year analysis of national Medicare data. Ann Rheum Dis. 2014 Dec;73(12):2107–15. 13 Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial Disparities in Readmission Rates among Patients Discharged to Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672– 1679. 14 Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for Medicare Beneficiaries by Race and Site of Care. JAMA. 2011;305(7):675–681. 15 Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day readmission rates for Medicare beneficiaries by race and site of care. Ann Surg. Jun 2014;259(6):1086–1090. 16 Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. Readmission rates for Hispanic Medicare beneficiaries with heart failure and acute myocardial infarction. Am Heart J. Aug 2011;162(2):254–261 e253. 17 Centers for Medicare and Medicaid Services. Medicare Hospital Quality Chartbook: Performance Report on Outcome Measures; 2014. 18 Guide to Reducing Disparities in Readmissions. CMS Office of Minority Health. Revised August VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 shown that African Americans are significantly more likely than white Americans to die prematurely from heart disease and stroke.21 The COVID– 19 pandemic has further illustrated many of these longstanding health inequities with higher rates of infection, hospitalization, and mortality among Black, Latino, and Indigenous and Native American persons relative to White persons.22 23 As noted by the Centers for Disease Control ‘‘longstanding systemic health and social inequities have put many people from racial and ethnic minority groups at increased risk of getting sick and dying from COVID–19.’’ 24 One important strategy for addressing these important inequities is improving data collection to allow for better measurement and reporting on equity across our programs and policies. We are committed to achieving equity in health care outcomes for our beneficiaries by supporting providers in quality improvement activities to reduce health inequities, enabling them to make more informed decisions, and promoting provider accountability for health care disparities.25 For the purposes of this proposed rule, we are using a definition of equity established in Executive Order 13985, as ‘‘the consistent and systematic fair, just, and impartial treatment of all individuals, including individuals who belong to underserved communities that have been denied such treatment, such as Black, Latino, and Indigenous and Native American persons, Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; lesbian, gay, bisexual, transgender, and queer 2018. Available at: https://www.cms.gov/AboutCMS/Agency-Information/OMH/Downloads/OMH_ Readmissions_Guide.pdf. 19 Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. Chronic obstructive pulmonary disease readmissions at minority-serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680–684. 20 Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for Medicare Beneficiaries by Race and Site of Care. JAMA. 2011;305(7):675–681. 21 HHS. Heart disease and African Americans. (March 29, 2021). https:// www.minorityhealth.hhs.gov/omh/ browse.aspx?lvl=4&lvlid=19. 22 https://www.cms.gov/files/document/medicarecovid-19-data-snapshot-fact-sheet.pdf. 23 Ochieng N, Cubanski J, Neuman T, Artiga S, and Damico A. Racial and Ethnic Health Inequities and Medicare. Kaiser Family Foundation. Februray 2021. Available at: https://www.kff.org/medicare/ report/racial-and-ethnic-health-inequities-andmedicare/. 24 https://www.cdc.gov/coronavirus/2019-ncov/ community/health-equity/race-ethnicity.html. 25 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/ QualityInitiativesGenInfo/Downloads/CMS-QualityStrategy.pdf. PO 00000 Frm 00017 Fmt 4701 Sfmt 4702 19495 (LGBTQ+) persons; persons with disabilities; persons who live in rural areas; and persons otherwise adversely affected by persistent poverty or inequality.’’ 26 We note that this definition was recently established by the current administration, and provides a useful, common definition for equity across different areas of government, although numerous other definitions of equity exist. Our ongoing commitment to closing the equity gap in CMS quality programs is demonstrated by a portfolio of programs aimed at making information on the quality of health care providers and services, including disparities, more transparent to consumers and providers. The CMS Equity Plan for Improving Quality in Medicare outlines a path to equity which aims to support Quality Improvement Networks and Quality Improvement Organizations (QIN– QIOs); Federal, state, local, and tribal organizations; providers; researchers; policymakers; beneficiaries and their families; and other stakeholders in activities to achieve health equity.27 The CMS Equity Plan for Improving Quality in Medicare focuses on three core priority areas which inform our policies and programs: (1) Increasing understanding and awareness of health disparities; (2) developing and disseminating solutions to achieve health equity; and (3) implementing sustainable actions to achieve health equity.28 The CMS Quality Strategy 29 and Meaningful Measures Framework 30 include elimination of racial and ethnic disparities as a central principle. Our efforts aimed at closing the health equity gap to date have included both providing transparency about health disparities, supporting providers with evidence-informed solutions to achieve health equity, and reporting to providers 26 https://www.federalregister.gov/documents/ 2021/01/25/2021-01753/advancing-racial-equityand-support-for-underserved-communities-throughthe-Federal-government. 27 Centers for Medicare and Medicaid Services Office of Minority Health. The CMS Equity Plan for Improving Quality in Medicare. 2015. https:// www.cms.gov/About-CMS/Agency-Information/ OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_ 090615.pdf. 28 Centers for Medicare and Medicaid Services Office of Minority Health. The CMS Equity Plan for Improving Quality in Medicare. 2015. https:// www.cms.gov/About-CMS/Agency-Information/ OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_ 090615.pdf. 29 Centers for Medicare Services. CMS Quality Strategy. 2016. https://www.cms.gov/Medicare/ Quality-Initiatives-Patient-Assessment-Instruments/ QualityInitiativesGenInfo/Downloads/CMS-QualityStrategy.pdf. 30 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/ QualityInitiativesGenInfo/MMF/General-info-SubPage. E:\FR\FM\13APP2.SGM 13APP2 19496 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 on gaps in quality through the following reports and programs: • The CMS Mapping Medicare Disparities Tool, which is an interactive map that identifies areas of disparities and a starting point to understand and investigate geographical, racial and ethnic differences in health outcomes for Medicare patients.31 • The Racial, Ethnic, and Gender Disparities in Health Care in Medicare Advantage Stratified Report, which highlights racial and ethnic differences in health care experiences and clinical care, compares quality of care for women and men, and looks at racial and ethnic differences in quality of care among women and men separately for Medicare Advantage plans.32 • The Rural-Urban Disparities in Health Care in Medicare Report, which details rural-urban differences in health care experiences and clinical care.33 • The Standardized Patient Assessment Data Elements for certain post-acute care Quality Reporting Programs, which now includes data reporting for race and ethnicity and preferred language, in addition to screening questions for social needs (84 FR 42536 through 42588). • The CMS Innovation Center’s Accountable Health Communities Model, which include standardized data collection of health-related social needs data. • The Guide to Reducing Disparities which provides an overview of key issues related to disparities in readmissions and reviews sets of activities that can help hospital leaders reduce readmissions in diverse populations.34 • The CMS Disparity Methods, which provide hospital-level confidential results stratified by dual eligibility for condition-specific readmission measures currently included in the Hospital Readmission Reduction Program (84 FR 42496 through 42500). These programs are informed by reports by the National Academies of Science, Engineering and Medicine 31 https://www.cms.gov/About-CMS/AgencyInformation/OMH/OMH-Mapping-MedicareDisparities. 32 https://www.cms.gov/About-CMS/AgencyInformation/OMH/research-and-data/statistics-anddata/stratified-reporting. 33 Centers for Medicare and Medicaid Services. Rural-Urban Disparities in Health Care in Medicare. 2019. https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/Rural-UrbanDisparities-in-Health-Care-in-Medicare-Report.pdf. 34 Guide to Reducing Disparities in Readmissions. CMS Office of Minority Health. Revised August 2018. Available at: https://www.cms.gov/AboutCMS/Agency-Information/OMH/Downloads/OMH_ Readmissions_Guide.pdf. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 (NASEM) 35 and the Office of the Assistant Secretary for Planning and Evaluation (ASPE) 36 which have examined the influence of social risk factors on several of our quality programs. In this RFI, we address only the sixth initiative listed, the CMS Disparity Methods, which we have implemented for measures in the Hospital Readmissions Reduction Program and are considering in other programs, including the IPFQR Program. We discuss the implementation of these methods to date and present considerations for continuing to improve and expand these methods to provide providers and ultimately consumers with actionable information on disparities in health care quality to support efforts at closing the equity gap. 2. Current CMS Disparity Methods We first sought public comment on potential confidential and public reporting of IPFQR program measure data stratified by social risk factors in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20121). We initially focused on stratification by dual eligibility, which is consistent with recommendations from ASPE’s First Report to Congress which was required by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 (Pub. L. 113–185).37 This report found that in the context of value-based purchasing (VBP) programs, dual eligibility was among the most powerful predictors of poor health outcomes among those social risk factors that ASPE examined and tested. In the FY 2018 IPPS/LTCH PPS final rule we also solicited feedback on two potential methods for illuminating differences in outcomes rates among patient groups within a provider’s patient population that would also allow for a comparison of those differences, or disparities, across providers for the Hospital IQR Program (82 FR 38403 through 38409). The first method (the Within-Hospital disparity method) promotes quality improvement by calculating differences in outcome rates among patient groups within a hospital while accounting for their clinical risk factors. This method also 35 National Academies of Sciences, Engineering, and Medicine. 2016. Accounting for Social Risk Factors in Medicare Payment: Identifying Social Risk Factors. Washington, DC: The National Academies Press. https://doi.org/10.17226/21858. 36 https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 37 https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. PO 00000 Frm 00018 Fmt 4701 Sfmt 4702 allows for a comparison of the magnitude of disparity across hospitals, permitting hospitals to assess how well they are closing disparity gaps compared to other hospitals. The second methodological approach (the AcrossHospital method) is complementary and assesses hospitals’ outcome rates for dual-eligible patients only, across hospitals, allowing for a comparison among hospitals on their performance caring for their patients with social risk factors. In the FY 2018 IPPS/LTCH PPS proposed rule under the IPFQR Program (82 FR 20121), we also specifically solicited feedback on which social risk factors provide the most valuable information to stakeholders. Overall, comments supported the use of dual eligibility as a proxy for social risk, although commenters also suggested investigation of additional social risk factors, and we continue to consider which risk factors provide the most valuable information to stakeholders. Concurrent with our comment solicitation on stratification in the IPFQR Program, we have considered methods for stratifying measure results for other quality reporting programs. For example, FY 2019 IPPS/LTCH PPS final rule (82 FR 41597 through 41601), we finalized plans to provide confidential hospital-specific reports (HSRs) containing stratified results of the Pneumonia Readmission (NQF #0506) and Pneumonia Mortality (NQF #0468) measures including both the AcrossHospital Disparity Method and the Within-Hospital Disparity Method (disparity methods), stratified by dual eligibility. In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41554 through 41556), we also removed six condition/ procedure specific readmissions measures, including the Pneumonia Readmission measure (NQF #0506) and five mortality measures, including the Pneumonia Mortality measure (NQF #0468) (83 FR 41556 through 41558) from the Hospital IQR Program. However, the Pneumonia Readmission (NQF #0506) and the other condition/ procedure measures remained in the Hospital Readmissions Reduction Program. In 2019, we provided hospitals with results of the Pneumonia Readmission measure (NQF #0506) stratified using dual eligibility. We provided this information in annual confidential HSRs for claims-based measures. We then, in the FY 2020 IPPS/LTCH PPS Final Rule (84 FR 42388 through 42390), finalized the proposal to provide confidential hospital specific reports (HSRs) containing data stratified by dual-eligible status for all six readmission measures included in the E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules Hospital Readmission Reduction Program. 3. Potential Expansion of the CMS Disparity Methods We are committed to advancing health equity by improving data collection to better measure and analyze disparities across programs and policies.38 As we previously noted, we have been considering, among other things, expanding our efforts to provide stratified data for additional social risk factors and measures, optimizing the ease-of-use of the results, enhancing public transparency of equity results, and building towards provider accountability for health equity. We are seeking public comment on the potential stratification of quality measures in the IPFQR Program across two social risk factors: Dual eligibility and race/ethnicity. jbell on DSKJLSW7X2PROD with PROPOSALS2 a. Stratification of Quality Measure Results—Dual Eligibility As described above, landmark reports by the National Academies of Science, Engineering and Medicine (NASEM) 39 and the Office of the Assistant Secretary for Planning and Evaluation (ASPE),40 which have examined the influence of social risk factors on several of our quality programs, have shown that in the context of value-based purchasing (VBP) programs, dual eligibility, as an indicator of social risk, is a powerful predictor of poor health outcomes. We note that the patient population of IPFs has a higher percentage of dually eligible patients than the general Medicare population. Specifically, over half (56 percent) of Medicare patients in IPFs are dually eligible 41 while approximately 20 percent of all Medicare patients are dually eligible.42 We are considering stratification of quality measure results in the IPFQR Program and are considering which 38 Centers for Medicare Services. CMS Quality Strategy. 2016. https://www.cms.gov/Medicare/ Quality-Initiatives-Patient-Assessment-Instruments/ QualityInitiativesGenInfo/Downloads/CMS-QualityStrategy.pdf. 39 National Academies of Sciences, Engineering, and Medicine. 2016. Accounting for Social Risk Factors in Medicare Payment: Identifying Social Risk Factors. Washington, DC: The National Academies Press. https://doi.org/10.17226/21858. 40 https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 41 https://aspe.hhs.gov/basic-report/transitionscare-and-service-use-among-medicare-beneficiariesinpatient-psychiatric-facilities-issue-brief. 42 https://www.cms.gov/Medicare-MedicaidCoordination/Medicare-and-MedicaidCoordination/Medicare-Medicaid-CoordinationOffice/DataStatisticalResources/Downloads/ MedicareMedicaidDualEnrollmentEverEnrolled TrendsDataBrief2006-2018.pdf. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 measures would be most appropriate for stratification and if dual eligibility would be a meaningful social risk factor for stratification. For the IPFQR Program, we would consider disparity reporting using two disparity methods derived from the Within-Hospital and Across-Hospital methods, described above. The first method (based on the Within-Facility disparity method) would aim to promote quality improvement by calculating differences in outcome rates between dual and non-dual eligible patient groups within a facility while accounting for their clinical risk factors. This method would allow for a comparison of those differences, or disparities, across facilities, so facilities could assess how well they are closing disparity gaps compared to other facilities. The second approach (based the Across-Facility method) would be complementary and assesses facilities’ outcome rates for subgroups of patients, such as dual eligible patients, across facilities, allowing for a comparison among facilities on their performance caring for their patients with social risk factors. b. Stratification of Quality Measure Results—Race and Ethnicity The Administration’s Executive Order on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government directs agencies to assess potential barriers that underserved communities and individuals may face to enrollment in and access to benefits and services in Federal Programs. As summarized above, studies have shown that among Medicare beneficiaries, racial and ethnic minority persons often experience worse health outcomes, including more frequent hospital readmissions and operative complications. An important part of identifying and addressing inequities in health care is improving data collection to allow us to better measure and report on equity across our programs and policies. We are considering stratification of quality measure results in the IPFQR Program by race and ethnicity and are considering which measures would be most appropriate for stratification. As outlined in the 1997 Office of Management and Budget (OMB) Revisions to the Standards for the Collection of Federal Data on Race and Ethnicity, the racial and ethnic categories, which may be used for reporting the disparity methods are considered to be social and cultural, not PO 00000 Frm 00019 Fmt 4701 Sfmt 4702 19497 biological or genetic.43 The 1997 OMB Standard lists five minimum categories of race: (1) American Indian or Alaska Native; (2) Asian; (3) Black or African American; (4) Native Hawaiian or Other Pacific Islander; (5) and White. In the OMB standards, Hispanic or Latino is the only ethnicity category included, and since race and ethnicity are two separate and distinct concepts, persons who report themselves as Hispanic or Latino can be of any race.44 Another example, the ‘‘Race & Ethnicity—CDC’’ code system in Public Health Information Network (PHIN) Vocabulary Access and Distribution System (VADS) 45 permits a much more granular structured recording of a patient’s race and ethnicity with its inclusion of over 900 concepts for race and ethnicity. The recording and exchange of patient race and ethnicity at such a granular level can facilitate the accurate identification and analysis of health disparities based on race and ethnicity. Further, the ‘‘Race & Ethnicity—CDC’’ code system has a hierarchy that rolls up to the OMB minimum categories for race and ethnicity and, thus, supports aggregation and reporting using the OMB standard. ONC includes both the CDC and OMB standards in its criterion for certified health IT products.46 For race and ethnicity, a certified health IT product must be able to express both detailed races and ethnicities using any of the 900 plus concepts in the ‘‘Race & Ethnicity—CDC’’ code system in the PHIN VADS, as well as aggregate each one of a patient’s races and ethnicities to the categories in the OMB standard for race and ethnicity. This approach can reduce burden on providers recording demographics using certified products. Self-reported race and ethnicity data remain the gold standard for classifying an individual according to race or ethnicity. However, CMS does not consistently collect self-reported race and ethnicity for the Medicare program, but instead gets the data from the Social Security Administration (SSA) and the data accuracy and comprehensiveness have proven challenging despite capabilities in the marketplace via 43 Executive Office of the President Office of Management and Budget, Office of Information and Regulatory Affairs. Revisions to the standards for the classification of Federal data on race and ethnicity. Vol 62. Federal Register. 1997:58782– 58790. 44 https://www.census.gov/topics/population/ hispanic-origin/about.html. 45 https://phinvads.cdc.gov/vads/ViewValue Set.action?id=67D34BBC-617F-DD11-B38D00188B398520. 46 ONC criteria for certified health IT products: https://www.healthit.gov/isa/representing-patientrace-and-ethnicity. E:\FR\FM\13APP2.SGM 13APP2 19498 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 certified health IT products. Historical inaccuracies in Federal data systems and limited collection classifications have contributed to the limited quality of race and ethnicity information in Medicare’s administrative data systems.47 In recent decades, to address these data quality issues, we have undertaken numerous initiatives, including updating to data taxonomies and conducting direct mailings to some beneficiaries to enable more comprehensive race and ethnic identification.48 49 Despite those efforts, studies reveal varying data accuracy in identification of racial and ethnic groups in Medicare administrative data, with higher sensitivity for correctly identifying White and Black individuals, and lower sensitivity for correctly identifying individuals of Hispanic ethnicity or of Asian/Pacific Islander and American Indian/Alaskan Native race.50 Incorrectly classified race or ethnicity may result in overestimation or underestimation in the quality of care received by certain groups of beneficiaries. We continue to work with Federal and private partners to better collect and leverage data on social risk to improve our understanding of how these factors can be better measured in order to close the health equity gap. Among other things, we have developed an Inventory of Resources for Standardized Demographic and Language Data Collection 51 and supported collection of specialized International Classification of Disease, 10th Edition, Clinical Modification (ICD–10–CM) codes for describing the socioeconomic, cultural, and environmental determinants of health, and sponsored several initiatives to statistically estimate race and ethnicity information 47 Eicheldinger, C., & Bonito, A. (2008). More accurate racial and ethnic codes for Medicare administrative data. Health Care Financing Review, 29(3), 27–42. 48 Filice CE, Joynt KE. Examining Race and Ethnicity Information in Medicare Administrative Data. Med Care. 2017;55(12):e170-e176. doi:10.1097/MLR.0000000000000608. 49 Eicheldinger, C., & Bonito, A. (2008). More accurate racial and ethnic codes for Medicare administrative data. Health Care Financing Review, 29(3), 27–42. 50 Centers for Medicare and Medicaid Services. Building an Organizational Response to Health Disparities Inventory of Resources for Standardized Demographic and Language Data Collection. 2020. https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/Data-CollectionResources.pdf. 51 Centers for Medicare and Medicaid Services. Building an Organizational Response to Health Disparities Inventory of Resources for Standardized Demographic and Language Data Collection. 2020. https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/Data-CollectionResources.pdf. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 when it is absent.52 The Office of the National Coordinator for Health Information Technology (ONC) included social, psychological, and behavioral standards in the 2015 Edition health information technology (IT) certification criteria (2015 Edition), providing interoperability standards (LOINC (Logical Observation Identifiers Names and Codes) and SNOMED CT (Systematized Nomenclature of Medicine—Clinical Terms)) for financial strain, education, social connection and isolation, and others. Additional stakeholder efforts underway to expand capabilities to capture additional social determinants of health data elements include the Gravity Project to identify and harmonize social risk factor data for interoperable electronic health information exchange for EHR fields, as well as proposals to expand the ICD–10 (International Classification of Diseases, Tenth Revision) z-codes, the alphanumeric codes used worldwide to represent diagnoses.53 While development of sustainable and consistent programs to collect data on social determinants of health can be considerable undertakings, we recognize that another method to identify better race and ethnicity data is needed in the short term to address the need for reporting on health equity. In working with our contractors, two algorithms have been developed to indirectly estimate the race and ethnicity of Medicare beneficiaries (as described further in the following paragraphs). We feel that using indirect estimation can help to overcome the current limitations of demographic information and enable timelier reporting of equity results until longer term collaborations to improve demographic data quality across the health care sector materialize. The use of indirectly estimated race and ethnicity for conducting stratified reporting does not place any additional collection or reporting burdens on facilities as these data are derived using existing administrative and censuslinked data. Indirect estimation relies on a statistical imputation method for inferring a missing variable or improving an imperfect administrative variable using a related set of information that is more readily 52 https://pubmed.ncbi.nlm.nih.gov/18567241/, https://pubmed.ncbi.nlm.nih.gov/30506674/, Eicheldinger C, Bonito A. More accurate racial and ethnic codes for Medicare administrative data. Health Care Finance Rev. 2008;29(3):27–42. Haas A, Elliott MN, Dembosky JW, et al. Imputation of race/ ethnicity to enable measurement of HEDIS performance by race/ethnicity. Health Serv Res. 2019;54(1):13–23. doi:10.1111/1475–6773.13099. 53 https://aspe.hhs.gov/pdf-report/second-impactreport-to-congress. PO 00000 Frm 00020 Fmt 4701 Sfmt 4702 available.54 Indirectly estimated data are most commonly used at the population level (such as the facility or health planlevel), where aggregated results form a more accurate description of the population than existing, imperfect data sets. These methods often estimate race and ethnicity using a combination of other data sources which are predictive of self-identified race and ethnicity, such as language preference, information about race and ethnicity in our administrative records, first and last names matched to validated lists of names correlated to specific national origin groups, and the racial and ethnic composition of the surrounding neighborhood. Indirect estimation has been used in other settings to support population-based equity measurement when self-identified data are not available.55 As described above, we have previously supported the development of two such methods of indirect estimation of race and ethnicity of Medicare beneficiaries. One indirect estimation approach, developed by our contractor, uses Medicare administrative data, first name and surname matching, derived from the U.S. Census and other sources, with beneficiary language preference, state of residence, and the source of the race and ethnicity code in Medicare administrative data to reclassify some beneficiaries as Hispanic or Asian/ Pacific Islander (API).56 In recent years, we have also worked with another contractor to develop a new approach, the Medicare Bayesian Improved Surname Geocoding (MBISG), which combines Medicare administrative data, first and surname matching, geocoded residential address linked to the 2010 U.S. Census, and uses both Bayesian updating and multinomial logistic regression to estimate the probability of belonging to each of six racial/ethnic groups.57 54 IOM. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. 55 IOM. 2009. Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. 56 Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of New Race-Ethnicity Codes and Socioeconomic Status (SES) Indicators for Medicare Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI International for the Centers for Medicare and Medicaid Services through an interagency agreement with the Agency for Healthcare Research and Policy, under Contract No. 500–00–0024, Task No. 21) AHRQ Publication No. 08–0029–EF. Rockville, MD, Agency for Healthcare Research and Quality. January 2008. 57 Haas, A., Elliott, M. et al (2018). Imputation of race/ethnicity to enable measurement of HEDIS E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 The MBISG model is currently used to conduct the national, contract-level, stratified reporting of Medicare Part C & D performance data for Medicare Advantage Plans by race and ethnicity.58 Validation testing reveals concordances of 0.88 through 0.95 between indirectly estimated and selfreport among individuals who identify as White, Black, Hispanic and API for the MIBSG version 2.0 and concordances with self-reported race and ethnicity of 0.96 through 0.99 for these same groups for MBISG version 2.1.59 60 The algorithms under consideration are considerably less accurate for individuals who selfidentify as American Indian/Alaskan Native or multiracial.61 Indirect estimation can be a statistically reliable approach for calculating populationlevel equity results for groups of individuals (such as the facility-level) and is not intended, nor being considered, as an approach for inferring the race and ethnicity of an individual. However, despite the high degree of statistical accuracy of the indirect estimation algorithms under consideration there remains the small risk of unintentionally introducing bias. For example, if the indirect estimation is not as accurate in correctly estimating race and ethnicity in certain geographies or populations it could lead to some bias in the method results. Such bias might result in slight overestimation or underestimation of the quality of care received by a given group. We feel this amount of bias is considerably less than performance by race/ethnicity. Health Services Research, 54:13–23. 58 The Office of Minority Health (2020). Racial, Ethnic, and Gender Disparities in Health Care in Medicare Advantage, The Centers for Medicare and Medicaid Services, (pg vii). https://www.cms.gov/ About-CMS/Agency-Information/OMH/researchand-data/statistics-and-data/stratified-reporting. 59 Haas, A., Elliott, M. et al (2018). Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity. Health Services Research, 54:13–23. 60 MBISG 2.1 validation results performed under contract #GS–10F–0012Y/HHSM–500–2016– 00097G). Pending public release of the 2021 Part C and D Performance Data Stratified by Race, Ethnicity, and Gender Report, available at: https:// www.cms.gov/About-CMS/Agency-Information/ OMH/research-and-data/statistics-and-data/ stratified-reporting. 61 Haas, A., Elliott, M. et al (2018). Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity. Health Services Research, 54:13–23 and Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of New RaceEthnicity Codes and Socioeconomic Status (SES) Indicators for Medicare Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI International for the Centers for Medicare and Medicaid Services through an interagency agreement with the Agency for Healthcare Research and Policy, under Contract No. 500–00–0024, Task No. 21) AHRQ Publication No. 08–0029–EF. Rockville, MD, Agency for Healthcare Research and Quality. January 2008. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 would be expected if stratified reporting was conducted using the race and ethnicity currently contained in our administrative data. Indirect estimation of race and ethnicity is envisioned as an intermediate step, filling the pressing need for more accurate demographic information for the purposes of exploring inequities in service delivery, while allowing newer approaches, as described in the next section, for improving demographic data collection to progress. We are interested in learning more about, and soliciting comments about, the potential benefits and challenges associated with measuring facility equity using an imputation algorithm to enhance existing administrative data quality for race and ethnicity until self-reported information is sufficiently available. c. Improving Demographic Data Collection Stratified facility-level reporting using dual eligibility and indirectly estimated race and ethnicity would represent an important advance in our ability to provide equity reports to facilities. However, self-reported race and ethnicity data remain the gold standard for classifying an individual according to race or ethnicity. The CMS Quality Strategy outlines our commitment to strengthening infrastructure and data systems by ensuring that standardized demographic information is collected to identify disparities in health care delivery outcomes.62 Collection and sharing of a standardized set of social, psychological, and behavioral data by facilities, including race and ethnicity, using electronic data definitions which permit nationwide, interoperable health information exchange, can significantly enhance the accuracy and robustness of our equity reporting.63 This could potentially include expansion to additional social risk factors, such as disability status, where accuracy of administrative data is currently limited. We are mindful that additional resources, including data collection and staff training may be necessary to ensure that conditions are created whereby all patients are comfortable answering all demographic questions, and that individual preferences for non-response are maintained. 62 The Centers for Medicare & Medicaid Services. CMS Quality Strategy. 2016. https://www.cms.gov/ Medicare/Quality-Initiatives-Patient-AssessmentInstruments/QualityInitiativesGenInfo/Downloads/ CMS-Quality-Strategy.pdf. 63 The Office of the National Coordinator for Health Information Technology. United State Core Data for Interoperability Draft Version 2. 2021. https://www.healthit.gov/isa/sites/isa/files/2021-01/ Draft-USCDI-Version-2-January-2021-Final.pdf. PO 00000 Frm 00021 Fmt 4701 Sfmt 4702 19499 We are also interested in learning about and are soliciting comments on current data collection practices by facilities to capture demographic data elements (such as race, ethnicity, sex, sexual orientation and gender identity (SOGI), primary language, and disability status). Further, we are interested in potential challenges facing facility collection, at the time of admission, of a minimum set of demographic data elements in alignment with national data collection standards (such as the standards finalized by the Affordable Care Act) 64 and standards for interoperable exchange (such as the U.S. Core Data for Interoperability incorporated into certified health IT products as part of the 2015 Edition of health IT certification criteria).65 Advancing data interoperability through collection of a minimum set of demographic data collection, and incorporation of this demographic information into quality measure specifications, has the potential for improving the robustness of the disparity method results, potentially permitting reporting using more accurate, self-reported information, such as race and ethnicity, and expanding reporting to additional dimensions of equity, including stratified reporting by disability status. d. Potential Creation of a Facility Equity Score To Synthesize Results Across Multiple Social Risk Factors As we describe in section IV.D.3.a of this proposed rule, we are considering expanding the disparity methods to IPFs and to include two social risk factors (dual eligibility and race/ethnicity). This approach would improve the comprehensiveness of health equity information provided to facilities. Aggregated results from multiple measures and multiple social risk factors, from the CMS Disparity Methods, in the format of a summary score, can improve the usefulness of the equity results. In working with our contractors, we recently developed an equity summary score for Medicare Advantage contract/plans, the Health Equity Summary Score (HESS), with application to stratified reporting using two social risk factors: dual eligibility and race and as described in Incentivizing Excellent Care to At-Risk Groups with a Health Equity Summary Score.66 64 https://minorityhealth.hhs.gov/assets/pdf/ checked/1/Fact_Sheet_Section_4302.pdf. 65 https://www.healthit.gov/sites/default/files/ 2020-08/2015EdCures_Update_CCG_USCDI.pdf. 66 Agniel D, Martino SC, Burkhart Q, et al. Incentivizing Excellent Care to At-Risk Groups with E:\FR\FM\13APP2.SGM Continued 13APP2 19500 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules The HESS calculates standardized and combined performance scores blended across the two social risk factors. The HESS also combines results of the within-plan (similar to the Within-Facility method) and across-plan method (similar to the Across-Facility method) across multiple performance measures. We are considering building a ‘‘Facility Equity Score,’’ not yet developed, which would be modeled off the HESS but adapted to the context of risk-adjusted facility outcome measures and potentially other IPF quality measures. We envision that the Facility Equity Score would synthesize results for a range of measures and using multiple social risk factors, using measures and social risk factors, which would be reported to facilities as part of the CMS Disparity Methods. We believe that creation of the Facility Equity Score has the potential to supplement the overall measure data already reported on the Care Compare or successor website, by providing easy to interpret information regarding disparities measured within individual facilities and across facilities nationally. A summary score would decrease burden by minimizing the number of measure results provided and providing an overall indicator of equity. The Facility Equity Score under consideration would potentially: • Summarize facility performance across multiple social risk factors (initially dual eligibility and indirectly estimated race and ethnicity, as described above); and • Summarize facility performance across the two disparity methods (that is, the Within-Facility Disparity Method and the Across-Facility Disparity Method) and potentially for multiple measures. Prior to any future public reporting, if we determine that a Facility Equity Score can be feasibly and accurately calculated, we would provide results of the Facility Equity Score, in confidential facility specific reports, which facilities and their QIN–QIOs would be able to download. Any potential future proposal to display the Facility Equity Score on the Care Compare or successor website would be made through future RFI or rulemaking. jbell on DSKJLSW7X2PROD with PROPOSALS2 c. Solicitation of Public Comment We are soliciting public comments on the possibility of stratifying IPFQR Program measures by dual eligibility and race and ethnicity. We are also a Health Equity Summary Score. J Gen Intern Med. Published online November 11, 2019 Nov 11. doi: 10.1007/s11606–019–05473–x. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 soliciting public comments on mechanisms of incorporating cooccurring disability status into such stratification as well. We are soliciting public comments on the application of the within-facility or across-facility disparities methods IPFQR Program measures if we were to stratify IPFQR Program measures. We are also seeking comment on the possibility of facility collection of standardized demographic information for the purposes of potential future quality reporting and measure stratification. In addition, we are soliciting public comments on the potential design of a facility equity score for calculating results across multiple social risk factors and measures, including race and disability. Any data pertaining to these areas that are recommended for collection for measure reporting for a CMS program and any potential public disclosure on Care Compare or successor website would be addressed through a separate and future notice- and-comment rulemaking. We plan to continue working with ASPE, facilities, the public, and other key stakeholders on this important issue to identify policy solutions that achieve the goals of attaining health equity for all patients and minimizing unintended consequences. We look forward to receiving feedback on these topics. We also note our intention for additional RFIs or rulemaking on this topic in the future. Specifically, we are soliciting public comment on the following: Future Potential Stratification of Quality Measure Results • The possible stratification of facility-specific reports for IPFQR program measure data by dual-eligibility status given that over half of the patient population in IPFs are dually eligible, including, which measures would be most appropriate for stratification; • The potential future application of indirect estimation of race and ethnicity to permit stratification of measure data for reporting facility-level disparity results until more accurate forms of selfidentified demographic information are available; • Appropriate privacy safeguards with respect to data produced from the indirect estimation of race and ethnicity to ensure that such data are properly identified if/when it is shared with providers. • Ways to address the challenges of defining and collecting accurate and standardized self-identified demographic information, including information on race and ethnicity and disability, for the purposes of reporting, PO 00000 Frm 00022 Fmt 4701 Sfmt 4702 measure stratification and other data collection efforts relating to quality. • Recommendations for other types of readily available data elements for measuring disadvantage and discrimination for the purposes of reporting, measure stratification and other data collection efforts relating to quality, in addition, or in combination with race and ethnicity. • Recommendations for types of quality measures or measurement domains to prioritize for stratified reporting by dual eligibility, race and ethnicity, and disability. • Examples of approaches, methods, research, and/or considerations for use of data-driven technologies that do not facilitate exacerbation of health inequities, recognizing that biases may occur in methodology or be encoded in datasets. Improving Demographic Data Collection • Experiences of users of certified health IT regarding local adoption of practices for collection of social, psychological, and behavioral data elements, the perceived value of using these data for improving decisionmaking and care delivery, and the potential challenges and benefits of collecting more granular, structured demographic information, such as the ‘‘Race & Ethnicity—CDC’’ code system. • The possible collection of a minimum set of social, psychological, and behavioral data elements by hospitals at the time of admission using structured, interoperable data standards, for the purposes of reporting, measure stratification and other data collection efforts relating to quality. Potential Creation of a Facility Equity Score To Synthesize Results Across Multiple Social Risk Factors • The possible creation and confidential reporting of a Facility Equity Score to synthesize results across multiple social risk factors and disparity measures. • Interventions facilities could institute to improve a low facility equity score and how improved demographic data could assist with these efforts. E. Measure Adoption We strive to put consumers and caregivers first, ensuring they are empowered to make decisions about their own healthcare along with their clinicians using information from datadriven insights that are increasingly aligned with meaningful quality measures. We support technology that reduces burden and allows clinicians to focus on providing high-quality healthcare for their patients. We also E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules support innovative approaches to improve quality, accessibility, and affordability of care while paying particular attention to improving clinicians’ and beneficiaries’ experiences when interacting with our programs. In combination with other efforts across the Department of Health and Human Services (HHS), we believe the IPFQR Program helps to incentivize facilities to improve healthcare quality and value while giving patients and providers the tools and information needed to make the best decisions for them. Consistent with these goals, our objective in selecting quality measures is to balance the need for information on the full spectrum of care delivery and the need to minimize the burden of data collection and reporting. We have primarily focused on measures that evaluate critical processes of care that have significant impact on patient outcomes and support CMS and HHS priorities for improved quality and efficiency of care provided by IPFs. When possible, we also propose to incorporate measures that directly evaluate patient outcomes and experience. We refer readers to section VIII.F.4.a. of the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645 through 53646) for a detailed discussion of the considerations taken into account in selecting quality measures. 1. Measure Selection Process jbell on DSKJLSW7X2PROD with PROPOSALS2 Before being proposed for inclusion in the IPFQR Program, measures are placed on a list of measures under consideration (MUC), which is published annually on behalf of CMS by the National Quality Forum (NQF). Following publication on the MUC list, the Measure Applications Partnership (MAP), a multi-stakeholder group convened by the NQF, reviews the measures under consideration for the IPFQR Program, among other Federal programs, and provides input on those measures to the Secretary. We consider the input and recommendations provided by the MAP in selecting all measures for the IPFQR Program. In our evaluation of the IPFQR Program measure set, we identified two measures that we believe are appropriate to propose for the IPFQR Program. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 2. Proposed Adoption of COVID–19 Vaccination Coverage Among Health Care Personnel (HCP) 67 Measure for the FY2023 Payment Determination and Subsequent Years a. Background On January 31, 2020, the Secretary declared a public health emergency (PHE) for the U.S. in response to the global outbreak of SARS–CoV–2, a novel (new) coronavirus that causes a disease named ‘‘coronavirus disease 2019’’ (COVID–19).68 COVID–19 is a contagious respiratory illness 69 that can cause serious illness and death. Older individuals and those with underlying medical conditions are considered to be at higher risk for more serious complications from COVID–19.70 As of April 2, 2021, the U.S. has reported over 30 million cases of COVID–19 and over 550,000 COVID–19 deaths.71 Hospitals and health systems saw significant surges of COVID–19 patients as community infection levels increased.72 From December 2, 2020 through January 30, 2021, more than 100,000 Americans were in the hospital with COVID–19 at the same time.73 Evidence indicates that COVID–19 primarily spreads when individuals are in close contact with one another.74 The virus is typically transmitted through respiratory droplets or small particles 67 This measure was previously titled, ‘‘SARS– CoV–2 Vaccination Coverage among Healthcare Personnel.’’. 68 U.S. Dept of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response. (2020). Determination that a Public Health Emergency Exists. Available at: https:// www.phe.gov/emergency/news/healthactions/phe/ Pages/2019-nCoV.aspx. 69 Centers for Disease Control and Prevention. (2020). Your Health: Symptoms of Coronavirus. Available at: https://www.cdc.gov/coronavirus/ 2019-ncov/symptoms-testing/symptoms.html. 70 Centers for Disease Control and Prevention. (2020). Your Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019ncov/symptoms-testing/symptoms.html. 71 Centers for Disease Control and Prevention. (2020). CDC COVID Data Tracker. Accessed on April 3, 2021 at: https://covid.cdc.gov/covid-datatracker/#cases_casesper100klast7days. 72 Associated Press. Tired to the Bone. Hospitals Overwhelmed with Virus Cases. November 18, 2020. Accessed on December 16, 2020, at https:// apnews.com/article/hospitals-overwhelmedcoronavirus-cases74a1f0dc3634917a5dc13408455cd895. Also see: New York Times. Just how full are U.S. intensive care units? New data paints an alarming picture. November 18, 2020. Accessed on December 16, 2020, at: https://www.nytimes.com/2020/12/09/ world/just-how-full-are-us-intensive-care-units-newdata-paints-an-alarming-picture.html. 73 U.S. Currently Hospitalized | The COVID Tracking Project https://covidtracking.com/data/ charts/us-currently-hospitalized. 74 Centers for Disease Control and Prevention. (2021). How COVID–19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019ncov/prevent-getting-sick/how-covid-spreads.html. PO 00000 Frm 00023 Fmt 4701 Sfmt 4702 19501 created when someone who is infected with the virus coughs, sneezes, sings, talks, or breathes.75 Thus, the CDC advises that infections mainly occur through exposure to respiratory droplets when a person is in close contact with someone who has COVID–19.76 Experts believe that COVID–19 spreads less commonly through contact with a contaminated surface (although that is not thought to be a common way that COVID–19 spreads),77 and that in certain circumstances, infection can occur through airborne transmission.78 According to the CDC, those at greatest risk of infection are persons who have had prolonged, unprotected close contact (that is, within 6 feet for 15 minutes or longer) with an individual with confirmed SARS–CoV–2 infection, regardless of whether the individual has symptoms.79 Although personal protective equipment (PPE) and other infection-control precautions can reduce the likelihood of transmission in health care settings, COVID–19 can spread between health care personnel (HCP) and patients, or from patient to patient given the close contact that may occur during the provision of care.80 The CDC has emphasized that health care settings, including long-term care settings, can be high-risk places for COVID–19 exposure and transmission.81 Vaccination is a critical part of the nation’s strategy to effectively counter the spread of COVID–19 and ultimately help restore societal functioning.82 On 75 Centers for Disease Control and Prevention. (2021). How COVID–19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019ncov/prevent-getting-sick/how-covid-spreads.html. 76 Centers for Disease Control and Prevention. (2021). How COVID–19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019ncov/prevent-getting-sick/how-covid-spreads.html. 77 Centers for Disease Control and Prevention. (2021). How COVID–19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019ncov/prevent-getting-sick/how-covid-spreads.html. 78 Centers for Disease Control and Prevention. (2021). How COVID–19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019ncov/prevent-getting-sick/how-covid-spreads.html. 79 Centers for Disease Control and Prevention. (2021). When to Quarantine. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019ncov/if-you-are-sick/quarantine.html. 80 Centers for Disease Control and Prevention. (2020). Interim U.S. Guidance for Risk Assessment and Work Restrictions for Healthcare Personnel with Potential Exposure to COVID–19. Accessed on April 2, 2021 at: https://www.cdc.gov/coronavirus/ 2019-ncov/hcp/faq.html#Transmission. 81 Dooling, K, McClung, M, et al. ‘‘The Advisory Committee on Immunization Practices’ Interim Recommendations for Allocating Initial Supplies of COVID–19 Vaccine—United States, 2020.’’ Morb Mortal Wkly Rep. 2020; 69(49): 1857–1859. 82 Centers for Disease Control and Prevention. (2020). COVID–19 Vaccination Program Interim Playbook for Jurisdiction Operations. Accessed on April 3, 2021 at: https://www.cdc.gov/vaccines/imz- E:\FR\FM\13APP2.SGM Continued 13APP2 19502 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 December 11, 2020, the FDA issued the first Emergency Use Authorization (EUA) for a COVID–19 vaccine in the U.S.83 Subsequently, the FDA issued EUAs for additional COVID–19 vaccines.84 The FDA determined that it was reasonable to conclude that the known and potential benefits of each vaccine, when used as authorized to prevent COVID–19, outweighed its known and potential risks.85 As part of its national strategy to address COVID–19, the Biden Administration stated that it would work with states and the private sector to execute an aggressive vaccination strategy and has outlined a goal of administering 200 million shots in 100 days,86 Although the goal of the U.S. government is to ensure that every American who wants to receive a COVID–19 vaccine can receive one, Federal agencies recommended that early vaccination efforts focus on those critical to the PHE response, including HCP providing direct care to patients with COVID–19, and individuals at highest risk for developing severe illness from COVID–19.87 For example, the CDC’s Advisory Committee on Immunization Practices (ACIP) recommended that HCP should be among those individuals prioritized to receive the initial, limited supply of the managers/downloads/COVID-19-VaccinationProgram-Interim_Playbook.pdf. 83 U.S. Food and Drug Administration. (2020). Pfizer-BioNTech COVID–19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/ media/144412/download. 84 U.S. Food and Drug Administration. (2020). Moderna COVID–19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/ media/144636/download; U.S. Food and Drug Administration. (2021). Janssen COVID–19 Vaccine EUA Letter of Authorization. Available at https:// www.fda.gov/media/146303/download. 85 U.S. Food and Drug Administration. (2020). Pfizer-BioNTech COVID–19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/ media/144412/download and .S. Food and Drug Administration. (2020). Moderna COVID–19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download; U.S. Food and Drug Administration. (2021). Janssen COVID–19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/ download. 86 https://www.whitehouse.gov/briefing-room/ speeches-remarks/2021/03/29/remarks-bypresident-biden-on-the-covid-19-response-and-thestate-of-vaccinations/. 87 Health and Human Services, Department of Defense. (2020) From the Factory to the Frontlines: The Operation Warp Speed Strategy for Distributing a COVID–19 Vaccine. Accessed December 18 at: https://www.hhs.gov/sites/default/files/strategy-fordistributing-covid-19-vaccine.pdf; Centers for Disease Control (2020). COVID–19 Vaccination Program Interim Playbook for Jurisdiction Operations. Accessed December 18 at: https:// www.cdc.gov/vaccines/imz-managers/downloads/ COVID-19-Vaccination-Program-Interim_ Playbook.pdf. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 COVID–19 vaccination given the potential for transmission in health care settings and the need to preserve health care system capacity.88 Research suggests most states followed this recommendation,89 and HCP began receiving the vaccine in mid-December of 2020.90 There are approximately 18 million healthcare workers in the U.S.91 As of April 3, 2021 the CDC reported that over 162 million doses of COVID–19 vaccine had been administered, and approximately 60 million people had received a complete vaccination course as described in IV.1.b.i of this proposed rule.92 President Biden indicated on March 2, 2021 that the U.S. is on track to have sufficient vaccine supply for every adult by the end of May 2021.93 We believe it is important to require that IPFs report HCP vaccination in their facilities in order to assess whether they are taking steps to protect health care workers and to help sustain the ability of IPFs to continue serving their communities throughout the PHE and beyond. Therefore, we are proposing a new measure, COVID–19 Vaccination Coverage Among HCP, beginning with the FY 2023 program year. For that program year, IPFs would be required to report data on the measure for the fourth quarter of 2021 (October 1, 2021 through December 31, 2021). For more information about the proposed reporting period, see section V.E.2.c of this proposed rule. The measure would assess the proportion of an IPF’s health care workforce that has been vaccinated against COVID–19. Although at this time data to show the effectiveness of COVID–19 vaccines to prevent asymptomatic infection or transmission of SARS–CoV–2 are limited, we believe IPFs should report the level of vaccination among their HCP as part of their efforts to assess and reduce the risk of transmission of COVID–19 within their facilities. HCP vaccination can potentially reduce illness that leads to work absence and limit disruptions to care.94 Data from influenza vaccination demonstrates that provider uptake of the vaccine is associated with that provider recommending vaccination to patients,95 and we believe HCP COVID– 19 vaccination in IPFs could similarly increase uptake among that patient population. We also believe that publishing the HCP vaccination rates will be helpful to many patients, including those who are at high-risk for developing serious complications from COVID–19, as they choose facilities from which to seek treatment. Under CMS’ Meaningful Measures Framework, the COVID–19 measure addresses the quality priority of ‘‘Promote Effective Prevention and Treatment of Chronic Disease’’ through the Meaningful Measure Area of ‘‘Preventive Care.’’ 88 Dooling, K, McClung, M, et al. ‘‘The Advisory Committee on Immunization Practices’ Interim Recommendations for Allocating Initial Supplies of COVID–19 Vaccine—United States, 2020.’’ Morb. Mortal Wkly Rep. 2020; 69(49): 1857–1859. ACIP also recommended that long-term care residents be prioritized to receive the vaccine, given their age, high levels of underlying medical conditions, and congregate living situations make them high risk for severe illness from COVID–19. 89 Kates, J, Michaud, J, Tolbert, J. ‘‘How Are States Prioritizing Who Will Get the COVID–19 Vaccine First?’’ Kaiser Family Foundation. December 14, 2020. Accessed on December 16 at https:// www.kff.org/policy-watch/how-are-statesprioritizing-who-will-get-the-covid-19-vaccine-first/. 90 Associated Press. ‘Healing is Coming:’ U.S. Health Workers Start Getting Vaccine. December 15, 2020. Accessed on December 16 at: https:// apnews.com/article/us-health-workers-coronavirusvaccine-56df745388a9fc12ae93c6f9a0d0e81f. 91 https://www.cdc.gov/niosh/topics/healthcare/ default.html#:∼:text=HEALTHCARE %20WORKERS,-Related%20Pages&text=Healthcare %20is%20the%20fastest%2Dgrowing,of%20the %20healthcare%20work%20force. 92 CDC. COVID Data Tracker. COVID–19 Vaccinations in the United States. Accessed on 2/ 18/21 at: https://covid.cdc.gov/covid-data-tracker/ #vaccinations. 93 The White House. Remarks by President Biden on the Administration’s COVID–19 Vaccination Efforts. Accessed March 18, 2021 at: https:// www.whitehouse.gov/briefing-room/speechesremarks/2021/03/02/remarks-by-president-bidenon-the-administrations-covid-19-vaccinationefforts/. The COVID–19 Vaccination Coverage Among HCP measure (‘‘COVID–19 HCP vaccination measure’’) is a process measure developed by the CDC to track COVID–19 vaccination coverage among HCP in facilities such as IPFs. PO 00000 Frm 00024 Fmt 4701 Sfmt 4702 b. Overview of Measure (1). Measure Specifications The denominator is the number of HCP eligible to work in the IPF for at least 1 day during the reporting period, excluding persons with contraindications to COVID–19 vaccination that are described by the CDC.96 The numerator is the cumulative number of HCP eligible to work in the health care facility for at least 1 day 94 Centers for Disease Control and Prevention. Overview of Influenza Vaccination among Health Care Personnel. October 2020. (2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/ long-term-care/why.htm. 95 Measure Application Committee Coordinating Committee Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 at: https:// www.qualityforum.org/Project_Pages/MAP_ Coordinating_Committee.aspx. 96 Centers for Disease Control and Prevention. Contraindications and precautions. https:// www.cdc.gov/vaccines/covid-19/info-by-product/ clinical-considerations.html#Contraindications. E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules during the reporting period and who received a completed vaccination course against COVID–19 since the vaccine was first available or on a repeated interval if revaccination on a regular basis is needed.97 Vaccination coverage for the purposes of this measure is defined as the estimated percentage of HCP eligible to work at the IPF for at least 1 day who received a completed vaccination course. A completed vaccination course may require one or more doses depending on the EUA for the specific vaccine used. The finalized specifications for this measure will be available at https:// www.cdc.gov/nhsn/nqf/. jbell on DSKJLSW7X2PROD with PROPOSALS2 (2). Review by the Measure Applications Partnership The COVID–19 HCP vaccination measure was included on the publicly available ‘‘List of Measures under Consideration for December 21, 2020,’’ 98 a list of measures under consideration for use in various Medicare programs. When the Measure Applications Partnership (MAP) Hospital Workgroup convened on January 11, 2021, it reviewed the MUC List and the COVID–19 HCP vaccination measure. The MAP recognized that the proposed measure represents a promising effort to advance measurement for an evolving national pandemic and that it would bring value to the IPFQR Program measure set by providing transparency about an important COVID–19 intervention to help prevent infections in HCP and patients.99 The MAP also stated that collecting information on COVID–19 vaccination coverage among HCP and providing feedback to facilities will allow facilities to benchmark coverage rates and improve coverage in their facility, and that reducing rates of COVID–19 in HCP may reduce transmission among patients and reduce instances of staff shortages due to illness.100 In its preliminary recommendations, the MAP Hospital Workgroup did not support this measure for rulemaking, 97 Measure Application Partnership Coordinating Committee Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 at: https:// www.qualityforum.org/Project_Pages/MAP_ Coordinating_Committee.aspx. 98 https://www.qualityforum.org/WorkArea/ linkit.aspx?LinkIdentifier=id&ItemID=94212. 99 Measure Applications Partnership. MAP Preliminary Recommendations 2020–2021. Accessed on January 24, 2021 at: https:// www.qualityforum.org/Project_Pages/MAP_ Hospital_Workgroup.aspx. 100 Measure Applications Partnership. MAP Preliminary Recommendations 2020–2021. Accessed on January 24, 2021 at: https:// www.qualityforum.org/Project_Pages/MAP_ Hospital_Workgroup.aspx. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 subject to potential for mitigation.101 To mitigate its concerns, the MAP believed that the measure needed welldocumented evidence, finalized specifications, testing, and NQF endorsement prior to implementation.102 Subsequently, the MAP Coordinating Committee met on January 25, 2021, and reviewed the COVID–19 Vaccination Coverage Among HCP measure. In the 2020–2021 MAP Final Recommendations, the MAP offered conditional support for rulemaking contingent on CMS bringing the measures back to MAP once the specifications are further refined.103 The MAP specifically stated, ‘‘the incomplete specifications require immediate mitigation and further development should continue.’’ 104 The spreadsheet of final recommendations no longer cited concerns regarding evidence, testing, or NQF endorsement.105 In response to the MAP final recommendation request that CMS bring the measure back to the MAP once the specifications are further refined, CMS and the CDC met with MAP Coordinating committee on March 15th. Additional information was provided to address vaccine availability, alignment of the COVID–19 Vaccination Coverage Among HCP as closely as possible with the data collection for the Influenza HCP vaccination measure (NQF 0431) and clarification related to how HCP are defined. At this meeting, CMS and the CDC presented preliminary findings from the testing of the numerator of COVID–19 Vaccination Coverage Among HCP, which is currently in process. These preliminary findings show numerator data should be feasible and reliable. Testing of the numerator of the number of healthcare personnel vaccinated involves a comparison of the data collected through NHSN and independently reported through the Federal pharmacy partnership program for delivering vaccination to LTC facilities. These are two completely 101 Measure Applications Partnership. MAP Preliminary Recommendations 2020–2021. Accessed on January 24, 2021 at: https:// www.qualityforum.org/Project_Pages/MAP_ Hospital_Workgroup.aspx. 102 Measure Applications Partnership. MAP Preliminary Recommendations 2020–2021. Accessed on January 24, 2021 at: https:// www.qualityforum.org/Project_Pages/MAP_ Hospital_Workgroup.aspx. 103 Measure Applications Partnership. 2020–2021 MAP Final Recommendations. Accessed on February 3, 2021 at: https://www.qualityforum.org/ Setting_Priorities/Partnership/Measure_ Applications_Partnership.aspx. 104 Measure Applications Partnership. 2020–2021 MAP Final Recommendations. Accessed on February 23, 2021 at: https://www.qualityforum.org/ Project_Pages/MAP_Hospital_Workgroup.aspx. 105 Ibid. PO 00000 Frm 00025 Fmt 4701 Sfmt 4702 19503 independent data collection systems. In initial analyses of the first month of vaccination, the number of healthcare workers vaccinated in approximately 1,200 facilities, which had data from both systems the number of healthcare personnel vaccinated was highly correlated between these 2 systems with a correlation coefficient of nearly 90 percent in the second two weeks of reporting.106 The MAP further noted that the measure would add value to the program measure set by providing visibility into an important intervention to limit COVID–19 infections in healthcare personnel and the patients for whom they provide care.107 We value the recommendations of the MAP and considered these recommendations carefully. Section 1890A(a)(4) of the Act requires the Secretary to take into consideration input from multi-stakeholder groups in selecting certain quality and efficiency measures. While we value input from the MAP, we believe it is important to propose the measure as quickly as possible to address the urgency of the COVID–19 PHE and its impact on vulnerable populations, including IPFs. CMS continues to engage with the MAP to mitigate concerns and appreciates the MAP’s conditional support for the measure. (3). NQF Endorsement Under section 1886(s)(4)(D)(i) of the Act, unless the exception of clause (ii) applies, measures selected for the quality reporting program must have been endorsed by the entity with a contract under section 1890(a) of the Act. The NQF currently holds this contract. Section 1886(s)(4)(D)(ii) of the Act provides an exception to the requirement for NQF endorsement of measures: In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. This measure is not NQF endorsed and has not been submitted to NQF for 106 For more information on testing results and other measure updates, please see the Meeting Materials (including Agenda, Recording, Presentation Slides, Summary, and Transcript) of the March 15, 2021 meeting available at https:// www.qualityforum.org/ProjectMaterials.aspx? projectID=75367. 107 Measure Applications Partnership. 2020–2021 MAP Final Recommendations. Accessed on February 23, 2021 at: https://www.qualityforum.org/ Project_Pages/MAP_Hospital_Workgroup.aspx. E:\FR\FM\13APP2.SGM 13APP2 19504 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules endorsement consideration. CMS will consider the potential for future NQF endorsement as part of its ongoing work with the MAP. Because this measure is not NQFendorsed, we considered other available measures. We found no other feasible and practical measures on the topic of COVID–19 vaccination among HCP, therefore, we believe the exception in Section 1186(s)(4)(D)(ii) of the Act applies. jbell on DSKJLSW7X2PROD with PROPOSALS2 c. Data Collection, Submission and Reporting 108 Centers for Disease Control and Prevention. Surveillance for Weekly HCP COVID–19 Vaccination. Accessed at: https://www.cdc.gov/ nhsn/hps/weekly-covid-vac/. on February 10, 2021. 19:14 Apr 12, 2021 Jkt 253001 3. Proposed Adoption of the Follow-Up After Psychiatric Hospitalization (FAPH) Measure for the FY 2024 Payment Determination and Subsequent Years a. Background Given the time-sensitive nature of this measure considering the PHE, we are proposing that IPFs would be required to begin reporting data on the proposed COVID–19 Vaccination Coverage Among HCP measure beginning October 1, 2021 for the FY 2023 IPFQR Program year. Thereafter, we propose annual reporting periods. To report this measure facilities would report COVID–19 vaccination data to the NHSN for at least one week each month, beginning in October 2021 for the October 1, 2021 through December 31, 2021 reporting period affecting FY 2023 payment determination and continuing for each quarter in subsequent years. For more details on data submission, we refer readers to section V.J.2.a of this proposed rule. If our proposal to adopt this measure is finalized, IPFs would report the measure through the CDC National Healthcare Safety Network (NHSN) webbased surveillance system.108 While the IPFQR Program does not currently require use of the NHSN web-based surveillance system, we have previously required use of this system. We refer readers to the FY 2015 IPF PPS final rule in which we adopted the Influenza Vaccination Coverage Among Healthcare Personnel (NQF #0431) measure for additional information on reporting through the NHSN web-based surveillance system (79 FR 45968 through 45970). IPFs would report COVID–19 vaccination data in the NHSN Healthcare Personnel Safety (HPS) Component by reporting the number of HCP eligible to have worked at the facility that week (denominator) and the number of those HCP who have received a completed vaccination course of a COVID–19 vaccination (numerator). For additional information about the data VerDate Sep<11>2014 reporting requirements, see V.J.4. of this proposed rule. We invite public comment on our proposal to add a new measure, COVID– 19 Vaccination Coverage Among HCP, to the IPFQR Program for the FY 2023 payment determination and subsequent years. We are proposing one new measure, Follow-Up After Psychiatric Hospitalization (FAPH), for the FY 2024 payment determination and subsequent years. The FAPH measure would use Medicare fee-for-service (FFS) claims to determine the percentage of inpatient discharges from an inpatient psychiatric facility (IPF) stay with a principal diagnosis of select mental illness or substance use disorders (SUDs) for which the patient received a follow-up visit for treatment of mental illness or SUD. Two rates would be calculated for this measure: (1) The percentage of discharges for which the patient received follow-up within 7 days of discharge, and; (2) the percentage of discharges for which the patient received follow-up within 30 days of discharge. The proposed FAPH measure is an expanded and enhanced version of the Follow-Up After Hospitalization for Mental Illness (FUH, NQF #0576) measure currently in the IPFQR Program. We are proposing to adopt the FAPH measure and replace the FUH measure and refer readers to section IV.F.2.d of this proposed rule for our proposal to remove the FUH measure contingent on adoption of the FAPH measure. The FUH (NQF #0576) measure uses Medicare FFS claims to determine the percentage of inpatient discharges from an IPF stay with a principal diagnosis of select mental illness diagnoses for which the patient received a follow-up visit for treatment of mental illness, and it excludes patients with primary substance use diagnoses. During the 2017 comprehensive review of NQF #0576, the NQF Behavioral Health Standing Committee (BHSC) recommended expanding the measure population to include patients hospitalized for drug and alcohol disorders, because these patients also require follow-up care after they are discharged. In 2018, CMS began development of a measure to expand the IPFQR FUH population to include patients with principal SUD diagnoses PO 00000 Frm 00026 Fmt 4701 Sfmt 4702 to address the NQF BHSC recommendation and the CMS Meaningful Measures priority to promote treatment of SUDs. The FAPH measure would expand the number of discharges in the denominator by about 35 percent over the current FUH measure by adding patients with SUD or dementia, populations that also benefit from timely follow-up care. Furthermore, compared to the criteria for provider type in the current FUH measure, the FAPH measure does not limit the provider type for the follow-up visit if it is billed with a diagnosis of mental illness or SUD. During the measure’s testing, the most frequent provider types for the FAPH measure were family or general practice physicians, internal medicine physicians, nurse practitioners, and physician assistants. The technical expert panel (TEP) convened by our contractor agreed that these provider types should be credited by the measure for treating mental illness and SUD and confirmed that this is aligned with integrated care models that aim to treat the whole patient. The TEP further noted that in areas where there are shortages of mental health or SUD clinicians, other types of providers are often the only choice for follow-up treatment. Allowing visits to these types of providers to count towards the numerator allows the measure to capture the rates of appropriate followup care more accurately in areas with provider shortages. Performance on the FAPH measure indicates that follow-up rates for patients hospitalized with mental illness or SUD are less than optimal and that room for improvement is ample. The clinical benefits of timely follow-up care after hospitalization, including reduced risk of readmission and improved adherence to medication, are well-documented in the published literature.109 110 111 112 113 114 115 109 Tong, L., Arnold, T., Yang, J., Tian, X., Erdmann, C., & Esposito, T. (2018). The association between outpatient follow-up visits and all-cause non-elective 30-day readmissions: A retrospective observational cohort study. PloS one, 13(7), e0200691. https://doi.org/10.1371/ journal.pone.0200691. 110 Terman, S.W., Reeves, M.J., Skolarus, L.E., & Burke, J.F. (2018). Association Between Early Outpatient Visits and Readmissions After Ischemic Stroke. Circulation. Cardiovascular quality and outcomes, 11(4), e004024. https://doi.org/10.1161/ CIRCOUTCOMES.117.004024. 111 First Outpatient Follow-Up After Psychiatric Hospitalization: Does One Size Fit All? (2014). Psychiatric Services, 66(6), 364–372. https:// doi.org/10.1176/appi.ps.201400081. 112 Terman, S.W., Reeves, M.J., Skolarus, L.E., & Burke, J.F. (2018). Association Between Early Outpatient Visits and Readmissions After Ischemic Stroke. Circulation. Cardiovascular quality and E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 Behavioral health patients in particular have a number of risk factors that underscore the need for timely follow-up and continuity of care: Behavioral health patients have higher baseline hospitalization rates, higher hospital readmission rates, and higher health care costs as compared with the general population of patients.116 117 Among patients with serious mental illness, 90 percent have comorbid clinical conditions such as hypertension, cardiovascular disease, hyperlipidemia, or diabetes.118 Among patients hospitalized for general medical conditions, those who also have a mental illness are 28 percent more likely to be readmitted within 30 days than their counterparts without a psychiatric comorbidity.119 The high prevalence of clinical comorbidities among behavioral health patients, combined with the compounding effect of mental illness on patients with general medical conditions, suggests that behavioral health patients are uniquely vulnerable and supports the intent of the measure to increase followup after hospitalization. In addition, clinical practice guidelines stress the importance of continuity of care between settings for patients with mental illness and SUD. For the treatment of SUD patients, the 2010 guidelines of the American outcomes, 11(4), e004024. https://doi.org/10.1161/ CIRCOUTCOMES.117.004024. 113 Jackson, C., Shahsahebi, M., Wedlake, T., & DuBard, C.A. (2015). Timeliness of outpatient follow-up: An evidence-based approach for planning after hospital discharge. Annals of family medicine, 13(2), 115–122. https://doi.org/10.1370/ afm.1753. 114 Hernandez, A.F., Greiner, M.A., Fonarow, G.C., Hammill, B.G., Heidenreich, P.A., Yancy, C.W., Peterson, E.D., & Curtis, L.H. (2010). Relationship between early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure. JAMA, 303(17), 1716–1722. https://doi.org/10.1001/ jama.2010.533. 115 Nadereh Pourat, Xiao Chen, Shang-Hua Wu and Anna C. Davis. Timely Outpatient Follow-up Is Associated with Fewer Hospital Readmissions among Patients with Behavioral Health Conditions. The Journal of the American Board of Family Medicine. May 2019, 32 (3) 353–361; DOI: https:// doi.org/10.3122/jabfm.2019.03.180244. 116 Germack, H.D., et al. (2019, January). Association of comorbid serious mental illness diagnosis with 30-day medical and surgical readmissions. JAMA Psychiatry. 117 First Outpatient Follow-Up After Psychiatric Hospitalization: Does One Size Fit All? (2014). Psychiatric Services, 66(6), 364–372. https:// doi.org/10.1176/appi.ps.201400081. 118 First Outpatient Follow-Up After Psychiatric Hospitalization: Does One Size Fit All? (2014). Psychiatric Services, 66(6), 364–372. https:// doi.org/10.1176/appi.ps.201400081. 119 Benjenk, I., & Chen, J. (2018). Effective mental health interventions to reduce hospital readmission rates: A systematic review. Journal of hospital management and health policy, 2, 45. https:// doi.org/10.21037/jhmhp.2018.08.05. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 Psychiatric Association (APA) state: ‘‘It is important to intensify the monitoring for substance use during periods when the patient is at a high risk of relapsing, including during the early stages of treatment, times of transition to less intensive levels of care, and the first year after active treatment has ceased.’’ 120 This statement is accompanied by a grade of [I], which indicates the highest level of APA endorsement: ‘‘recommended with substantial clinical evidence.’’ Evidence supports that outpatient follow-up care and interventions after hospital discharges are associated with a decreased risk of readmissions for patients with mental illness.121 122 IPFs can influence rates of follow-up care for patients hospitalized for mental illness or SUD. Three studies reported that with certain interventions—such as predischarge transition interviews, appointment reminder letters or reminder phone calls, meetings with outpatient clinicians before discharge, and meetings with inpatient staff familiar to patients at the first postdischarge appointment—facilities achieved 30-day follow-up rates of 88 percent or more.123 124 125 This is substantially higher than the national rate of about 52 percent observed in the current FUH measure for Medicare FFS discharges between July 1, 2016, and June 30, 2017.126 Medicare FFS data from July 1, 2016, to June 30, 2017, 120 American Psychiatric Association. Practice guideline for the treatment of patients with substance use disorders. 2010. https:// psychiatryonline.org/pb/assets/raw/sitewide/ practice_guidelines/guidelines/substanceuse.pdf. 121 Kurdyak P, Vigod SN, Newman A, Giannakeas V, Mulsant BH, Stukel T. Impact of Physician Follow-Up Care on Psychiatric Readmission Rates in a Population-Based Sample of Patients With Schizophrenia. Psychiatr Serv. 2018;69(1):61–68. doi: 10.1176/appi.ps.201600507. 122 Marcus SC, Chuang CC, Ng-Mak DS, Olfson M. Outpatient follow-up care and risk of hospital readmission in schizophrenia and bipolar disorder. Psychiatr Serv. 2017;68(12):1239–1246. doi: 10.1176/appi.ps.201600498. 123 Batscha C, McDevitt J, Weiden P, Dancy B. The effect of an inpatient transition intervention on attendance at the first appointment post discharge from a psychiatric hospitalization. J Am Psychiatr Nurses Assoc. 2011;17(5):330–338. doi: 10.1177/ 1078390311417307. 124 Agarin T, Okorafor E, Kailasam V, et al. Comparing kept appointment rates when calls are made by physicians versus behavior health technicians in inner city hospital: Literature review and cost considerations. Community Ment Health J. 2015;51(3):300–304. doi: 10.1007/s10597–014– 9812–x. 125 Olfson M, Mechanic D, Boyer CA, Hansell S. Linking inpatients with schizophrenia to outpatient care. Psychiatr Serv. 1998;49(7):911–917. doi: 10.1176/ps.49.7.911. Quality AFHRA. 2017 National Healthcare Quality and Disparities Report. Rockville, MD: Services USDoHaH; 2018. 126 https://data.cms.gov/provider-data/archiveddata/hospitals’’. PO 00000 Frm 00027 Fmt 4701 Sfmt 4702 19505 show the national 7-day follow-up rate to be 35.5 percent and the 30-day rate to be 61.0 percent. These data reveal wide variation in follow-up rates across facilities, with a 16.9 percent absolute difference between the 25th and 75th percentiles for the 7-day rate and a 17.4 percent absolute difference for the 30day rate. If all facilities achieved the benchmark follow-up rates for their Medicare FFS patients (as calculated using the AHRQ Achievable Benchmarks of Care method),127 53,841 additional discharges would have a 7day follow-up visit, and 47,552 would have a 30-day follow-up visit.128 During the development process, we used the CMS Quality Measures Public Comment Page to ask for public comments on the measure.129 We accepted public comments from Friday, January 25, 2019, to Wednesday, February 13, 2019. During this period, we received comments from 29 organizations or individuals. Many commenters acknowledged the importance of developing a measure that assesses acute care providers for follow-up post-hospitalization. Some commenters expressed skepticism about the measure’s appropriateness as a tool for evaluating the performance of discharging IPFs due to factors beyond the IPFs’ control that can affect whether a patient receives timely post-discharge follow-up care. Ten stakeholders expressed support for the measure based on the expanded list of qualifying diagnoses in the denominator and the inclusion of more patients who could benefit from post-discharge follow-up visits.130 We reviewed the comments we received with the TEP, whose members shared similar feedback regarding the importance of follow-up for patients with both mental health diagnoses and substance use disorders, as well as concerns about the ability of IPFs to influence follow-up care. We agree with commenters that some factors that influence follow-up are outside of a facility’s control. However, as described, in section IV.E.3.a, we believe that there are interventions (such as pre-discharge transition interviews, appointment reminder letters or reminder phone calls, meetings with outpatient 127 https://nhqrnet.ahrq.gov/inhqrdr/resources/ methods#Benchmarks. 128 Quality AfHRa. 2017 National Healthcare Quality and Disparities Report. Rockville, MD: Services USDoHaH; 2018. 129 https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/MMS/ Downloads/IPF_-Follow-Up-After-PsychiatricHospitalization_Public-Comment-Summary.pdf. 130 Mathematica. FAPH public comment summary. April 2019. E:\FR\FM\13APP2.SGM 13APP2 19506 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules clinicians before discharge, and meetings with inpatient staff familiar to patients at the first post-discharge appointment) that allow facilities to improve their follow-up adherence. We remain committed to monitoring followup to improve health outcomes and view this measure as an expansion of our ability to measure appropriate follow-up care established by FUH. b. Overview of Measure (1). Measure Calculation The FAPH measure would be calculated by dividing the number of discharges that meet the numerator criteria by the number that meet the denominator criteria. Two rates are reported for this measure: The 7-day rate and the 30-day rate. (a) Numerator The first rate that would be reported for this measure includes discharges from a psychiatric facility that are followed by an outpatient visit for treatment of mental illness or SUD within 7 days. The second rate reported for this measure would include discharges from a psychiatric facility that are followed by an outpatient visit for treatment of mental illness or SUD within 30 days. Outpatient visits are defined as outpatient visits, intensive outpatient encounters, or partial hospitalization and are defined by the Current Procedural Terminology (CPT), Healthcare Common Procedure Coding System (HCPCS), and Uniform Billing (UB) Revenue codes. Claims with codes for emergency room visits do not count toward the numerator. jbell on DSKJLSW7X2PROD with PROPOSALS2 (b) Denominator The denominator includes discharges paid under the IPF prospective payment system during the performance period for Medicare FFS patients with a principal diagnosis of mental illness or SUD. Specifically, the measure includes IPF discharges for which the patient was: • Discharged with a principal diagnosis of mental illness or SUD that would necessitate outpatient follow-up care, • Alive at the time of discharge, • Enrolled in Medicare Parts A and B during the month of the discharge date and at least one month after the discharge date to ensure that data are available to capture the index admission and follow-up visits, and • Age 6 or older on the date of discharge, because follow-up treatment for mental illness or SUD might not always be recommended for younger children. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 The denominator excludes IPF discharges for patients who: • Were admitted or transferred to acute and non-acute inpatient facilities within the 30-day follow-up period, because admission or transfer to other institutions could prevent an outpatient follow-up visit from taking place, • Were discharged against medical advice, because the IPF could have limited opportunity to complete treatment and prepare for discharge, • Died during the 30-day follow-up period, or • Use hospice services or elect to use a hospice benefit at any time during the measurement year regardless of when the services began, because hospice patients could require different followup services. The FAPH measure differs from FUH mostly in the expansion of the measure population to include SUD and other mental health diagnoses in the measure’s denominator, but it includes some additional differences: • The FAPH measure simplifies the exclusion of admission or transfer to acute or non-acute inpatient facilities within 30 days after discharge by aligning with the HEDIS® Inpatient Stay Value Set used in both the HEDIS® FUH and the HEDIS® Follow-Up After Emergency Department Visit for Alcohol and Other Drug Abuse or Dependence (FUA) measures to identify acute and non-acute inpatient stays. A discharge is excluded from the FAPH measure if it is followed by an admission or a transfer with one of the codes in the value set. • The FAPH measure uses Medicare UB Revenue codes (rather than inpatient discharge status code, which the FUH measure uses) to identify discharge or transfer to other health care institutions. This is to align better with the intent of the HEDIS® FUH and HEDIS® FUA measures. • The FAPH measure allows mental illness or SUD diagnoses in any position on the follow-up visit claim to count toward the numerator and does not require that it be in the primary position as the FUH measure does. (2) Measure Reliability and Validity In 2019, CMS used the final measure specifications to complete reliability and validity testing, which revealed that the FAPH measure provides reliable and valid facility-level rates of follow-up after psychiatric hospitalization. We evaluated measure reliability based on a signal-to-noise analysis,131 in which a score of 0.0 implies that all variation is 131 For additional information on reliability tests see https://www.qualityforum.org/Measuring_ Performance/Improving_NQF_Process/Measure_ Testing_Task_Force_Final_Report.aspx. PO 00000 Frm 00028 Fmt 4701 Sfmt 4702 attributed to measurement error (noise), and a score of 1.0 implies that all measure score variation is caused by a real difference in performance across IPFs. Using that approach, we established a minimum denominator size of 40 discharges to attain an overall reliability score of 0.7 for both the 7-day and the 30-day rate. These analyses revealed that the measure can reliably distinguish differences in performance between IPFs with adequate denominator size. We evaluated the validity of the measure based on its correlation to two conceptually related measures in the IPFQR Program: The 30-Day All-Cause Unplanned Readmission After Psychiatric Discharge from an IPF (IPF Readmission) measure, and the Medication Continuation Following Inpatient Psychiatric Discharge (Medication Continuation) measure. We observed a weak negative correlation between FAPH and the IPF Readmission measure for both 7-day (¥0.11) and 30day (¥0.18) measure rates. This negative correlation is expected because a higher score is indicative of better quality of care for the FAPH, while a lower score is indicative of better quality of care for the IPF readmission measure (that is, a lower rate of unplanned readmissions). High rates of follow-up after visits after discharge and low rates of unplanned readmissions both indicate good care coordination during the discharge process. We observed a weak positive correlation between the 7-day FAPH measure rate and the Medication Continuation measure (0.32), and between the 30-day FAPH measure rate and the Medication Continuation measure (0.42). This result is expected because for both the FAPH and the Medication Continuation measures higher scores are indicative of better-quality care. Follow-up visits after discharge and continuation of medication after discharge both indicate good care coordination during the discharge process. After reviewing these results and the proposed measure specifications, all 13 TEP members who were present agreed that the measure had face validity.132 132 Face validity is defined as a subjective determination by experts that the measure appears to reflect quality of care, done through a systematic and transparent process, that explicitly addresses whether performance scores resulting from the measure as specified can be used to distinguish good from poor quality, with degree of consensus and any areas of disagreement provided/discussed: https://www.qualityforum.org/Measuring_ Performance/Scientific_Methods_Panel/Docs/ Evaluation_Guidance.aspx. E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules (3) Review by the Measure Applications Partnership and NQF Under section 1890A(a)(2) of the Act, this measure was included in a publicly available document: ‘‘List of Measures Under Consideration for December 1, 2019,’’ available at: https:// www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/QualityMeasures/ Downloads/Measures-underConsideration-List-for-2018.pdf. On January 15, 2020, the MAP Coordinating Committee rated the measure as ‘‘Conditional Support for Rulemaking’’ contingent upon NQF endorsement. We submitted the measure to the NQF for endorsement in the spring 2020 cycle. However, some members of the NQF Behavioral Health and Substance Use Standing Committee were concerned about the measure’s exclusions for patients who died during the 30-day follow-up period or who were transferred. In addition, some members objected to combining persons with a diagnosis of SUD and those with a diagnosis for a mental health disorder into a single measure of follow-up care. Therefore, the NQF declined to endorse this measure. We noted that the exclusions for patients who died or who were admitted or transferred to an acute or non-acute inpatient facility during the 30-day follow up period align with the FUH measure currently in the IPFQR Program. Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure for the IPFQR Program that is not endorsed by NQF. The exception to the requirement to specify an endorsed measure states that in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization. The FAPH measure is not NQF endorsed. We have reviewed NQFendorsed and other consensus-endorsed measures related to follow-up care and identified the FUH measure (NQF #0576) currently in the IPFQR Program and Continuity of Care after Inpatient or |Residential Treatment for SUD (NQF #3453). We believe that the FAPH measure is an improvement over the current FUH measure and over the Continuity of Care after Inpatient or Residential Treatment of Substance Use Disorder because we believe that it is VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 important to ensure appropriate access to follow-up treatment for the largest patient population possible and the FAPH measure applies to a larger patient population than either of the measures we considered. Therefore, we propose to adopt the FAPH measure described in this section for the FY 2024 payment determination and subsequent years. c. Data Collection, Submission and Reporting FAPH uses Medicare FFS Part A and Part B claims that are received by Medicare for payment purposes. The measure links Medicare FFS claims submitted by IPFs and subsequent outpatient providers for Medicare FFS IPF discharges. Therefore, no additional data collection would be required from IPFs. For additional information on data submission for this measure, see section IV.J.2.b of this proposed rule. The performance period used to identify cases in the denominator is 12 months. Data from this period and 30 days afterward are used to identify follow-up visits in the numerator. Consistent with other claims-based measures in the IPFQR Program, the performance period for this measure is July 1 through June 30. For example, for the FY 2024 payment determination, the performance period will include discharges between July 1, 2021 and June 30, 2022.133 We invite public comment on our proposal to add a new measure, FollowUp After Psychiatric Hospitalization, to the IPFQR Program, beginning with the FY 2024 payment determination and subsequent years. F. Removal or Retention of IPFQR Program Measures 1. Background In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through 38465), we adopted considerations for removing or retaining measures within the IPFQR Program and criteria for determining when a measure is ‘‘topped out.’’ In the FY 2019 IPF PPS final rule (83 FR 38591 through 38593), we adopted one additional measure removal factor. We are not proposing any changes to these removal factors, topped-out criteria, or retention factors and refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through 38465) and the FY 2019 IPF PPS final rule (83 FR 38591 133 If data availability or operational issues prevent use of this performance period, we would announce the updated performance period through subregulatory communications including announcement on a CMS website and/or on our applicable listservs. PO 00000 Frm 00029 Fmt 4701 Sfmt 4702 19507 through 38593) for more information. We will continue to retain measures from each previous year’s IPFQR Program measure set for subsequent years’ measure sets, except when we specifically propose to remove or replace a measure. We will continue to use the notice-and-comment rulemaking process to propose measures for removal or replacement, as we described upon adopting these factors in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38464 through 38465). In our continual evaluation of the IPFQR Program measure set under our Meaningful Measures Framework and according to our measure removal and retention factors, we identified four measures that we believe are appropriate to propose removing from the IPFQR Program for the FY 2024 payment determination and subsequent years. Our discussion of these measures follows. 2. Measures for Removal a. Proposal To Remove Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention (SUB–2/2a) Beginning With FY 2024 Payment Determination We are proposing to remove the Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention (SUB–2/2a) measure from the IPFQR Program beginning with the FY 2024 payment determination under our measure removal Factor 8, ‘‘The costs associated with a measure outweigh the benefit of its continued use in the program.’’ We adopted the Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention (SUB–2/2a) measure in the FY 2016 IPF PPS final rule (80 FR 46699 through 46701) because we believe it is important to address the common comorbidity of alcohol use among IPF patients. This measure requires facilities to chart-abstract measure data on a sample of IPF patient records, in accordance with established sampling policies (80 FR 46717 through 46719). We have previously stated our intent to move away from chart-abstracted measures to reduce information collection burden in this and other CMS quality programs (78 FR 50808; 79 FR 50242; 80 FR 49693). When we adopted the SUB–2/2a measure to the IPFQR Program, the benefits of this measure were high because facility performance was not consistent. Therefore, the measure provided a means of distinguishing facility performance and incentivized facilities to improve rates of treatment for this common comorbidity. Between the FY 2018 E:\FR\FM\13APP2.SGM 13APP2 19508 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules payment determination (the first year that SUB–2/2a was included in the IPFQR Program measure set) and the FY 2019 payment determination, we saw substantial performance improvement on the SUB–2 measure (which is the portion of the SUB–2/2a measure that assess whether the facility provided or offered a brief intervention for alcohol use). However, for the FY 2019 and FY 2020 payment determinations, that improvement has leveled off to consistently high performance, as indicated in Table 2. These data further show that at this time there is little room for improvement in the SUB 2 measure, and that the quality improvement benefits from the measure have greatly diminished. We continue to believe that alcohol use is an important comorbidity to address in the IPF setting, and that brief interventions are a key component of addressing this comorbidity. However, based on these data, we believe that most IPFs routinely offer alcohol use brief interventions, and that IPFs will continue to offer these interventions to patients, regardless of whether the SUB– 2/2a measure is in the IPFQR Program measure set, because it has become an embedded part of their clinical workflows. TABLE 2—PERFORMANCE ANALYSIS FOR ALCOHOL USE BRIEF INTERVENTION PROVIDED OR OFFERED (SUB–2) Year Mean jbell on DSKJLSW7X2PROD with PROPOSALS2 2016 (2018 Payment Determination) ................................... 2017 (2019 Payment Determination) ................................... 2018 (2020 Payment Determination) ................................... While the measure does not meet our criteria for ‘‘topped-out’’ status because of the TCV higher than 0.1, we believe that this measure no longer meaningfully supports the program objectives of informing beneficiary choice and driving improvement in IPF interventions for alcohol use because it is no longer showing significant improvement in facility performance (that is, in providing or offering alcohol use brief interventions). Furthermore, as we stated in the FY 2019 IPF PPS final rule, costs are multi-faceted and include not only the burden associated with reporting, but also the costs associated with implementing and maintaining the program (83 FR 38592). For example, it may be costly for health care providers to maintain general administrative knowledge to report this measure. Additionally, CMS must expend resources in maintaining information collection systems, analyzing reported data, and providing public reporting of the collected information. Here, IPF information collection burden and related costs associated with reporting the SUB 2/2a measure to CMS are high because it is a chart-abstracted measure. Furthermore, CMS incurs costs associated with the program oversight of the measure for public display. As a result, we believe that the costs and burdens associated with this chartabstracted measure outweigh the benefit of its continued use in the program. Therefore, we are proposing to remove the Alcohol Use Brief VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 75th percentile Median 66.96 77.11 79.49 77 88 91 Intervention Provided or Offered and Alcohol Use Brief Intervention (SUB–2/ 2a) measure from the IPFQR Program beginning with the FY 2024 payment determination. We welcome public comments on our proposal to remove the SUB–2/2a measure from the IPFQR Program. b. Proposal To Remove Tobacco Use Brief Intervention Provided or Offered and Tobacco Use Brief Intervention (TOB–2/2a) Beginning With FY 2024 Payment Determination We are proposing to remove the Tobacco Use Brief Intervention Provided or Offered and Tobacco Use Brief Intervention (TOB–2/2a) measure from the IPFQR Program beginning with the FY 2024 payment determination under our measure removal Factor 8, ‘‘The costs associated with a measure outweigh the benefit of its continued use in the program.’’ We adopted the Tobacco Use Brief Intervention Provided or Offered and Tobacco Use Brief Intervention (TOB–2/2a) measure in the FY 2015 IPF PPS final rule (79 FR 45971 through 45972) because we believe it is important to address the common comorbidity of tobacco use among IPF patients. Like SUB–2/2a described in the previous subsection, this measure requires facilities to chartabstract measure data on a sample of IPF patient records, in accordance with established sampling policies (80 FR 46717 through 46719). When we introduced the TOB–2/2a measure to PO 00000 Frm 00030 Fmt 4701 Sfmt 4702 96 99 100 90th percentile 100 100 100 Truncated coefficient of variation (TCV) 0.49 0.28 0.25 the IPFQR Program, the benefits of this measure were high, because facility performance was not consistent and therefore the measure provided a means of distinguishing facility performance and incentivized facilities to improve rates of treatment for this common comorbidity. Between the FY 2017 payment determination (the first year that TOB–2/2a was included in the IPFQR Program’s measure set) and the FY 2019 payment determination we saw substantial performance improvement on TOB–2. However, between the FY 2019 and FY 2020 payment determinations, that improvement has leveled off to consistently high performance, as indicated in Table 3. These data further show that currently there is little room for improvement in the TOB–2 measure, and that the quality improvement benefits from the measure have greatly diminished. We continue to believe that tobacco use is an important comorbidity to address in the IPF setting, and that brief interventions are a key component of addressing this comorbidity. However, based on these data, we believe that most IPFs routinely offer tobacco use brief interventions, and that IPFs will continue to offer these interventions to patients, regardless of whether the TOB–2/2a measure is in the IPFQR Program measure set, because it has become an embedded part of their clinical workflows. E:\FR\FM\13APP2.SGM 13APP2 19509 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules TABLE 3—PERFORMANCE ANALYSIS FOR TOBACCO USE BRIEF INTERVENTION PROVIDED OR OFFERED (TOB–2) Year 2015 2016 2017 2018 (2017 (2018 (2019 (2020 Payment Payment Payment Payment Mean Determination) Determination) Determination) Determination) ................................... ................................... ................................... ................................... jbell on DSKJLSW7X2PROD with PROPOSALS2 While the measure does not meet our criteria for ‘‘topped-out’’ status because of the TCV higher than 0.1, we believe that this measure no longer meaningfully supports the program objectives of informing beneficiary choice and driving improvement in IPF interventions for tobacco use because it is no longer showing significant improvement in facility performance (that is, in providing or offering tobacco use brief interventions). Furthermore, as we stated in the FY 2019 IPF PPS final rule, costs are multi-faceted and include not only the burden associated with reporting, but also the costs associated with implementing and maintaining the program (83 FR 38592). For example, it may be costly for health care providers to maintain general administrative knowledge to report this measure. Additionally, CMS must expend resources in maintaining information collection systems, analyzing reported data, and providing public reporting of the collected information. Here, IPF information collection burden and related costs associated with reporting this measure to CMS are high because the measure is a chart-abstracted measure. Furthermore, CMS incurs costs associated with the program oversight of the measure for public display. As a result, we believe that the costs and burdens associated with this chartabstracted measure outweigh the benefit of its continued use in the program. Therefore, we are proposing to remove the Tobacco Use Brief Intervention Provided or Offered and Tobacco Use Brief Intervention (TOB–2/ 2a) measure from the IPFQR Program beginning with the FY 2024 payment determination. We welcome public comments on our proposal to remove the TOB–2/2a measure from the IPFQR Program. c. Proposal To Remove Timely Transmission of Transition Record (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care) Beginning With FY 2024 Payment Determination We are proposing to remove the Timely Transmission of Transition VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 Median 63.83 74.72 79.04 79.08 71.5 84 88 88 Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure from the IPFQR Program beginning with the FY 2024 payment determination under our measure removal Factor 8, ‘‘The costs associated with a measure outweigh the benefit of its continued use in the program.’’ We adopted the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure in the FY 2016 IPF PPS final rule (80 FR 46706 through 46709) because more timely communication of vital information regarding the inpatient hospitalization results in better care, reduction of systemic medical errors, and improved patient outcomes. The Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure builds on the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure, which requires facilities to provide a discharge record with 11 specified elements to patients at discharge. We continue to believe that the 11 elements required by the Transition Record with Specified Elements measure provide meaningful information about the quality of care provided by IPFs, and we are therefore not proposing to remove that measure from the IPFQR Program. However, we believe that the benefits of requiring facilities to transmit the discharge record with 11 specified elements to the next level care provided within 24 hours, as required by the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure, have been reduced. Reporting this measure requires facilities to chart-abstract measure data on a sample of IPF patient records, in accordance with established sampling policies (80 FR 46717 through 46719). On May 1, 2020, we updated the Conditions of Participation (CoPs) for PO 00000 Frm 00031 Fmt 4701 Sfmt 4702 75th percentile 90th percentile 91 95 97 98 99 100 100 100 Truncated coefficient of variation (TCV) 0.49 0.28 0.22 0.22 IPFs participating in the Medicare program in the Medicare and Medicaid Programs; Patient Protection and Affordable Care Act; Interoperability and Patient Access for Medicare Advantage Organization and Medicaid Managed Care Plans, State Medicaid Agencies, CHIP Agencies and CHIP Managed Care Entities, Issuers of Qualified Health Plans on the Federally Facilitated Exchanges, and Health Care Providers final rule (85 FR 25588). In the May 1, 2020 update to the CoPs, we adopted a requirement for psychiatric hospitals that possess EHR systems with the technical capacity to generate information for electronic patient event notifications to send electronic patient event notifications of a patient’s admission, discharge, and/or transfer to another health care facility or to another community provider at the time of a patient’s discharge or transfer. Because these updated CoP requirements overlap with, but are not the same as, the requirements for the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure (which requires transmission of a discharge record with 11 specified elements to the next level care provider within 24 hours of the patient’s discharge rather that requiring notification regarding the patient’s inpatient stay to be transmitted at discharge), we believe that the adoption of these updated CoPs increases the costs of the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure while decreasing its benefit. Specifically, we believe that the costs of this measure are increased because facilities to which the new CoPs apply (that is, facilities that possess EHR or other administrative systems with the technical capacity to generate information for electronic patient event notifications) could bear increased cost if they separately implement the patient event notifications meeting both the criteria for the updated CoPs and the capacity to share a transition record that meets the requirements of our measure. We E:\FR\FM\13APP2.SGM 13APP2 19510 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules note that the updated CoPs do not include the level of detail regarding data to be transferred at discharge that our Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires. While the set of information in the CoP notification policy is a minimal set of information, we believe that it would continue to be appropriate for providers to transmit the transition record that they will continue to be providing to patients under our Transition Record Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure. We believe the different requirements regarding both timeliness of notification and contents of notification could lead some providers to send two separate discharge notifications to meet the separate requirements. Further, we believe that the benefits of the measure are reduced because all facilities to which the new CoPs apply will be sending patient discharge information to the next level of care provider as required by the CoPs. Therefore, the benefits of this measure are reduced because it is less likely to ensure that these facilities provide patient discharge information to the next level care provider, and it is less likely to provide information to help consumers differentiate quality between facilities. While these updated CoPs do not directly address transmission of patient event notifications for facilities that do not possess EHR systems with patient event notification capabilities, such facilities should continue to transmit data using their existing infrastructure and timelines. Because we believe that the costs are now increased and the benefits are now reduced, we believe that the costs and burdens associated with this chartabstracted measure outweigh the benefit of its continued use in the IPFQR Program. Therefore, we are proposing to remove the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure from the IPFQR Program beginning with the FY 2024 payment determination. We welcome public comments on our proposal to remove the Timely Transmission of Transition Record measure from the IPFQR Program. d. Proposal To Remove Follow-Up After Hospitalization for Mental Illness (FUH, NQF #0576) Beginning With FY 2024 Payment Determination If we finalize adoption of the FollowUp After Psychiatric Hospitalization measure described in Section IV.E.3, we believe that our current measure removal Factor 3 would apply to the existing Follow-Up After Hospitalization for Mental Illness (FUH, NQF #0576) measure. Measure removal Factor 3 applies when a ‘‘measure can be replaced by a more broadly applicable measure (across settings or populations) or a measure that is more proximal in time to desired patient outcomes for the particular topics.’’ We adopted removal factor 3 in the FY 2017 IPPS/LTCH PPS final rule (82 FR 38463 through 38465). The proposed FAPH measure expands the patient population from patients with mental illness to also include patients with primary SUD diagnoses while addressing the same important aspect of care transitions. Because this FAPH measure uses the same methodology to address the same element of care for a broader patient population than the FUH measure, we believe that it is more broadly applicable across populations. Therefore, we are proposing to remove the FUH measure under measure removal Factor 3 only if we finalize our proposal to adopt of the FAPH measure. We note that if we do not adopt the FAPH measure, we will retain the FUH measure because we believe this measure addresses an important clinical topic. We welcome public comments on our proposal to remove FUH if we adopt FAPH. G. Summary of Previously Finalized and Newly Proposed Measures 1. Previously Finalized and Newly Proposed Measures for the FY 2023 Payment Determination and Subsequent Years There are 14 previously finalized measures for the FY 2023 payment determination and subsequent years. In this proposed rule, we are proposing to adopt one measure for the FY 2023 payment determination and subsequent years. The 15 measures which would be in the program if this proposal is finalized are shown in Table 4. jbell on DSKJLSW7X2PROD with PROPOSALS2 TABLE 4—IPFQR PROGRAM MEASURE SET FOR THE FY 2023 PAYMENT DETERMINATION AND SUBSEQUENT YEARS IF MEASURE ADOPTION IS FINALIZED AS PROPOSED NQF # Measure ID Measure 0640 ........ 0641 ........ 0560 ........ HBIPS–2 ..................................................... HBIPS–3 ..................................................... HBIPS–5 ..................................................... 0576 ........ N/A * ........ FUH ............................................................. SUB–2 and SUB–2a ................................... N/A * ........ SUB–3 and SUB–3a ................................... N/A * ........ N/A * ........ TOB–2 and TOB–2a ................................... TOB–3 and TOB–3a ................................... 1659 ........ N/A * ........ IMM–2 ......................................................... N/A .............................................................. N/A * ........ N/A .............................................................. N/A .......... 2860 ........ N/A .............................................................. N/A .............................................................. 3205 ........ Med Cont .................................................... Hours of Physical Restraint Use. Hours of Seclusion Use. Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. Follow-Up After Hospitalization for Mental Illness. Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention. Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a Alcohol and Other Drug Use Disorder Treatment at Discharge. Tobacco Use Treatment Provided or Offered and TOB–2a Tobacco Use Treatment. Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment at Discharge. Influenza Immunization. Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care). Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or any Other Site of Care). Screening for Metabolic Disorders. Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient Psychiatric Facility. Medication Continuation Following Inpatient Psychiatric Discharge. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 PO 00000 Frm 00032 Fmt 4701 Sfmt 4702 E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 19511 TABLE 4—IPFQR PROGRAM MEASURE SET FOR THE FY 2023 PAYMENT DETERMINATION AND SUBSEQUENT YEARS IF MEASURE ADOPTION IS FINALIZED AS PROPOSED—Continued NQF # Measure ID Measure TBD ......... COVID HCP ................................................ COVID–19 Healthcare Personnel (HCP) Vaccination Measure. * Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topics for the IPF setting. 2. Previously Finalized and Newly Proposed Measures for the FY 2024 Payment Determination and Subsequent Years There are 14 previously finalized measures for the FY 2024 payment determination and subsequent years. In this proposed rule, we are proposing to adopt one measure for the FY 2023 payment determination and subsequent years. Additionally, we are proposing to remove three measures and replace one measure for the FY 2024 payment determination and subsequent years. The 12 measures which would be in the program for FY 2024 payment determination and subsequent years if these proposals are finalized are shown in Table 5. TABLE 5—IPFQR PROGRAM MEASURE SET FOR THE FY 2024 PAYMENT DETERMINATION AND SUBSEQUENT YEARS IF ADOPTIONS AND REMOVALS ARE FINALIZED AS PROPOSED NQF # Measure ID Measure 0640 ........ 0641 ........ 0560 ........ HBIPS–2 ..................................................... HBIPS–3 ..................................................... HBIPS–5 ..................................................... N/A .......... 1659 ........ N/A * ........ FAPH ........................................................... IMM–2 ......................................................... SUB–3 and SUB–3a ................................... N/A * ........ TOB–3 and TOB–3a ................................... N/A * ........ N/A .............................................................. N/A .......... 2860 ........ N/A .............................................................. N/A .............................................................. 3205 ........ TBD ......... Med Cont .................................................... COVID HCP ................................................ Hours of Physical Restraint Use. Hours of Seclusion Use. Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. Follow-Up After Psychiatric Hospitalization. Influenza Immunization. Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a Alcohol and Other Drug Use Disorder Treatment at Discharge. Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment at Discharge. Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care). Screening for Metabolic Disorders. Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient Psychiatric Facility. Medication Continuation Following Inpatient Psychiatric Discharge. COVID–19 Healthcare Personnel (HCP) Vaccination Measure. * Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topics for the IPF setting. jbell on DSKJLSW7X2PROD with PROPOSALS2 H. Considerations for Future Measure Topics As we have previously indicated, we seek to develop a comprehensive set of quality measures to be available for widespread use for informed decisionmaking and quality improvement in the IPF setting (79 FR 45974 through 45975). Therefore, through future rulemaking, we intend to propose new measures for development or adoption that will help further our goals of achieving better healthcare and improved health for individuals who obtain inpatient psychiatric services through the widespread dissemination and use of quality information. In 2017, we introduced the Meaningful Measures Framework as a tool to foster operational efficiencies and reduce costs including collection and reporting VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 burden while producing quality measurement that is more focused on meaningful outcomes (83 FR 38591). As we continue to evolve the Meaningful Measures Framework, we have stated that we intend to better address health care priorities and gaps, emphasize digital quality measurement, and promote patient perspectives.134 As we work to align the IPFQR Program’s measure set with these priorities, we have identified the following areas that we believe are important to stakeholders, but which are not covered in the current IPFQR Program measure set: Patient Experience of Care, Functional Outcomes Measurement, and digital measures. As described in the following subsections, we are seeking 134 https://www.cms.gov/meaningful-measures20-moving-measure-reduction-modernization. PO 00000 Frm 00033 Fmt 4701 Sfmt 4702 public comment on each of these topics and other future measure considerations which stakeholders believe are important. 1. Patient Experience of Care Data Collection Instrument When we finalized removal of the Assessment of Patient Experience of Care attestation measure in the FY 2019 IPF PPS final rule (83 FR 38596) we stated that we believed we had collected sufficient information to inform development of a patient experience of care measure that would capture data on the results of such a survey. In the FY 2020 IPF PPS proposed rule (84 FR 16986 through 16987), we solicited input on how providers had implemented the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey in their E:\FR\FM\13APP2.SGM 13APP2 19512 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules jbell on DSKJLSW7X2PROD with PROPOSALS2 facilities. We also sought public comment on other potential surveys that commenters believed would be appropriate to adopt for the IPFQR Program. We received many comments on this subject, and many of these comments expressed that there is not one survey used predominantly across IPFs (84 FR 38467). Additional commenters expressed concerns that the HCAHPS survey may not be appropriate for the IPF setting because it does not include some of the unique aspects of inpatient psychiatric care including, group therapy, non-physician providers, and involuntary admissions. While we did not solicit public comment on this issue in the FY 2021 IPF PPS proposed rule, we received many comments addressing this issue (85 FR 47043). We continue to seek to identify a minimally burdensome patient experience of care instrument that would be appropriate for the IPF setting. Therefore, we are seeking public comment on instruments currently in use in the IPF setting, input on whether the HCAHPS survey may be appropriate for this setting, and information on how facilities that currently use the HCAHPS survey have addressed challenges with using this survey within this setting (that is, concerns regarding unique aspects of inpatient psychiatric care). 2. Functional Outcomes Instrument for Use in a Patient Reported Outcomes Measure When we introduced the Meaningful Measures Framework, we stated that we wanted to focus on meaningful outcomes (83 FR 38591). As we have assessed the IPFQR Program measure set against the Meaningful Measures Framework, we have identified functional outcomes as a potential gap area in the IPFQR Program’s measure set. Therefore, we are evaluating whether a patient reported outcomes measure that assesses functional outcomes, such as global functioning, interpersonal problems, psychotic symptoms, alcohol or drug use, emotional lability, and self-harm, would be an appropriate measure to include in the IPFQR program measure set. If we were to develop such a measure, we would develop a measure that compares a patient’s responses to a standardized functional outcomes assessment instrument at admission with the patient’s results on the same assessment instrument at discharge. We are seeking public comment on the value of such a measure in the IPFQR program measure set, what would be an appropriate functional outcome assessment instrument to use in the potential development of such a measure, and VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 any additional topics or concepts stakeholders believe would be appropriate for patient reported outcomes measures. 3. Measures for Electronic Data Reporting As we seek to improve digital measurement across our quality reporting and value-based payment programs, we are considering measures both within and appropriate to adopt for the IPFQR Program measure set that would be appropriate for digital data collection. In our assessment of the current measure set, we identified the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure as a potential option for digital data collection. We are seeking stakeholder input on the current data collection burden associated with this measure, concerns regarding potential electronic specification and data collection for this measure, and other measures that may be appropriate for electronic data collection, either those currently in the IPFQR Program measure set, or those that we could adopt in the future. I. Public Display and Review Requirements We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53653 through 53654), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through 50898), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 through 57249) for discussion of our previously finalized public display and review requirements. In this proposed rule, we are not proposing any changes to these requirements. J. Form, Manner, and Timing of Quality Data Submission for the FY 2022 Payment Determination and Subsequent Years 1. Procedural Requirements for the FY 2023 Payment Determination and Subsequent Years We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53654 through 53655), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50898 through 50899), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 through 38472) for our previously finalized procedural requirements. In this proposed rule, we are proposing to use the term ‘‘QualityNet security official’’ instead of ‘‘QualityNet system administrator,’’ proposing to revise § 412.434(b)(3) by replacing the term ‘‘QualityNet system administrator’’ with PO 00000 Frm 00034 Fmt 4701 Sfmt 4702 the term ‘‘QualityNet security official,’’ and clarifying our policy under the previously finalized requirement that hospitals ‘‘[i]dentify a QualityNet Administrator who follows the registration process located on the QualityNet website’’ (77 FR 53654). a. Proposal To Update Reference to QualityNet System Administrator and to No Longer Require Active Account To Qualify for Payment The previously finalized QualityNet security administrator requirements, including those for setting up a QualityNet account and the associated timelines, are described in the FY 2013 IPPS/LTCH final rule (77 FR 53654). In this proposed rule, we propose to use the term ‘‘QualityNet security official’’ instead of ‘‘QualityNet system administrator’’ to denote the exercise of authority invested in the role and align with the Hospital Outpatient Quality Reporting Program and other programs. The term ‘‘security official’’ would refer to ‘‘the individual(s)’’ who have responsibilities for security and account management requirements for a facility’s QualityNet account. To clarify, this proposed update in terminology would not change the individual’s responsibilities or add burden. We invite public comment on our proposal to replace the term ‘‘QualityNet system administrator’’ with ‘‘QualityNet security official.’’ Additionally, we are proposing to no longer require IPFs to maintain an active QualityNet security official account to qualify for payment. As we reviewed the requirements for the security official role and the basic user 135 role to identify the most appropriate language to describe the distinguishing authority invested in the security official role, we recognized that the QualityNet security official is not required for submitting data—a basic user can serve in this role—but remains necessary to set up QualityNet basic user accounts and for security purposes. Therefore, consistent with our proposal to adopt the security official term to differentiate the unique security authority and responsibilities of the role from the data submission responsibilities of the basic user role, we would continue to require a QualityNet basic user account to meet 135 We also noted that a basic user is a QualityNet user who (1) does not have the registration access described for security officials, (2) has the appropriate data entry roles and permissions for program participation, (3) can submit and review measures and non-measure data, (4) signs and submits the Data Accuracy Completeness Acknowledgement (DACA) form, and (5) refreshes their QualityNet account password every 180 days to ensure that the facility’s IPFQR Program Notice of Participation status is ‘‘Participating.’’ E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules IPFQR Program requirements, including data submission and administrative requirements, while recommending, but not requiring, that hospitals maintain an active QualityNet security official account. We welcome public comments on our proposal to no longer require facilities to maintain an active QualityNet security official account to qualify for payment. b. Proposal To Update Reference to QualityNet Administrator in Code of Federal Regulations In this proposed rule, we propose to revise our regulation at § 412.434(b)(3) by replacing ‘‘QualityNet system administrator’’ with ‘‘QualityNet security official.’’ The term ‘‘QualityNet security official’’ refers to the individual(s) who have responsibilities for security and account management requirements for a hospital’s QualityNet account. To clarify, this proposed update in terminology would not change the individual’s responsibilities or add burden. If finalized, the revised paragraph (b)(3) would read: ‘‘Contact information for the inpatient psychiatric facility’s chief executive officer and QualityNet security official, including each individual’s name, email address, telephone number, and physical mailing address.’’ We invite public comment on our proposal to replace the term ‘‘QualityNet system administrator’’ with ‘‘QualityNet security official’’ at § 412.434(b)(3). jbell on DSKJLSW7X2PROD with PROPOSALS2 2. Data Submission Requirements We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53655 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50899 through 50900), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472 through 38473) for our previously finalized data submission requirements. In this proposed rule, we are proposing to adopt one measure for the FY 2023 payment determination and subsequent years and one measure for the FY 2024 payment determination and subsequent years. Data submission requirements for each of these measures are described in the following subsections. Additionally, we are proposing to adopt patient level data submission for certain chart abstracted measures beginning with data submitted for the FY 2023 payment determination and subsequent years; details of this proposal are in subsection c. of this section. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 a. Data Submission Requirements for FY 2023 Payment Determination and Subsequent Years The measure we are proposing for FY 2023 payment determination and subsequent years (the COVID–19 HCP— Vaccination measure) requires facilities to report data on the number of HCP who have received completed vaccination course of a COVID–19 vaccine through the CDC’s National Healthcare Safety Network (NHSN). Specific details on data submission for this measure can be found in the CDC’s Overview of the Healthcare Safety Component, available at https:// www.cdc.gov/nhsn/PDFs/slides/NHSNOverview-HPS_Aug2012.pdf. For each CMS Certification Number (CCN), a percentage of the HCP who received a completed vaccine course of the COVID–19 vaccination will be calculated and publicly reported, so that the public will know what percentage of the HCP have been vaccinated in each IPF. For the COVID–19 HCP Vaccination measure, we are proposing that facilities would report the numerator and denominator for the COVID–19 HCP vaccination measure to the NHSN for at least one week each month, beginning in October 2021 for the October 1, 2021 through December 31, 2021 reporting period affecting the FY 2023 payment determination. If facilities report more than one week of data in a month, the most recent week’s data would be used to calculate the measure. Each quarter, the CDC would calculate a single quarterly result of COVID–19 vaccination coverage which would summarize the data submitted by IPFs for each of the three weeks of data submitted over the three month period. If finalized, CMS would publicly report the CDC’s quarterly summary of COVID–19 vaccination coverage for IPFs. We invite public comment on our proposal to require facilities to report the COVID–19 HCP vaccination measure. b. Data Submission Requirements for FY 2024 Payment Determination and Subsequent Years Because the Follow-Up After Psychiatric Hospitalization (FAPH) measure would be calculated by CMS using Medicare Fee-for-Service claims, there will be no additional data submission requirements for the FY 2024 payment determination and subsequent years. Therefore, we are not proposing any changes to our data submission policies associated with the proposal to adopt this measure. PO 00000 Frm 00035 Fmt 4701 Sfmt 4702 19513 c. Proposal To Adopt Patient-Level Reporting for Certain Chart-Abstracted Measures Beginning With FY 2024 Payment Determination and Subsequent Years In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 53657), we finalized that IPFs participating in the IPFQR Program must submit data to the Web-Based Measures Tool found in the Inpatient Psychiatric Facility section of the QualityNet website’s secure portal between July 1 and August 15 of each year. We noted that the data input forms within the Quality Net secure portal require submission of aggregate data for each separate quarter. In the FY 2014 IPPS/LTCH PPS final rule, we clarified our intent to require that IPFs submit aggregate data on measures on an annual basis via the Web-Based Measures Tool found in the IPF section of the Quality Net website’s secure portal and that the forms available require aggregate data for each separate quarter (78 FR 50899 through 50900). In the FY 2016 IPF PPS final rule (80 FR 46716), we updated our data submission requirements to require facilities to report data for chart-abstracted measures to the Web-Based Measures Tool on an aggregate basis by year, rather than by quarter. Additionally, we discontinued the requirement for reporting by age group. We updated these policies in the FY 2018 IPPS/ LTCH PPS final rule (82 FR 38472 through 38473) to change the specification of the submission deadline from exact dates to a 45-day submission period beginning at least 30 days following the end of the data collection period. In the FY 2019 IPF PPS final rule (83 FR 38607), we observed that reporting aggregate measure data increases the possibility of human error, such as making typographical errors while entering data, which cannot be detected by CMS or by data submission systems. We noted that unlike patient-level data reporting, aggregate measure data reporting does not allow for data accuracy validation, thereby lowering the ability to detect error. We stated that we were considering requiring patientlevel data reporting (data regarding each patient included in a measure and whether the patient was included in each numerator and denominator of the measure) of IPFQR measure data in the future. We sought public comment on including patient-level data collection in the IPFQR program. Several commenters expressed support for patient-level data collection, observing that it provides greater confidence in the data’s validity and reliability. Other E:\FR\FM\13APP2.SGM 13APP2 19514 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules commenters recommended that CMS use a system that has already been tested and used for IPF data reporting or work with IPFs in selecting a system so that any selected system would avoid additional burden. We believe that patient-level data reporting would improve the accuracy of the submitted and publicly reported data without increasing burden. As we considered the current IPFQR measure set, we determined that patient-level reporting of the Hours of Physical Restraint Use (HBIPS–2, NQF #0640) measure and Hours of Seclusion Use (HBIPS–2, NQF #0641) measure would be appropriate for the numerators of these measures only, because these measures are calculated with a denominator of 1,000 hours rather than a denominator of patients who meet specific criteria for inclusion in the measure. Therefore, we are proposing to require reporting patient-level information for the numerators of these measures only. For the remainder of the chart-abstracted measures in the IPFQR Program we are proposing to require patient-level reporting of the both the numerator and the denominator. Table 6 lists the proposed FY 2023 IPFQR measure set categorized by whether we would require patient-level data submission through the QualityNet secure portal. TABLE 6—PATIENT-LEVEL DATA SUBMISSION REQUIREMENTS FOR FY 2024 IPFQR PROGRAM MEASURE SET NQF # Measure ID Measure Patient-level data submission 0640 ........ 0641 ........ 0560 ........ HBIPS–2 ................................... HBIPS–3 ................................... HBIPS–5 ................................... 0576 ........ N/A * ........ FUH .......................................... SUB–2 and SUB–2a ................. N/A * ........ SUB–3 and SUB–3a ................. N/A * ........ TOB–2 and TOB–2a ................. N/A * ........ TOB–3 and TOB–3a ................. 1659 ........ N/A * ........ IMM–2 ....................................... N/A ............................................ N/A * ........ N/A ............................................ N/A .......... 2860 ........ N/A ............................................ N/A ............................................ 3205 ........ Med Cont .................................. TBD ......... COVID HCP .............................. Hours of Physical Restraint Use ................................................. Hours of Seclusion Use ............................................................... Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. Follow-Up After Hospitalization for Mental Illness ....................... Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention. Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a Alcohol and Other Drug Use Disorder Treatment at Discharge. Tobacco Use Treatment Provided or Offered and TOB–2a Tobacco Use Treatment. Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment at Discharge. Influenza Immunization ................................................................ Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care). Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or any Other Site of Care). Screening for Metabolic Disorders .............................................. Thirty-Day All-Cause Unplanned Readmission Following Psychiatric Hospitalization in an Inpatient Psychiatric Facility. Medication Continuation Following Inpatient Psychiatric Discharge. COVID–19 Healthcare Personnel (HCP) Vaccination Measure Yes, numerator only. Yes, numerator only. Yes. No (claims-based). Yes. Yes. Yes. Yes. Yes. Yes. Yes. Yes. No (claims-based). No (claims-based). No (calculated for HCP). jbell on DSKJLSW7X2PROD with PROPOSALS2 * Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topics for the IPF setting. Submission of aggregate data requires facilities to abstract patient-level data, then calculate measure performance prior to submitting data through the QualityNet website’s secure portal. For measures for which we would require patient-level data submission, we would allow facilities to submit data using a tool such as the CMS Abstraction & Reporting Tool (CART). This is the tool we use in our other quality reporting and value-based purchasing programs, and therefore, we believe that many facilities may already have familiarity with using this tool to abstract and report data. Additionally, the tool has been specifically designed to facilitate data reporting and minimize provider burden. We note that under aggregate data reporting, facilities submit aggregate VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 numerators and aggregate denominators for all measures to CMS in the Hospital Quality Reporting (HQR) system. These aggregate numerators and denominators are generally calculated by manually abstracting the medical record of each included patient using the algorithm, a paper tool, or a vendor abstraction tool. After each required medical record has been abstracted, the numerator and denominator results are added up and submitted as aggregate values in the HQR system. Under our patient level data reporting proposal, facilities would still manually abstract the medical record using either a vendor abstraction tool or an abstraction tool provided by CMS. The vendor abstraction tool or the CMS tool would then produce an individual XML file for each of the cases abstracted. Instead of submitting the PO 00000 Frm 00036 Fmt 4701 Sfmt 4702 aggregate data, the facility will log into HQR and upload batches of XML files that contain patient level data for each measure with data from all patients whose records were abstracted, and CMS would calculate the aggregate numerators, aggregate denominators, and measure rates from those XML file submissions. Because facilities must abstract patient-level data as one step in calculating measure results, we do not believe that requiring patient-level data submission will increase provider costs or burden associated with measure submission. Because we believe that patient-level data will improve the data accuracy without increasing provider burden, we are now proposing to adopt patient-level data reporting for numerators only for the Hours of Physical Restraint Use E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules (HBIPS–2, NQF #0640) and the Hours of Seclusion Use (HBIPS–3, NQF #0631) for numerators and denominators for the following 9 chart-abstracted IPFQR Program measures as detailed in Table 6: Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification (NQF #0560); Alcohol Use Brief Intervention Provided or Offered and SUB–2a Alcohol Use Brief Intervention; Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB–3a Alcohol and Other Drug Use Disorder Treatment at Discharge, Tobacco Use Treatment Provided or Offered and TOB–2a Tobacco Use Treatment, Tobacco Use Treatment Provided or Offered at Discharge and TOB–3a Tobacco Use Treatment at Discharge, Influenza Immunization (NQF #1659), Transition Record with Specified Elements Received by Discharged Patients (discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care), Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or any Other Site of Care), and Screening for Metabolic Disorders. We believe that it is appropriate to transition to patient-level reporting incrementally. This would allow facilities to become familiar with the data submission systems and to provide feedback on any challenges they face in reporting data to us. Therefore, we are proposing to allow voluntary patientlevel data submission for the FY 2023 payment determination (that is, data submitted during CY 2022). We note that because participation in patientlevel reporting for these chart-abstracted measures would be voluntary for this one-year period, facilities would be able to choose whether to submit measure data in aggregate or at the patient level, and would not face a payment reduction as long as they submit all measure data either at the patient level or in aggregate for each measure for which reporting is required, and as long as they met all other IPFQR Program requirements. Therefore, we are proposing to allow voluntary patient-level reporting prior to requiring such data submission for one year prior to the FY 2024 payment determination. If we transition to patient-level reporting, we will ensure that facilities have guidance available through our standard communications channels (that is, listserv announcements, educational webinars, and training material on the QualityNet website). We are also proposing to require patient-level data submission for these chart-abstracted measures for the FY 2024 payment determination (that is, VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 data submitted during CY 2023) and subsequent years. We welcome comment on our proposals to allow voluntary patientlevel data reporting for these chartabstracted measures for the FY 2023 payment determination and then to require patient-level data reporting for the FY 2024 payment determination and subsequent years. 3. Considerations for Data Validation Pilot As discussed in section IV.J.4 and in the FY 2019 IPF PPS final rule, we are concerned about the limitations of aggregate data submission (83 FR 28607). One such concern was that the ability to detect error is lower for aggregate measure data reporting than for patient-level data reporting (that is, data regarding each patient included in a measure and whether the patient was included in the numerator and denominator of the measure). We note that if we finalize our proposal to adopt patient-level data requirements, we would be able to adopt a data validation policy for the IPFQR Program in the future. We believe that it would be appropriate to develop such a policy incrementally through adoption of a data validation pilot prior to national implementation of data validation within the IPFQR Program. We seek public input on elements of a potential data validation pilot, for example, the number of measures to validate, number of participating facilities, whether the pilot should be mandatory or voluntary, potential thresholds for determining measure accuracy, or any other policies that commenters believe would be appropriate to include in a data validation pilot or eventual data validation policy. 4. Reporting Requirements for the FY 2022 Payment Determination and Subsequent Years We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53656 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50900 through 50901), and the FY 2015 IPF PPS final rule (79 FR 45976 through 45977) for our previously finalized reporting requirements. In this proposed rule, we are not proposing any changes to these policies. 5. Quality Measure Sampling Requirements We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53657 through 53658), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901 through 50902), the FY 2016 IPF PPS final rule (80 FR 46717 through 46719), and the PO 00000 Frm 00037 Fmt 4701 Sfmt 4702 19515 FY 2019 IPF PPS final rule (83 FR 38607 through 38608) for discussions of our previously finalized sampling policies. We note that neither the measure we are proposing to remove (FUH–NQF #0576) nor the measure we are proposing to adopt (FAPH) if we remove the FUH– NQF #0576 are affected by our sampling policies because these are both calculated by CMS using Medicare Feefor-Service claims and, therefore, apply to all Medicare patients in the denominator. Furthermore, the denominator of the COVID–19 Healthcare Personnel Vaccination measure we are proposing to adopt in this proposed rule is all healthcare personnel, and therefore, this measure is not eligible for sampling. In this proposed rule, we are not proposing any changes to our previously finalized sampling policies. 6. Non-Measure Data Collection We refer readers to the FY 2015 IPF PPS final rule (79 FR 45973), the FY 2016 IPF PPS final rule (80 FR 46717), and the FY 2019 IPF PPS final rule (83 FR 38608) for our previously finalized non-measure data collection policies. In this proposed rule, we are not proposing any changes to these policies. 7. Data Accuracy and Completeness Acknowledgement (DACA) Requirements We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53658) for our previously finalized DACA requirements. In this proposed rule, we are not proposing any changes to these policies. K. Reconsideration and Appeals Procedures We refer readers to 42 CFR 412.434 for the IPFQR Program’s reconsideration and appeals procedures. In this proposed rule, we are not proposing any changes to these policies. L. Extraordinary Circumstances Exceptions (ECE) Policy We refer readers to the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53659 through 53660), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50903), the FY 2015 IPF PPS final rule (79 FR 45978), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38473 through 38474) for our previously finalized ECE policies. In this proposed rule, we are not proposing any changes to these policies. V. Collection of Information Requirements Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et seq.), we are required to provide 60-day notice E:\FR\FM\13APP2.SGM 13APP2 19516 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules in the Federal Register and solicit public comment before a ‘‘collection of information’’ (as defined under 5 CFR 1320.3(c) of the PRA’s implementing regulations) requirement is submitted to the Office of Management and Budget (OMB) for review and approval. In order to fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the PRA requires that we solicit comment on the following issues: • The need for the information collection and its usefulness in carrying out the proper functions of our agency. • The accuracy of our estimate of the information collection burden. • The quality, utility, and clarity of the information to be collected. • Recommendations to minimize the information collection burden on the affected public, including automated collection techniques. We are soliciting public comment on each of the section 3506(c)(2)(A)— required issues for the following information collection requirements (ICRs). A. Proposed ICRs for the (IPFQR) Program The following proposed requirement and burden changes will be submitted to OMB for approval under control number 0938–1171 (CMS–10432). 1. Wage Estimates In the FY 2020 IPF PPS final rule (84 FR 38468), which was the most recent rule in which we adopted updates to the IPFQR Program, we estimated that reporting measures for the IPFQR Program could be accomplished by a Medical Records and Health Information Technician (BLS Occupation Code: 29–2071) with a median hourly wage of $18.83/hr. (May 2017). Since then, BLS (the Bureau of Labor Statistics) has revised their wage data (May 2019) to $20.50/hr.136 In response, we are proposing to adjust our cost estimates using the updated median wage rate figure of $20.50/hr., an increase of $1.67/hr. Under OMB Circular A–76, in calculating direct labor, agencies should not only include salaries and wages, but also ‘‘other entitlements’’ such as fringe benefits and overhead.137 Consistent with our past approach, we continue to calculate the cost of fringe benefits and overhead at 100 percent of the median hourly wage (81 FR 57266). This is necessarily a rough adjustment, both because fringe benefits and overhead costs vary significantly from employer to employer, and methods of estimating these costs vary widely from study to study. Therefore, using these assumptions, we estimate an hourly labor cost increase from $37.66/hr ($18.83/hr base salary + $18.83/hr fringe benefits and overhead) to $41.00/hr ($20.50/hr base salary + $20.50/hr fringe benefits and overhead). Table 7 presents these assumptions. TABLE 7—WAGE ASSUMPTIONS FOR THE IPFQR PROGRAM Occupation title Occupation code Median hourly wage ($/hr) Fringe benefits and overhead ($/hr) Adjustedhourly wage ($/hr) Medical Records and Health Information Technician ...................................... 29–2071 20.50 20.50 41.00 2. ICRs Regarding the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program a. Currently Approved Burden In subsection 2.a., we restate our currently approved burden estimates. In subsection 2.b., we estimate the proposed adjustments in burden associated with the updated BLS wage rate, our facility estimates, and our case estimates. In subsection 2.c., we estimate the changes in burden associated with the proposals in this rule. Finally, in subsection 2.d., we provide an overview of the total estimated burden. For a detailed discussion of the burden for the IPFQR Program requirements that we have previously adopted, we refer readers to the following rules: • The FY 2013 IPPS/LTCH PPS final rule (77 FR 53673); • The FY 2014 IPPS/LTCH PPS final rule (78 FR 50964); • The FY 2015 IPF PPS final rule (79 FR 45978 through 45980); • The FY 2016 IPF PPS final rule (80 FR 46720 through 46721); • The FY 2017 IPPS/LTCH PPS final rule (81 FR 57265 through 57266); • The FY 2018 IPPS/LTCH PPS final rule (82 FR 38507 through 38508); • The FY 2019 IPF PPS final rule (83 FR 38609 through 38612); and • The FY 2020 IPF PPS final rule (84 FR 38468 through 38476). Tables 8, 9, and 10 provide an overview of our currently approved burden. These tables use our previous estimate of $37.66 ($18.83 base salary plus $18.83 fringe benefits and overhead) hourly labor cost. For more information on our currently approved burden estimates, please see PRA Supporting Statement A on the Office of Information and Regulatory Affairs website.138 jbell on DSKJLSW7X2PROD with PROPOSALS2 TABLE 8—CURRENTLY APPROVED MEASURE COLLECTION AND REPORTING BURDEN NQF # Measure ID Measure description 0640 ........... 0641 ........... 0560 ........... HBIPS–2 ................ HBIPS–3 ................ HBIPS–5 ................ N/A ............. SUB–2 and SUB– 2a. Hours of Physical Restraint Use Hours of Seclusion Use ............... Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. Alcohol Use Brief Intervention Provided or Offered. 136 https://www.bls.gov/oes/current/ oes292098.htm (Accessed on March 30, 2021). VerDate Sep<11>2014 19:35 Apr 12, 2021 Jkt 253001 Estimated cases (per facility) Time per case (hours) Annual time per facility (hours) Frm 00038 Total annual time (hours) Total annual cost ($) 1,283 1,283 609 0.25 0.25 0.25 320.75 320.75 152.25 1,679 1,679 1,679 538,539.25 538,539.25 255,627.75 20,281,388 20,281,388 9,626,941 609 0.25 152.25 1,679 255,627.75 9,626,941 137 https://www.whitehouse.gov/omb/circulars_ a076_a76_incl_tech_correction. PO 00000 Number IPFs Fmt 4701 Sfmt 4702 138 https://www.reginfo.gov/public/do/ PRAViewDocument?ref_nbr=201908-0938-011. E:\FR\FM\13APP2.SGM 13APP2 19517 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules TABLE 8—CURRENTLY APPROVED MEASURE COLLECTION AND REPORTING BURDEN—Continued NQF # Measure ID N/A ............. SUB–3 and SUB– 3a. 0576 ........... FUH ........................ N/A ............. TOB–2 and TOB– 2a. N/A ............. TOB–3 and TOB– 3a. 1659 ........... 0647 ........... IMM–2 .................... N/A ......................... 0648 ........... N/A ......................... N/A ............. 2860 ........... N/A ......................... N/A ......................... 3205 ........... Med Cont ............... Total .... ................................ Estimated cases (per facility) Measure description Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and Alcohol and Other Drug Use Disorder Treatment at Discharge. Follow-Up After Hospitalization for Mental Illness *. Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment. Tobacco Use Treatment Provided or Offered at Discharge and Tobacco Use Treatment at Discharge. Influenza Immunization ................ Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care). Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care). Screening for Metabolic Disorders Thirty-day all-cause unplanned readmission following psychiatric hospitalization in an IPF *. Medication Continuation Following Inpatient Psychiatric Discharge *. ...................................................... Time per case (hours) Annual time per facility (hours) Total annual time (hours) Number IPFs Total annual cost ($) 609 0.25 152.25 1,679 255,627.75 9,626,941 0 0 0 0 0 0 609 0.25 152.25 1,679 255,627.75 9,626,941 609 0.25 152.25 1,679 255,627.75 9,626,941 609 609 0.25 0.25 152.25 152.25 1,679 1,679 255,627.75 255,627.75 9,626,941 9,626,941 609 0.25 152.25 1,679 255,627.75 9,626,941 609 0 0.25 0 152.25 0 1,679 0 255,627.75 0 9,626,941 0 0 0 0 0 0 0 8,047 Varies 2,011.75 1,679 3,377,728 127,205,245 * CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any cases. TABLE 9—CURRENTLY APPROVED NON-MEASURE DATA COLLECTION AND REPORTING BURDEN Tasks Annual time per facility (hours) Number IPFs Non-measure Data Collection and Submission ........................ I 1,679 I Total annual time (hours) I 2.0 3,358 Wage rate ($/hr) I 37.66 Total annual cost for all IPFs ($) Cost per IPF ($) I 75.32 I 126,462 TABLE 10—CURRENTLY APPROVED TOTAL BURDEN Requirement Respondents Measure Data Collection and Reporting ................................. 1,679 Non-Measure Data Collection and Reporting ......................... 1,679 Notice of Participation, Data Accuracy Acknowledgment, and Vendor Authorization Form *. Total ................................................................................. Time (hours) Responses Cost ($) 3,377,728 127,205,245 3,358 126,462 N/A 13,510,913 (8,047 responses or cases per facility * 1,679 facilities). 6,716 (4 * responses per facility * 1,679 facilities) 4. N/A ......................................... N/A N/A 1,679 13,517,629 ............................. 3,381,086 127,331,707 jbell on DSKJLSW7X2PROD with PROPOSALS2 * The 15 minutes per measure for chart abstraction under Measure Data Collection and Reporting also includes the time for completing and submitting any forms. b. Proposed Adjustments in Burden Due to Updated Wage, Facility Count, and Case Count Estimates In the FY 2020 IPF PPS final rule (84 FR 38468), which is the most recent rule, that updated the IPFQR Program VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 policies, we estimated that there were 1,679 participating IPFs and that (for measures that require reporting on the entire patient population) these facilities will report on an average of 1,283 cases per facility. In this FY 2022 rule, we are proposing to update our PO 00000 Frm 00039 Fmt 4701 Sfmt 4702 facility count and case estimates by using the most recent data available. Specifically, we estimate that there are now approximately 1,634 facilities (a decrease of 45 facilities) and an average of 1,346 cases per facility (an increase of 63 cases per facility). Tables 11, 12, E:\FR\FM\13APP2.SGM 13APP2 19518 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules and 13, depict the effects of these updates, as well as the wage rate update to $41.00/hr described in section V.A.1 of the preamble of this proposed rule, on our previously estimated burden. TABLE 11—MEASURE COLLECTION AND REPORTING BURDEN BASED ON UPDATED CASES PER FACILITY, FACILITY COUNTS, AND WAGE RATE Estimated cases (per facility) Annual time per facility (hours) Time per case (hours) Total annual time (hours) Number IPFs Total annual cost ($) NQF # Measure ID Measure description 0640 ........... 0641 ........... 0560 ........... HBIPS–2 ............... HBIPS–3 ............... HBIPS–5 ............... 1,346 1,346 * 609 0.25 0.25 0.25 336.50 336.50 152.25 1,634 1,634 1,634 549,841 549,841 248,776.5 22,543,481 22,543,481 10,199,836.50 N/A ............. SUB–2 and SUB– 2a. * 609 0.25 152.25 1,634 248,776.5 10,199,836.50 N/A ............. SUB–3 and SUB– 3a. * 609 0.25 152.25 1,634 248,776.5 10,199,836.50 0576 ........... FUH ...................... 0 0 0 0 0 0 N/A ............. TOB–2 and TOB– 2a. * 609 0.25 152.25 1,634 248,776.5 10,199,836.50 N/A ............. TOB–3 and TOB– 3a. * 609 0.25 152.25 1,634 248,776.5 10,199,836.50 1659 ........... 0647 ........... IMM–2 ................... N/A ........................ * 609 * 609 0.25 0.25 152.25 152.25 1,634 1,634 248,776.5 248,776.5 10,199,836.50 10,199,836.50 0648 ........... N/A ........................ * 609 0.25 152.25 1,634 248,776.5 10,199,836.50 N/A ............. N/A ........................ * 609 0.25 152.25 1,634 248,776.5 10,199,836.50 2860 ........... N/A ........................ 0 0 0 0 0 0 3205 ........... Med Cont .............. 0 0 0 0 0 0 N/A ............. COVID–19 HCP .... ** 0 0 0 0 0 0 N/A ............. FAPH .................... Hours of Physical Restraint Use Hours of Seclusion Use ............ Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention Provided. Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and Alcohol and Other Drug Use Disorder Treatment at Discharge. Follow-Up After Hospitalization for Mental Illness *. Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment. Tobacco Use Treatment Provided or Offered at Discharge and Tobacco Use Treatment at Discharge. Influenza Immunization ............. Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care). Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/ Self Care or Any Other Site of Care). Screening for Metabolic Disorders. Thirty-day all-cause unplanned readmission following psychiatric hospitalization in an IPF*. Medication Continuation Following Inpatient Psychiatric Discharge*. COVID–19 Vaccination Rate Among Healthcare Personnel. Follow-Up After Psychiatric Hospitalization. 0 0 0 0 0 0 Total .... ............................... .................................................... 8,173 Varies 2,043.25 1,634 3,338,671 136,885,491 jbell on DSKJLSW7X2PROD with PROPOSALS2 * Under our previously finalized ‘‘global sample’’ (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global sample would be required to report data for 609 cases. Because facilities are only required to submit data on a number specified by the global sampling methodology, rather than abstracting data for all patients or applying measure specific sampling methodologies, we believe that the number of cases under the global sample is a good approximation of facility burden associated with these measures. Therefore, for the average IPF discharge rate of 1,346 discharges versus the previously estimated 1,283, the global sample continues to require abstraction of 609 records. ** The COVID–19 HCP measure will be calculated using data submitted to the CDC under a separate OMB Control Number (0920–1317). TABLE 12—NON-MEASURE DATA COLLECTION AND REPORTING BURDEN BASED ON UPDATED CASES PER FACILITY, FACILITY COUNTS, AND WAGE RATE Tasks Number IPFs Annual time per facility (hours) Total annual time (hours) Wage rate ($/hr) Cost per IPF ($) Total annual cost for all IPFs ($) Non-measure Data Collection and Submission ........................ 1,634 2.0 3,268 41.00 82.00 133,988 VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 PO 00000 Frm 00040 Fmt 4701 Sfmt 4702 E:\FR\FM\13APP2.SGM 13APP2 19519 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules TABLE 13—TOTAL BURDEN BASED ON UPDATED CASES PER FACILITY, FACILITY COUNTS, AND WAGE RATE Requirement Respondents Measure Data Collection and Reporting ........ 1,634 Non-Measure Data Collection and Reporting 1,634 Total ......................................................... jbell on DSKJLSW7X2PROD with PROPOSALS2 c. Changes in Burden Due to This Proposed Rule (1). Updates Due to Proposed Measure Adoptions In section IV.E of this preamble, we are proposing to adopt the following two measures: • COVID–19 HCP Vaccination for FY 2023 Payment Determination and Subsequent Years; and • Follow-Up After Psychiatric Hospitalization (FAPH) for FY 2024 Payment Determination and Subsequent Years. We are proposing to adopt the COVID–19 HCP Vaccination measure beginning with an initial reporting period from October 1 to December 31, 2021 affecting the FY 2023 payment determination followed by annual reporting beginning with the FY 2024 payment determination and subsequent years. IPFs would submit data through the CDC NHSN. The NHSN is a secure, internet-based system maintained by the CDC and provided free. Currently the CDC does not estimate burden for COVID–19 vaccination reporting under the CDC PRA package currently approved under OMB control number 0920–1317 because the agency has been granted a waiver under Section 321 of the National Childhood Vaccine Injury Act (NCVIA).139 Although the burden as associated with the COVID–19 HCP Vaccination measure is not accounted for under the CDC PRA package currently approved under OMB control number 0920–1317 due to the NCVIA waiver, the cost and burden information is discussed here and will be included in a revised information collection request for 0920– 1317. Consistent with the CDC’s experience of collecting data using the NHSN, we estimate that it would take each IPF on average approximately 1 hour per month to collect data for the COVID–19 Vaccination Coverage among 139 Section 321 of the National Childhood Vaccine Injury Act (NCVIA) provides the PRA waiver for activities that come under the NCVIA, including those in the NCVIA at section 2102 of the Public Health Service Act (42 U.S.C. 300aa–2). Section 321 is not codified in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa–1. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 1,634 3,338,671 136,885,491 3,268 133,988 13,361,218 ..................................................... 3,341,939 137,019,479 140 https://www.bls.gov/oes/current/ oes436013.htm (accessed on March 30, 2021). The hourly rate of $36.62 includes an adjustment of 100 percent of the median hourly wage to account for the cost of overhead, including fringe benefits. Frm 00041 Cost ($) 13,354,682 (8,173 responses per facility * 1,634 facilities). 6,536 (4 responses per facility * 1,634 facilities). HCP measure and enter it into NHSN. We have estimated the time to complete this entire activity, since it could vary based on provider systems and staff availability. This burden is comprised of administrative hours and wages. We believe it would take an Administrative Assistant 140 between 45 minutes and 1 hour and 15 minutes to enter this data into NHSN. For the CY 2021 reporting period (consisting of October 1, 2021 through December 31, 2021) 3 months are required. For the CY 2021 reporting period/FY 2023 payment determination, IPFs would incur an additional burden between 2.25 hours (0.75 hours * 3 months) and 3.75 hours (1.25 hours * 3 months) per IPF. For all 1,634 IPFs, the total burden would range from 3,676.5 (2.25 hours * 1,634 IPFs) and 6,127.5 hours (3.75 hours * 1,634 IPFs). Each IPF would incur an estimated cost of between $27.47 (0.75 hour * $36.62/hr) and $45.78 (1.25 hours * 36.63/hr) monthly and between $82.40 (2.25 hours * $36.62/hr) and $137.33 (3.75 hours * $36.62/hr) in total over the CY 2021 reporting period to complete this task. Thereafter, 12 months of data are required annually. Therefore, IPFs would incur an additional annual burden between 9 hours (0.75 hours/ month * 12 months) and 15 hours (1.25 hours/month * 12 months) per IPF and between 14,706 hours (9 hours/IPF * 1,634 IPFs) and 24,510 hours (15 hours/ IPF * 1,634 IPFs) for all IPFs. Each IPF would incur an estimated cost of between $329.58 (9 hours × $36.62/hr) and $549.30 annually (15 hours × $36.62/hr). The estimated cost across all 1,634 IPFs would be between $134,641.6 ($82.40/IPF * 1,634 IPFs) and $224,397.22 ($137.33/IPF * 1,634 IPFs) for the CY 2021 reporting period. The estimated cost across all 1,634 IPFs would be between $538,533.72 ($329.58/IPF * 1,634 IPFs) and $897,556.2 ($549.30/IPF * 1,634 IPFs) annually thereafter. PO 00000 Time (hours) Responses Fmt 4701 Sfmt 4702 We recognize that many healthcare facilities are also reporting other COVID–19 data to HHS. We believe the benefits of requiring IPFs to report data on the COVID–19 HCP Vaccination measure to assess whether they are taking steps to limit the spread of COVID–19 among their healthcare workers and to help sustain the ability of IPFs to continue serving their communities throughout the PHE and beyond outweigh the costs of reporting. We welcome comments on the estimated time to collect data and enter it into the NHSN. We further note that as described in section IV.E.C of this preamble, we will calculate performance on the FAPH measure using Medicare Part A and Part B claims that facilities and other providers submit for payment. Since this is a claims-based measure, there is no additional burden outside of submitting the claim. The claim submission is approved by OMB under control number 0938–0050 (CMS–2552– 10). This rule does not propose any changes under that control number. (2). Updates Due to Proposed Measure Removals In section IV.F. of this preamble, we are proposing to remove the following four measures for the FY 2024 payment determination and subsequent years: • SUB–2—Alcohol Use Brief Intervention Provided or Offered and the subset measure SUB–2a Alcohol Use Brief Intervention Provided; • TOB–2—Tobacco Use Brief Intervention Provided or Offered and the subset measure TOB–2a Tobacco Use Brief Intervention; • Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care); and • FUH—Follow-Up After Hospitalization for Mental Illness (NQF #0576). For the FY 2024 payment determination, data on CY 2022 performance would be reported during the summer of 2023. Therefore, we are applying the burden reduction that would occur to the FY 2023 burden calculation. Three of these measures E:\FR\FM\13APP2.SGM 13APP2 19520 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules (SUB–2/2a, TOB–2/2a, and the Timely Transmission measure) fall under our previously finalized ‘‘global sample’’ (80 FR 46717 through 46718) and, therefore, would require abstraction of 609 records. We estimate that removing each of these three measures would result in a decrease in burden of 152.25 hours per facility, or 248,776.5 hours (152.25 hours × 1,634 facilities) across all IPFs. Therefore, the decrease in costs for each measure is approximately $6,242.25 per IPF ($41.00hr * 152.25 hours), or $10,199,836.50 across all IPFs ($6,242.25/facility * 1,634 facilities). For all three of these chart-abstracted measures the total decrease in burden is approximately 456.75 hours per IPF (3 measures * 152.25 hours per measure) or 746,329.5 hours across all IPFs (3 measures * 248,776.5 hours per measure). This equates to $18,726.75 per IPF (3 measures * $6,242.25 per measure), or $30,599,509.50 across all IPFs (3 measures * $10,199,836.50 per measure). We have previously estimated that the FUH (NQF #0576) measure does not have any reporting burden because it is calculated from Medicare FFS claims. Therefore, we do not anticipate a reduction in facility burden associated with the removal of this measure. Table 14 describes our estimated reduction in burden associated with removing these four measures. TABLE 14—BURDEN UPDATES DUE TO PROPOSED MEASURE REMOVALS Estimated cases (per facility) Time per case (hours) Annual time per facility (hours) Total annual time (hours) Number IPFs Total annual cost ($) NQF # Measure ID Measure description N/A ............. SUB–2 and SUB– 2a. FUH ...................... Alcohol Use Brief Intervention Provided or Offered. Follow-Up After Hospitalization for Mental Illness *. Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment. Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/ Self Care or Any Other Site of Care). (609) 0.25 152.25 1,634 (248,776.5) (10,199,836.5) 0 0 0 1,634 0 0 (609) 0.25 152.25 1,634 (248,776.5) (10,199,836.5) (609) 0.25 152.25 1,634 (248,776.5) (10,199,836.5) .................................................... (1,827) Varies (456.75) 1,634 (746,329.5) (30,599,509.50) 0576 ........... N/A ............. TOB–2 and TOB– 2a. 0648 ........... N/A ........................ Total .... ............................... * CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any cases. (3). Updates Due to Proposed Administrative Policies (a). Updates Associated With Proposed Updated Reference to QualityNet System Administrator In section IV.J.1.a of this preamble, we proposed to use the term ‘‘QualityNet security official’’ instead of ‘‘QualityNet system administrator.’’ Because this proposed update would not change the individual’s responsibilities, we do not believe there would be any changes to the information collection burden as a result of this update. We also do not believe that removing the requirement for facilities to have an active of aggregate data requires facilities to abstract patient-level data, then calculate measure performance prior to submitting data through the QualityNet website’s secure portal, facilities must already abstract patient-level data. Therefore, we do not believe that submitting data that facilities must already calculate through a tool that facilities already have experience using will change provider burden. QualityNet security official account to qualify for payment updates will affect burden because we continue to recommend that facilities maintain an active QualityNet security official account. (b). Updates Associated With Proposed Adoption of Patient-Level Reporting for Certain Chart Abstracted Measures In section IV.J.2.c of this preamble, we propose to adopt patient-level data submission for the eleven chartabstracted measures currently in the IPFQR Program measure set (for more details on these measures we refer readers to Table 6). Because submission d. Overall Burden Summary Table 15 summarizes the estimated burden associated with the IPFQR Program if the proposals in this rule are finalized. TABLE 15—TOTAL ESTIMATED IPFQR PROGRAM BURDEN Estimated responses per facility jbell on DSKJLSW7X2PROD with PROPOSALS2 Measure/response description Hours of Physical Restraint Use ................................................................................... Hours of Seclusion Use ................................................................................................ Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification ...................................................................................................................... Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge and Alcohol and Other Drug Use Disorder Treatment at Discharge ........................ Tobacco Use Treatment Provided or Offered at Discharge and Tobacco Use Treatment at Discharge ..................................................................................................... Influenza Immunization ................................................................................................. Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) .. Screening for Metabolic Disorders ................................................................................ Thirty-day all-cause unplanned readmission following psychiatric hospitalization in an IPF ........................................................................................................................ Medication Continuation Following Inpatient Psychiatric Discharge ............................ COVID–19 Vaccination Rate Among Healthcare Personnel ........................................ Follow-Up After Psychiatric Hospitalization .................................................................. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 PO 00000 Frm 00042 Fmt 4701 Time per response (hours) Annual time per facility (hours) Total annual time (hours) Total annual cost ($) 1,346 1,346 0.25 0.25 336.50 336.50 549,841 549,841 $22,543,481 22,543,481 * 609 0.25 152.25 248,776.5 10,199,836.50 * 609 0.25 152.25 248,776.5 10,199,836.50 * 609 * 609 0.25 0.25 152.25 152.25 248,776.5 248,776.5 10,199,836.50 10,199,836.50 * 609 * 609 0.25 0.25 152.25 152.25 248,776.5 248,776.5 10,199,836.50 10,199,836.50 ** 0 ** 0 *** 0 ** 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Sfmt 4702 E:\FR\FM\13APP2.SGM 13APP2 19521 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules TABLE 15—TOTAL ESTIMATED IPFQR PROGRAM BURDEN—Continued Estimated responses per facility Measure/response description Non-Measure Data Collection and Reporting ............................................................... Time per response (hours) 4 I Total ....................................................................................................................... 6,346 Annual time per facility (hours) 0.5 I N/A Total annual time (hours) 2.0 I 1,588.5 Total annual cost ($) 3,268 I 2,595,609 133,988 I 106,419,969 * Under our previously finalized ‘‘global sample’’ (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global sample would be required to report data for 609 cases. Because facilities are only required to submit data on a number specified by the global sampling methodology, rather than abstracting data for all patients or applying measure specific sampling methodologies, we believe that the number of cases under the global sample is a good approximation of facility burden associated with these measures. Therefore, for the average IPF discharge rate of 1,346 discharges versus the previously estimated 1,283, the global sample continues to require abstraction of 609 records. ** CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any cases. *** The COVID–19 HCP measure will be calculated using data submitted to the CDC under a separate OMB Control Number (0920–1317). The total change in burden associated with this proposed rule (including all updates to wage rate, case counts, facility numbers, and the measures and administrative policies) is a reduction of 785,477 hours and $20,911,738 from our currently approved burden of 3,381,086 hours and $127,331,707. We refer readers to Table 16 for details. TABLE 16—SUMMARY OF PROPOSED REQUIREMENTS AND ANNUAL BURDEN ESTIMATES UNDER OMB CONTROL NUMBER 0938–1171 (CMS–10432) Number respondents Program changes Active Burden ................................................................................ Total Burden Under CMS–1750–P ............................................... PROPOSED CHANGES ............................................................... B. Submission of PRA-Related Comments We have submitted a copy of this proposed rule to OMB for its review of the rule’s information collection and recordkeeping requirements. The requirements are not effective until they have been approved by OMB. To obtain copies of the supporting statement and any related forms for the proposed collections previously discussed, visit CMS’s website at: https://www.cms.gov/Regulations-andGuidance/Legislation/ PaperworkReductionActof1995/PRAListing.html or call the Reports Clearance Office at (410) 786–1326. We invite public comments on these information collection requirements. If you wish to comment, identify the rule (CMS–1750–P) and, where applicable, the preamble section, and the ICR section. See this rule’s DATES and ADDRESSES sections for the comment due date and for additional instructions. VI. Regulatory Impact Analysis jbell on DSKJLSW7X2PROD with PROPOSALS2 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 2022 (October 1, 2021 through September 30, 2022). We are proposing to apply the 2016-based IPF market basket increase of 2.3 percent, less the productivity adjustment of 0.2 percentage point as required by VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 I 1,679 1,634 (45) Time per response (hr) Total responses I 13,517,629 10,375,900 (3,141,729) I Varies Varies Varies 1886(s)(2)(A)(i) of the Act for a proposed total FY 2022 payment rate update of 2.1 percent. In this proposed rule, we are proposing to update the IPF laborrelated share and update the IPF wage index to reflect the FY 2022 hospital inpatient wage index. B. Overall Impact We have examined the impacts of this proposed 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 (the Act), section 202 of the Unfunded Mandates Reform Act of 1995 (March 22, 1995; Pub. L. 104–4), and Executive Order 13132 on Federalism (August 4, 1999). Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). Section 3(f) of Executive Order 12866 defines a ‘‘significant regulatory action’’ as an action that is likely to result in a rule: (1) Having an annual effect on the economy of $100 million or more in any 1 year, or adversely and materially affecting a sector of the PO 00000 Frm 00043 Fmt 4701 Sfmt 4702 Total time (hr) I 3,381,086 2,595,609 (785,477) Labor cost per hour ($/hr) I 37.66 41.00 +3.34 Total cost ($) I 127,331,707 106,419,969 (20,911,738) 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. We estimate that this rulemaking is likely to be economically significant as measured by the $100 million threshold, and hence, if finalized as proposed, a major rule under the Congressional Review Act. Accordingly, we have prepared a Regulatory Impact Analysis that to the best of our ability presents the costs and benefits of the rulemaking. We estimate that the total impact of these changes for FY 2022 payments compared to FY 2021 payments will be a net increase of approximately $90 million. This reflects an $80 million increase from the update to the payment rates (+$90 million from the 4th quarter 2020 IGI forecast of the 2016-based IPF market basket of 2.3 percent, and ¥$10 million for the productivity adjustment E:\FR\FM\13APP2.SGM 13APP2 19522 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules of 0.2 percentage point), as well as a $10 million increase as a result of the update to the outlier threshold amount. Outlier payments are estimated to change from 1.8 percent in FY 2021 to 2.0 percent of total estimated IPF payments in FY 2022. 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. The budget neutrality factor includes the following components: Outlier adjustment, stoploss 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 updating the wage index and labor-related share 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 2022 of 2.3 percent (see section III.A.4 of this proposed rule) less the productivity adjustment of 0.2 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 2022 impact will be a net increase of $90 million in payments to IPF providers. This reflects an estimated $80 million increase from the update to the payment rates and a $10 million increase 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 2022. This estimate does not include the implementation of the required 2.0 percentage point reduction of the market basket update factor for any IPF that fails to meet the IPF quality reporting requirements (as discussed in section V.A. 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 IPF PPS rates and factors for FY 2022 versus those under FY 2021. We determined the percent change in the estimated FY 2022 IPF PPS payments compared to the estimated FY 2021 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 update to the outlier fixed dollar loss threshold amount; the updated wage index data including the updated labor-related share; and the market basket update for FY 2022, as adjusted by the productivity adjustment according to section 1886(s)(2)(A)(i) of the Act. Our longstanding methodology uses the best available data as the basis for our estimates of payments. Typically, this is the most recent update of the latest available fiscal year of IPF PPS claims, and for this proposed rulemaking, that would be the FY 2020 claims. However, as discussed in section III.F.2 of this proposed rule, the U.S. healthcare system undertook an unprecedented response to the COVID– 19 PHE during FY 2020. Therefore, we considered whether the most recent available year of claims, FY 2020, or the prior year, FY 2019, would be the best for estimating IPF PPS payments in FY 2021 and FY 2022. To illustrate the impacts of the FY 2022 changes in this proposed rule, our analysis presents a side-by-side comparison of payments estimated using FY 2019 claims versus payments estimated using FY 2020 claims. We begin with FY 2019 IPF PPS claims (based on the 2019 MedPAR claims, June 2020 update) and FY 2020 IPF PPS claims (based on the 2020 MedPAR claims, December 2020 update). We estimate FY 2021 IPF PPS payments using these 2019 and 2020 claims, the finalized FY 2021 IPF PPS Federal per diem base rates, and the finalized FY 2021 IPF PPS patient and facility level adjustment factors (as published in the FY 2021 IPF PPS final rule (85 FR 47042 through 47070)). We then estimate the FY 2021 outlier payments based on these simulated FY 2021 IPF PPS payments using the same methodology as finalized in the FY 2021 IPF PPS final rule (85 FR 47061 through 47062) where total outlier payments are maintained at 2 percent of total estimated FY 2021 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 2022 IPF wage index, the proposed FY 2022 laborrelated share, and the proposed updated COLA factors. • The proposed market basket update for FY 2022 of 2.3 percent less the productivity adjustment of 0.2 percentage point in accordance with section 1886(s)(2)(A)(i) of the Act for a payment rate update of 2.1 percent. Our proposed column comparison in Table 17 illustrates the percent change in payments from FY 2021 (that is, October 1, 2020, to September 30, 2021) to FY 2022 (that is, October 1, 2021, to September 30, 2022) including all the payment policy changes in this proposed rule. For each column, Table 17 presents a side-by-side comparison of the results using FY 2019 and FY 2020 IPF PPS claims. TABLE 17—FY 2022 IPF PPS PROPOSED PAYMENT IMPACTS [Percent change in columns 3 through 5] Number of facilities jbell on DSKJLSW7X2PROD with PROPOSALS2 Facility by type FY 2019 Claims (1) 19:14 Apr 12, 2021 FY 2020 Claims FY 2019 Claims (2) All Facilities ....................................................... Total Urban ................................................ Urban unit ........................................... Urban hospital ..................................... Total Rural ................................................. Rural unit ............................................ Rural hospital ...................................... VerDate Sep<11>2014 Outlier Jkt 253001 1,526 1,226 742 484 300 240 60 PO 00000 Frm 00044 FY 2020 Claims Wage index FY22, LRS, and COLA Total percent change 1 FY 2019 Claims FY 2019 Claims (3) 1,536 1,238 738 500 298 237 61 Fmt 4701 0.2 0.2 0.3 0.1 0.1 0.1 0.1 Sfmt 4702 FY 2020 Claims (4) ¥0.7 ¥0.7 ¥1.1 ¥0.2 ¥0.5 ¥0.6 ¥0.2 0.0 0.0 ¥0.1 0.0 0.1 0.0 0.5 E:\FR\FM\13APP2.SGM 13APP2 FY 2020 Claims (5) 0.0 0.0 ¥0.1 0.0 0.1 0.0 0.5 2.3 2.3 2.3 2.2 2.4 2.2 2.7 1.4 1.3 0.9 1.9 1.8 1.5 2.4 19523 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules TABLE 17—FY 2022 IPF PPS PROPOSED PAYMENT IMPACTS—Continued [Percent change in columns 3 through 5] Number of facilities Facility by type FY 2019 Claims (1) Outlier FY 2020 Claims FY 2019 Claims (2) By Type of Ownership: Freestanding IPFs: Urban Psychiatric Hospitals: Government ........................................ Non-Profit ............................................ For-Profit ............................................. Rural Psychiatric Hospitals: Government ........................................ Non-Profit ............................................ For-Profit ............................................. IPF Units: Urban: Government ........................................ Non-Profit ............................................ For-Profit ............................................. Rural: Government ........................................ Non-Profit ............................................ For-Profit ............................................. By Teaching Status: Non-teaching .............................................. Less than 10% interns and residents to beds ........................................................ 10% to 30% interns and residents to beds More than 30% interns and residents to beds By Region: New England .............................................. Mid-Atlantic ................................................ South Atlantic ............................................. East North Central ..................................... East South Central ..................................... West North Central .................................... West South Central .................................... Mountain .................................................... Pacific ......................................................... By Bed Size: Psychiatric Hospitals: Beds: 0–24 .......................................... Beds: 25–49 ........................................ Beds: 50–75 ........................................ Beds: 76 + .......................................... Psychiatric Units: Beds: 0–24 .......................................... Beds: 25–49 ........................................ Beds: 50–75 ........................................ Beds: 76 + .......................................... FY 2020 Claims Wage index FY22, LRS, and COLA Total percent change 1 FY 2019 Claims FY 2019 Claims (3) FY 2020 Claims (4) FY 2020 Claims (5) 117 93 274 123 95 282 0.3 0.1 0.0 ¥1.1 ¥0.3 ¥0.1 ¥0.2 ¥0.3 0.1 ¥0.2 ¥0.2 0.2 2.2 1.9 2.3 0.7 1.6 2.2 31 12 17 32 12 17 0.1 0.2 0.0 ¥0.4 ¥0.7 0.0 0.5 0.0 0.6 0.6 0.1 0.6 2.8 2.3 2.7 2.2 1.5 2.7 109 482 151 108 480 150 0.4 0.3 0.1 ¥2.1 ¥1.1 ¥0.5 0.1 ¥0.1 ¥0.1 0.1 ¥0.1 ¥0.1 2.7 2.3 2.2 0.0 0.9 1.5 58 133 49 57 130 50 0.1 0.2 0.1 ¥0.2 ¥0.8 ¥0.4 0.3 0.0 ¥0.2 0.2 0.0 ¥0.2 2.5 2.2 2.0 2.1 1.2 1.4 1,329 1,339 0.1 ¥0.6 0.0 0.0 2.2 1.5 106 70 21 106 70 21 0.3 0.4 0.4 ¥1.2 ¥1.6 ¥1.9 0.0 0.0 ¥0.1 0.0 0.0 ¥0.1 2.4 2.4 2.4 0.9 0.5 0.1 106 215 241 245 152 110 225 103 129 106 217 243 245 155 110 227 102 131 0.2 0.3 0.1 0.1 0.1 0.2 0.1 0.1 0.2 ¥0.8 ¥1.3 ¥0.5 ¥0.4 ¥0.5 ¥0.9 ¥0.4 ¥0.4 ¥0.9 ¥0.3 ¥0.2 0.7 ¥0.1 ¥0.7 0.2 ¥0.3 0.1 0.4 ¥0.4 ¥0.2 0.7 ¥0.1 ¥0.7 0.2 ¥0.3 0.1 0.5 2.0 2.1 2.9 2.2 1.5 2.6 1.9 2.3 2.8 1.0 0.5 2.3 1.5 0.8 1.4 1.4 1.8 1.6 85 79 84 296 90 83 87 301 0.1 0.1 0.0 0.1 ¥0.3 ¥0.2 ¥0.1 ¥0.3 0.1 ¥0.5 0.1 0.1 0.1 ¥0.4 0.3 0.1 2.3 1.7 2.3 2.3 1.9 1.4 2.3 2.0 540 258 115 69 531 259 115 70 0.2 0.2 0.3 0.3 ¥0.8 ¥0.9 ¥1.1 ¥1.6 0.0 0.0 ¥0.2 0.0 ¥0.1 0.0 ¥0.3 0.0 2.3 2.4 2.2 2.4 1.2 1.2 0.7 0.4 jbell on DSKJLSW7X2PROD with PROPOSALS2 1 This column includes the impact of the updates in column (3) and (4) above, and of the proposed IPF market basket increase factor for FY 2022 (2.3 percent), reduced by 0.2 percentage point for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act. Note, the products of these impacts may be different from the percentage changes shown here due to rounding effects. 3. Impact Results Table 17 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 1,526 IPFs included in the analysis for FY 2019 claims or the 1,536 IPFs included in the analysis for FY 2020 claims. In column VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 2, we present the number of facilities of each type that had information available in the PSF and also had claims in the MedPAR dataset for FY 2019 or FY 2020. The number of providers in each category therefore differs slightly between the two years. In column 3, we present the effects of the update to the outlier fixed dollar loss threshold amount. Based on the FY 2019 claims, we would estimate that IPF outlier payments as a percentage of total IPF payments are 1.8 percent in FY 2021. Alternatively, based on the FY 2020 claims, we would estimate that IPF outlier payments as a percentage of total IPF payments are 2.7 percent in FY 2021. PO 00000 Frm 00045 Fmt 4701 Sfmt 4702 Thus, we are proposing to adjust the outlier threshold amount in this proposed rule to set total estimated outlier payments equal to 2.0 percent of total payments in FY 2022. Based on the FY 2019 claims, the estimated change in total IPF payments for FY 2022 would include an approximate 0.2 percent increase in payments because we would expect the outlier portion of total payments to increase from approximately 1.8 percent to 2.0 percent. Alternatively, based on the FY 2020 claims, the estimated change in total IPF payments for FY 2022 would include an approximate 0.7 percent decrease in payments because we would expect the outlier portion of total E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 19524 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules payments to decrease from approximately 2.7 percent to 2.0 percent. The overall impact of the estimated increase or decrease to payments due to updating the outlier fixed dollar loss threshold (as shown in column 3 of Table 17), across all hospital groups, is 0.2 percent based on the FY 2019 claims, or ¥0.7 percent based on the FY 2020 claims. If we decrease the outlier fixed dollar loss threshold based on the FY 2019 claims, the largest increase in payments due to this change is estimated to be 0.4 percent for urban, government-owned IPF units and also 0.4 percent for teaching IPFs with 10 percent or more interns and residents to beds. These same provider types, along with IPF units having more than 75 beds, would experience the largest estimated decrease in payments if we instead increase the outlier fixed dollar loss threshold based on the FY 2020 claims distribution. In column 4, we present the effects of the budget-neutral update to the IPF wage index, the Labor-Related Share (LRS), and the proposed updated COLA factors discussed in section III.D.3. 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 updated COLA factors and the update from the FY 2021 IPF wage index to the proposed FY 2022 IPF wage index, which includes basing the FY 2022 IPF wage index on the FY 2022 pre-floor, pre-reclassified IPPS hospital wage index data and updating the LRS from 77.3 percent in FY 2021 to 77.1 percent in FY 2022. We note that there is no projected change in aggregate payments to IPFs, as indicated in the first row of column 4; however, there will be distributional effects among different categories of IPFs. We also note that when comparing the results using FY 2019 and FY 2020 claims, the distributional effects are very similar. For example, we estimate the largest increase in payments to be 0.7 percent for IPFs in the South Atlantic region, and the largest decrease in payments to be ¥0.7 percent for IPFs in the East South Central region, based on either the FY 2019 or FY 2020 claims. Finally, column 5 compares the total proposed changes reflected in this proposed rule for FY 2022 to the estimates for FY 2021 (without these changes). The average estimated increase for all IPFs is approximately 2.3 percent based on the FY 2019 claims, or 1.4 percent based on the FY 2020 claims. These estimated net increases include the effects of the 2016- VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 based market basket update of 2.3 percent reduced by the productivity adjustment of 0.2 percentage point, as required by section 1886(s)(2)(A)(i) of the Act. They also include the overall estimated 0.2 percent increase or 0.7 percent decrease in estimated IPF outlier payments as a percent of total payments from updating the outlier fixed dollar loss threshold amount. In addition, column 5 includes the distributional effects of the proposed updates to the IPF wage index, the labor-related share, and the proposed updated COLA factors, whose impacts are displayed in column 4. Based on the FY 2020 claims distribution, the increase to estimated payments due to the market basket update factor are offset in large part for some provider types by the increase to the outlier fixed dollar loss threshold. In summary, comparing the impact results for the FY 2019 and FY 2020 claims, the largest difference in the results is due to the update to the outlier fixed dollar loss threshold. Therefore, we examined the differences between the FY 2019 and FY 2020 claims distributions to better understand the disparity in the estimate of outlier payments as a percentage of total PPS payments between the two years, which is driving the divergent results in column 3 of Table 17. The calculation of the estimated outlier percentage has two components: Estimated outlier payments and estimated total PPS payments. As discussed in section III.F.1 of this proposed rule, 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 facilitylevel adjustments) plus the Federal per diem payment amount for the case. Therefore, estimated outlier payments are a function of both estimated IPF costs and estimated IPF Federal per diem payment amounts per case. As such, we looked at changes in estimated costs, estimated Federal per diem payment amounts, estimated outlier payments, and estimated total PPS payments in order to understand the differences in the estimated outlier percentage when using the FY 2019 and FY 2020 claims data. To facilitate the comparison between our FY 2019 and FY 2020 datasets, we inflated all estimated costs to the midpoint of FY 2021 and estimated all payments based on the finalized FY 2021 IPF PPS patient and facility level adjustment factors (as published in the FY 2021 IPF PPS final rule (85 FR 47042 through 47070)). In summary, we found that estimated outlier payments using the FY PO 00000 Frm 00046 Fmt 4701 Sfmt 4702 2020 claims dataset are 26 percent higher than the estimated outlier payments using the FY 2019 claims dataset, due to estimated costs per stay that were relatively higher than estimated Federal per diem payment amounts per stay. Estimated total payments using the FY 2020 claims dataset are 14 percent lower than the estimated total payments using the FY 2019 claims dataset. Therefore, both the estimated outlier payments and estimated total payments are contributing to the differences in the estimated outlier payment percentage of 2.7 percent using the FY 2020 claims dataset and 1.8 percent using the FY 2019 claims dataset. We discuss estimated total payments and estimated outlier payments in more detail below. As stated above, we observed a reduction of estimated total PPS payments of approximately 14 percent using the FY 2020 claims dataset relative to estimated total PPS payments in our FY 2019 claims dataset. The reduction in estimated total PPS payments corresponds with a roughly 15 percent decline in covered IPF days and a roughly 17 percent decline in covered IPF stays. The consistency between the decline in IPF stays and IPF days indicates the overall length of stay is fairly consistent in the FY 2019 claims dataset and FY 2020 claims dataset. An important consideration for how we estimate the percentage of estimated outlier payments in FY 2022 is whether we expect this lower level of total payments to persist in future years. We note that although there has been a downward trend in IPF stays and total payments in recent years, the decrease from FY 2019 to FY 2020 is 2 to 3 times greater than the decreases in recent prior years. Looking on a monthly basis at the claims in our FY 2020 claims dataset, we observed that estimated total PPS payments per month declined sharply, nearly 28 percent, from January 2020 to April 2020. Estimated total PPS payments per month decreased overall by approximately 21 percent from January 2020 to September 2020. The lower estimated total PPS payments per month were a result of both lower covered IPF days and covered IPF stays. The COVID–19 PHE was declared on January 31, 2020, and continued through the end of FY 2020, with an initial surge in cases occurring in many places in the early months of the PHE. Based on the timing of the declines in covered IPF stays and covered IPF days, we believe they are related to the response to the COVID–19 PHE. Therefore, we do not anticipate that decreases in total PPS payments, E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules covered IPF days, and covered IPF stays of the same magnitude as observed in FY 2020 are likely to occur in FY 2022. We are seeking comments on this analysis. Specifically, we are requesting comments from stakeholders about likely explanations for the declines in total PPS payments, covered IPF days, and covered IPF stays in FY 2020. Next, we looked at estimated outlier payments. Estimated outlier payments were approximately 26 percent higher using the FY 2020 claims data compared to estimated outlier payments using the FY 2019 claims data despite overall covered IPF stays being approximately 17 percent lower using the FY 2020 claims data. As stated above, 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. We examined estimated IPF costs and estimated IPF Federal per diem payment amounts in order to understand the increase in estimated outlier payments. Overall, estimated costs were approximately 12 percent lower when using the FY 2020 claims dataset. However, estimated Federal per diem payment amounts were approximately 15 percent lower. In other words, both estimated costs and estimated Federal per diem payments declined along with the number of stays, but, importantly, estimated Federal per diem payment amounts decreased by a greater amount. When we account for the number of stays, we can see that estimated costs and Federal per diem payment amounts per stay were greater in FY 2020 than in FY 2019, but the increase in estimated cost per stay was greater. Estimated Federal per diem payment amounts per stay were approximately 2.5 percent higher using the FY 2020 claims dataset than estimated Federal per diem payment amounts per stay using the FY 2019 claims dataset. However, estimated costs per stay were about 6.0 percent higher than estimated Federal per diem payments per stay using the FY 2019 claims dataset. In other words, we observed that estimated costs per stay increased by more than estimated IPF Federal per diem payment amounts per stay when the FY 2020 claims dataset was used. As a result, total estimated costs were approximately 12 percent lower but total estimated Federal per diem payments were approximately 15 percent lower. This difference between estimated costs and estimated Federal per diem payments contributed to the 26 percent greater estimated outlier VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 payments using the FY 2020 claims dataset. We wanted to understand whether there were monthly trends in estimated costs and estimated Federal per diem payment amounts that would explain why estimated costs increased more than estimated Federal per diem payment amounts from FY 2019 to FY 2020, and if any of these monthly trends might be related to the COVID–19 PHE. Looking on a monthly basis, we observed that estimated cost per stay and estimated IPF Federal per diem payment per stay generally moved in line with average length of stay until July 2020, however estimated costs remained relatively higher than estimated payments from July 2020 until September 2020. Discharges in our dataset occurring in February and March 2020 had an average length of stay that was roughly 6 percent shorter than for discharges occurring in April 2020, and for May 2020, average length of stay was approximately 4 percent shorter than in the preceding month. We observed comparable peaks and valleys in average cost per stay and average estimated IPF Federal per diem payment per stay. However, the changes in average cost per stay were smaller, around a 3 percent increase from March 2020 to April 2020 and a 3.4 decrease percent from April 2020 to May 2020. Additionally, we observed that estimated cost per stay declined less than average length of stay and estimated IPF Federal per diem payment per stay from July 2020 to September 2020, declining approximately 0.6 percent compared to 1.4 percent for length of stay and 1.5 percent for estimated IPF Federal per diem payment per stay. In other words, we observed that from July 2020 to September 2020, the declines in estimated payments were greater than the declines in estimated costs, and therefore the gap between costs and payments increased during this period. Looking specifically at estimated outlier cases on a monthly basis, we observed a similar trend from March 2020 to May 2020 in average length of stay, estimated IPF Federal per diem payment per stay, and estimated cost per stay to those we observed in all FY 2020 claims in our dataset. However, from July 2020 to September 2020, estimated cost per stay, estimated IPF Federal per diem payment per stay, and average length of stay all increased. Estimated cost per stay and estimated length of stay increased approximately 3.9 percent and 2.0 percent, whereas estimated IPF Federal per diem payment per stay increased by a lower amount, approximately 2.4 percent. PO 00000 Frm 00047 Fmt 4701 Sfmt 4702 19525 Additionally, we observed that estimated outlier payment per outlier stay was approximately 50 percent higher in July 2020 than it was in May 2020. In September 2020 estimated outlier payment per outlier stay was approximately 62 percent higher than May 2020. In other words, we observed that the divergence in estimated costs and estimated payments in our FY 2020 dataset corresponded with the increase in estimated outlier payment per stay. Because the IPF PPS is a per diem payment system, we also looked at whether increased length of stay was contributing to the increased estimated outlier payment per case. Among estimated outlier cases, we calculated the estimated outlier payment per covered IPF day. We observed that estimated outlier payment per covered day was nearly 69 percent greater in July 2020 than it was in May 2020, and remained at a higher level through the end of the year than at the start of the year. Compared to January 2020, average length of stay for estimated outlier cases in September 2020 was approximately 10 percent lower, whereas estimated outlier payment per outlier stay was approximately 52 percent higher. Therefore, we concluded that increased length of stay among estimated outlier cases does not appear to be driving the increase in estimated outlier payments. We examined the distribution of DRGs throughout the FY 2020 claims in our dataset but did not observe variation that would explain the substantial increases in estimated outlier payments. In general, the majority of IPF cases have a DRG of 885 (Psychoses). The percentage of claims with this DRG remained very similar from FY 2019 (74.5 percent) to FY 2020 (75.2 percent), and this percentage did not appear to diverge or fluctuate meaningfully during FY 2020. We also looked at comorbidities and observed that the percentage of cases with a comorbidity increased slightly, from approximately 3.6 percent in our FY 2019 dataset to 3.8 percent in our FY 2020 dataset. In general, most IPF cases in both FY 2019 and FY 2020 did not have any IPF comorbidities. Among cases with at least one comorbidity, the number of cases for each comorbidity category declined in FY 2020, with the exception of Chronic Obstructive Pulmonary Disorder. We note that this is the IPF comorbidity category in which the COVID–19 diagnosis code, U07.1, falls. However, cases with this comorbidity category remained a relatively small percentage of all IPF cases, approximately 0.8 percent in FY 2019 and approximately 1.3 percent in FY 2020. Additionally, among estimated E:\FR\FM\13APP2.SGM 13APP2 jbell on DSKJLSW7X2PROD with PROPOSALS2 19526 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules outlier cases, those with at least one comorbidity received approximately 58 percent less estimated outlier pay per covered day than those without any comorbidities. This makes intuitive sense, because cases with an IPF comorbidity would receive a payment adjustment corresponding to the appropriate IPF comorbidity category, therefore reducing the difference between estimated IPF Federal per diem payments and costs for those cases. Therefore, it does not seem likely that cases with IPF comorbidities were the main driver of the increases in estimated outlier payments. Observing that changes in DRGs and comorbidities did not appear to be driving the increased estimated outlier payments in FY 2020, we wanted to understand what was causing the higher estimated costs relative to estimated IPF Federal per diem payments that we observed in FY 2020. Following our longstanding methodology, we estimate the costs per case based on the covered charges on each IPF claim and the IPF’s most recent CCR. Therefore, in order to better understand estimated costs, we looked at covered charges in FY 2019 and FY 2020. For this analysis, we used a different source for claims which enabled us to calculate covered charge by categories corresponding to the MedPAR ancillary departments. We analyzed FY 2019 and FY 2020 IPF claims data from the Common Working File (CWF). In general, laboratory charges make up roughly one third of the covered charges per IPF claim. Comparing FY 2019 to FY 2020, we observed that covered lab charges per claim in our CWF dataset increased approximately 6.8 percent. Looking on a monthly basis, we observed fluctuation in covered lab charges per claim and per day during the COVID–19 PHE. We looked specifically at the period January 2020 (the month in which the COVID–19 PHE was declared) to September 2020 (the end of FY 2020), and observed peaks and valleys in covered lab charges that we believe may be related to the response to the COVID–19 PHE. Covered lab charges per day increased approximately 6.3 percent (2.4 percent per claim) from January 2020 to March 2020, decreased approximately 7.1 percent (1.1 percent per claim) from March 2020 to April 2020, and then increased approximately 6.2 percent (0.9 percent per claim) from April 2020 to September 2020. Overall, covered lab charges per day increased approximately 4.9 percent (2.2 percent per claim) from January 2020 to September 2020. In other words, most of the 6.8 percent increase in covered lab VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 charges from FY 2019 to FY 2020 occurred during the period January 2020 to September 2020, with the highest levels of lab charges occurring during February/March and June through September. Based on the data available, we are not able to determine the root cause of these increases in covered lab charges during the COVID–19 PHE, however we acknowledge that these increased charges may be related to services in response to the COVID–19 PHE, such as COVID–19 testing. We are requesting comments on this analysis. Specifically, we are requesting comments from stakeholders about likely explanations for the observed fluctuations and overall increases in covered lab charges per claim and per day. We are also requesting comments regarding likely explanations for the increases in estimated cost per stay relative to estimated IPF Federal per diem payment amounts per stay. As discussed in this section, estimated outlier payments increased and estimated total PPS payments decreased, when comparing FY 2020 to FY 2019. Based on our analysis, we believe it is likely that the response to the COVID–19 PHE in FY 2020 has contributed to both of these trends. As a result, in contrast to our usual methodology, we are not confident that FY 2020 claims are the best available data for setting the FY 2022 proposed outlier fixed dollar loss threshold. Furthermore, the distributional effects of the updates presented in column 4 of Table 17 (the budget-neutral update to the IPF wage index, the LRS, and the proposed updated COLA factors) are very similar when using the FY 2019 or FY 2020 claims data. Therefore, we believe the FY 2019 claims would be the best available data for estimating payments in this FY 2022 proposed rulemaking, and we are proposing to use the FY 2019 claims to calculate the outlier fixed dollar loss threshold and wage index budget neutrality factor. IPF payments are therefore estimated to increase by 2.3 percent in urban areas and 2.4 percent in rural areas based on this proposal. Overall, IPFs are estimated to experience a net increase in payments as a result of the updates in this proposed rule. The largest payment increase is estimated at 2.9 percent for IPFs in the South Atlantic region. 4. Effect on Beneficiaries Under the FY 2022 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 PO 00000 Frm 00048 Fmt 4701 Sfmt 4702 section 124 of the BBRA. We expect that updating IPF PPS rates as proposed in this rule will improve or maintain beneficiary access to high quality care by ensuring that payment rates reflect the best available data on the resources involved in inpatient psychiatric care and the costs of these resources. We continue to expect that paying prospectively for IPF services under the FY 2022 IPF PPS will enhance the efficiency of the Medicare program. As discussed in sections IV.E.2, IV.E.3, and V.A.2.d of this proposed rule, we expect that additional program measures will improve follow-up for patients with both mental health and substance use disorders and ensure health-care personnel COVID–19 vaccinations. We also estimate a $20,911,738 reduction in information collection burden as a result of our measure removal proposals. Therefore, we expect that the proposed updates to the IPFQR program will improve quality for beneficiaries. 5. Effects of Updates to the IPFQR Program As discussed in section V. of this proposed rule and in accordance with section 1886(s)(4)(A)(i) of the Act, we will apply a 2 percentage point reduction in the FY 2022 market basket update for IPFs that have failed to comply with the IPFQR Program requirements for FY 2022, including reporting on the required measures. In section V. of this proposed rule, we discuss how the 2 percentage point reduction will be applied. For FY 2021, of the 1,634 IPFs eligible for the IPFQR Program, 43 IPFs (2.6 percent) did not receive the full market basket update because of the IPFQR Program; 31 of these IPFs chose not to participate and 12 did not meet the requirements of the program. We anticipate that even fewer IPFs would receive the reduction for FY 2022 as IPFs become more familiar with the requirements. Thus, we estimate that the IPFQR Program will have a negligible impact on overall IPF payments for FY 2022. Based on the IPFQR Program proposals made in this proposed rule, we estimate a total decrease in burden of 785,477 hours across all IPFs, resulting in a total decrease in information collection burden of $20,911,738 across all IPFs. As discussed in section VI. of this proposed rule, we will attribute the cost savings associated with the proposals to the year in which these savings begin; for the purposes of all the proposals in this proposed rule, that year is FY 2023. Further information on these estimates E:\FR\FM\13APP2.SGM 13APP2 19527 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules can be found in section VI. of this proposed rule. We intend to closely monitor the effects of the IPFQR Program on IPFs and help facilitate successful reporting outcomes through ongoing stakeholder education, national trainings, and a technical help desk. 6. Regulatory Review Costs If regulations impose administrative costs on private entities, such as the time needed to read and interpret this proposed rule, we should estimate the cost associated with regulatory review. Due to the uncertainty involved with accurately quantifying the number of entities that will be directly impacted and will review this proposed rule, we assume that the total number of unique commenters on the most recent IPF proposed rule from FY 2021 (85 FR 20625) will be the number of reviewers of 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 2021 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 solicited 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, 2019 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 $110.74 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 93.5 minutes (1.56 hours) for the staff to review half of this proposed rule, which is approximately 23,365 words. For each IPF that reviews the proposed rule, the estimated cost is (1.56 × $110.74) or $172.75. Therefore, we estimate that the total cost of reviewing this proposed rule is $79,810.50 ($172.75 × 462 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; applying the 2016-based IPF PPS market basket update for FY 2022 of 2.3 percent, reduced by the statutorily required multifactor productivity adjustment of 0.2 percentage point along with the wage index budget neutrality adjustment to update the payment rates; and proposing a FY 2022 IPF wage index which uses the FY 2022 pre-floor, pre-reclassified IPPS hospital wage index as its basis. As discussed in section VI.C.3 of this proposed rule, we also considered using FY 2020 claims data to determine the proposed FY 2022 outlier fixed dollar loss threshold, wage index budget neutrality factor, per diem base rate, and ECT rate. For the reasons discussed in that section, we are proposing to use FY 2019 claims data. 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 18, 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 18 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 1,526 IPFs with data available in the PSF and with claims in our FY 2019 MedPAR claims dataset. Table 18 also includes our best estimate of the cost savings for the 1,634 IPFs eligible for the IPFQR Program. Lastly, Table 18 also includes our best estimate of the costs of reviewing and understanding this proposed rule. TABLE 18—ACCOUNTING STATEMENT: CLASSIFICATION OF ESTIMATED COSTS, SAVINGS, AND TRANSFERS Primary estimate ($million/ year) Category Regulatory Review Costs .................................................................................. Annualized Monetized Costs Savings .............................................................. Annualized Monetized Transfers from Federal Government to IPF Medicare Providers ........................................................................................................ jbell on DSKJLSW7X2PROD with PROPOSALS2 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. VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 Units Low estimate High estimate 0.08 ¥20.91 ¥17.79 .................... ¥15.68 ¥13.34 .................... ¥26.14 ¥22.24 90 .................... .................... 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 17, we estimate that the overall PO 00000 Frm 00049 Fmt 4701 Sfmt 4702 Discount rate (%) Period covered 2020 2020 2020 .................... 7 3 * 2021–2022 * 2023–2031 2023–2031 2020 .................... 2021–2022 Year dollars revenue impact of this proposed rule on all IPFs is to increase estimated Medicare payments by approximately 2.3 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 E:\FR\FM\13APP2.SGM 13APP2 19528 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules 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 V.C.1 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 240 rural excluded psychiatric units and 60 rural psychiatric hospitals in our database of 1,526 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 2021, that threshold is approximately $158 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 $158 million in any one 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. jbell on DSKJLSW7X2PROD with PROPOSALS2 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 chapter IV as set forth below: VerDate Sep<11>2014 19:14 Apr 12, 2021 Jkt 253001 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 412.402 is amended by adding definitions for ‘‘Closure of an IPF’’, ‘‘Closure of an IPF’s residency training program’’, and ‘‘Displaced resident’’ in alphabetical order to read as follows: ■ § 412.402 Definitions. * * * * * Closure of an IPF means closure of a hospital as defined in § 413.79(h)(1)(i) by an IPF meeting the requirements of § 412.404(b) for the purposes of accounting for indirect teaching costs. Closure of an IPF’s residency training program means closure of a hospital residency training program as defined in § 413.79(h)(1)(ii) by an IPF meeting the requirements of § 412.404(b) for the purposes of accounting for indirect teaching costs. * * * * * Displaced resident means a displaced resident as defined in § 413.79(h)(1)(iii) for the purposes of accounting for indirect teaching costs. * * * * * ■ 3. Section 412.424 is amended by revising paragraph (d)(1)(iii)(F) to read as follows: § 412.424 Methodology for calculating the Federal per diem payment amount. * * * * * (d) * * * (1) * * * (iii) * * * (F) Closure of an IPF. (1) For cost reporting periods beginning on or after July 1, 2011, an IPF may receive a temporary adjustment to its FTE cap to reflect displaced residents added because of another IPF’s closure if the IPF meets the following criteria: (i) The IPF is training additional displaced residents from an IPF that closed on or after July 1, 2011. (ii) No later than 60 days after the IPF begins to train the displaced residents, the IPF submits a request to its Medicare contractor for a temporary adjustment to its cap, documents that the IPF is eligible for this temporary adjustment by identifying the displaced residents who have come from the closed IPF and have caused the IPF to exceed its cap, and specifies the length of time the adjustment is needed. (2) Closure of an IPF’s residency training program. If an IPF that closes its residency training program on or PO 00000 Frm 00050 Fmt 4701 Sfmt 4702 after July 1, 2011, agrees to temporarily reduce its FTE cap according to the criteria specified in paragraph (d)(1)(iii)(F)(2)(ii) of this section, another IPF(s) may receive a temporary adjustment to its FTE cap to reflect displaced residents added because of the closure of the residency training program if the criteria specified in paragraph (d)(1)(iii)(F)(2)(i) of this section are met. (i) Receiving IPF(s). For cost reporting periods beginning on or after July 1, 2011, an IPF may receive a temporary adjustment to its FTE cap to reflect displaced residents added because of the closure of another IPF’s residency training program if the IPF is training additional displaced residents from the residency training program of an IPF that closed a program; and if no later than 60 days after the IPF begins to train the displaced residents, the IPF submits to its Medicare Contractor a request for a temporary adjustment to its FTE cap, documents that it is eligible for this temporary adjustment by identifying the displaced residents who have come from another IPF’s closed program and have caused the IPF to exceed its cap, specifies the length of time the adjustment is needed, and submits to its Medicare contractor a copy of the FTE reduction statement by the hospital that closed its program, as specified in paragraph (d)(1)(iii)(F)(2)(ii) of this section. (ii) IPF that closed its program. An IPF that agrees to train displaced residents who have been displaced by the closure of another IPF’s program may receive a temporary FTE cap adjustment only if the hospital with the closed program temporarily reduces its FTE cap based on the FTE of displaced residents in each program year training in the program at the time of the program’s closure. This yearly reduction in the FTE cap will be determined based on the number of those displaced residents who would have been training in the program during that year had the program not closed. No later than 60 days after the displaced residents who were in the closed program begin training at another hospital, the hospital with the closed program must submit to its Medicare contractor a statement signed and dated by its representative that specifies that it agrees to the temporary reduction in its FTE cap to allow the IPF training the displaced residents to obtain a temporary adjustment to its cap; identifies the displaced residents who were in training at the time of the program’s closure; identifies the IPFs to which the displaced residents are transferring once the program closes; and specifies the E:\FR\FM\13APP2.SGM 13APP2 Federal Register / Vol. 86, No. 69 / Tuesday, April 13, 2021 / Proposed Rules reduction for the applicable program years. * * * * * ■ 4. Section 412.434 is amended by revising paragraph (b)(3) to read as follows: § 412.434 Reconsideration and appeals procedures of Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program decisions. jbell on DSKJLSW7X2PROD with PROPOSALS2 * * * VerDate Sep<11>2014 * (b) * * * (3) Contact information for the inpatient psychiatric facility’s chief executive officer and QualityNet security official, including each individual’s name, email address, telephone number, and physical mailing address; * * * * * Dated: March 29, 2021. Elizabeth Richter, Acting Administrator, Centers for Medicare & Medicaid Services. Dated: April 6, 2021. Xavier Becerra, Secretary, Department of Health and Human Services. [FR Doc. 2021–07433 Filed 4–7–21; 4:15 pm] BILLING CODE 4120–01–P * 19:14 Apr 12, 2021 Jkt 253001 PO 00000 Frm 00051 Fmt 4701 Sfmt 9990 19529 E:\FR\FM\13APP2.SGM 13APP2

Agencies

[Federal Register Volume 86, Number 69 (Tuesday, April 13, 2021)]
[Proposed Rules]
[Pages 19480-19529]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-07433]



[[Page 19479]]

Vol. 86

Tuesday,

No. 69

April 13, 2021

Part III





Department of Health and Human Services





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Centers for Medicare & Medicaid Services





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42 CFR Part 412





Medicare Program; FY 2022 Inpatient Psychiatric Facilities Prospective 
Payment System and Quality Reporting Updates for Fiscal Year Beginning 
October 1, 2021 (FY 2022); Proposed Rule

Federal Register / Vol. 86 , No. 69 / Tuesday, April 13, 2021 / 
Proposed Rules

[[Page 19480]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 412

[CMS-1750-P]
RIN 0938-AU40


Medicare Program; FY 2022 Inpatient Psychiatric Facilities 
Prospective Payment System and Quality Reporting Updates for Fiscal 
Year Beginning October 1, 2021 (FY 2022)

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

ACTION: Proposed rule.

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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 Inpatient Prospective Payment System (IPPS) hospital or critical 
access hospital. This rule also proposes to update and clarify the IPF 
teaching policy with respect to IPF hospital closures and displaced 
residents and proposes a technical change to the 2016-based IPF market 
basket price proxies. In addition, this proposed rule would update 
quality measures and reporting requirements under the Inpatient 
Psychiatric Facilities Quality Reporting (IPFQR) Program. These changes 
would be effective for IPF discharges occurring during the Fiscal Year 
(FY) beginning October 1, 2021 through September 30, 2022 (FY 2022).

DATES: To be assured consideration, comments must be received at one of 
the addresses provided below by June 7, 2021.

ADDRESSES: In commenting, please refer to file code CMS-1750-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 https://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-1750-P, P.O. Box 8010, 
Baltimore, MD 21244-8016.
    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-1750-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 
[email protected] 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: https://www.regulations.gov. Follow the search instructions on that website to 
view public comments.

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

    Addendum A to this proposed rule summarizes the FY 2022 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 the complete listing of ICD-10 Clinical 
Modification (CM) and Procedure Coding System codes underlying the Code 
First table, the FY 2022 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 2022 Wage Index for Urban Areas Based 
on Core-Based Statistical Area (CBSA) Labor Market Areas and the FY 
2022 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 the FY 2022 beginning October 1, 2021 
through September 30, 2022. This rule also proposes to update and 
clarify the IPF teaching policy with respect to IPF hospital closures 
and displaced residents and proposes a technical change to the 2016-
based IPF market basket price proxies. In addition, the proposed rule 
would update quality measures and reporting requirements under the 
Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program.

B. Summary of the Major Provisions

1. Inpatient Psychiatric Facilities Prospective Payment System (IPF 
PPS)
    For the IPF PPS, we are proposing to--
     Update IPF PPS teaching policy with respect to IPF 
hospital closures and displaced residents.
     Replace one of the price proxies currently used for the 
For-profit Interest cost category in the 2016-based IPF market basket 
with a similar price proxy.
     Adjust the 2016-based IPF market basket update (2.3 
percent) for economy-wide productivity (0.2 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 2.1 percent 
for FY 2022.
     Make technical rate setting changes: 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 $815.22 to $833.50.
    ++ The IPF PPS Federal per diem base rate for providers who failed 
to report quality data to $817.18.
    ++ The Electroconvulsive therapy (ECT) payment per treatment from 
$350.97 to $358.84.

[[Page 19481]]

    ++ The ECT payment per treatment for providers who failed to report 
quality data to $351.81.
    ++ The labor-related share from 77.3 percent to 77.1 percent.
    ++ The wage index budget-neutrality factor to 1.0014.
    ++ The fixed dollar loss threshold amount from $14,630 to $14,030 
to maintain estimated outlier payments at 2 percent of total estimated 
aggregate IPF PPS payments.
2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
    In this proposed rule, we are proposing to:
     Adopt voluntary patient-level data reporting for data 
submitted for FY 2023 payment determination and mandatory patient-level 
data reporting for FY 2024 payment determination and subsequent years;
     Adopt the Coronavirus disease 2019 (COVID-19) Healthcare 
Personnel (HCP) Vaccination measure for the FY 2023 payment 
determination and subsequent years;
     Adopt the Follow-up After Psychiatric Hospitalization 
(FAPH) measure for the FY 2024 payment determination and subsequent 
years; and
     Remove the following four measures for FY 2024 payment 
determination and subsequent years:
    ++ Alcohol Use Brief Intervention Provided or Offered and Alcohol 
Use Brief Intervention Provided (SUB-2/2a) measure;
    ++ Tobacco Use Brief Intervention Provided or Offered and Tobacco 
Use Brief Intervention Provided (TOB-2/2a) measure;
    ++ Timely Transmission of Transition Record (Discharges from an 
Inpatient Facility to Home/Self Care or Any Other Site of Care) 
measure; and
    ++ Follow-up After Hospitalization for Mental Illness (FUH) 
measure.

C. Summary of Impacts

------------------------------------------------------------------------
                                              Total transfers & cost
         Provision description                      reductions
------------------------------------------------------------------------
FY 2022 IPF PPS payment update.........  The overall economic impact of
                                          this proposed rule is an
                                          estimated $90 million in
                                          increased payments to IPFs
                                          during FY 2022.
FY2023 IPFQR Program update............  The overall economic impact of
                                          the IPFQR Program provisions
                                          of this proposed rule is an
                                          estimated $20,911,738
                                          reduction in information
                                          collection burden.
------------------------------------------------------------------------

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 Prospective Payment System (PPS) for inpatient hospital 
services furnished in psychiatric hospitals and excluded psychiatric 
units including an adequate patient classification system that reflects 
the differences in patient resource use and costs among psychiatric 
hospitals and excluded psychiatric units. ``Excluded psychiatric unit'' 
means a psychiatric unit in an inpatient prospective payment system 
(IPPS) hospital that is excluded from the IPPS, or a psychiatric unit 
in a Critical Access Hospital (CAH) that is excluded from the CAH 
payment system. These excluded psychiatric units would 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. As noted in 
our FY 2020 IPF PPS final rule with comment period, published in the 
Federal Register on August 6, 2019 (84 FR 38424 through 38482), for the 
RY beginning in 2019, the productivity adjustment currently in place 
was equal to 0.4 percentage point.
    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 
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 take into account such reduction in computing the 
payment amount for a subsequent RY. More 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 Fiscal Year 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 
Center for Medicare & Medicaid (CMS) website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/?redirect=/InpatientPsychFacilPPS/.

[[Page 19482]]

B. Overview of the IPF PPS

    The November 2004 IPF PPS final rule (69 FR 66922) 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; additionally, there are 
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.
    In November 2004, we implemented the IPF PPS in a final rule that 
published on November 15, 2004 in the Federal Register (69 FR 66922). 
In developing the IPF PPS, and to ensure that the IPF PPS is able to 
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 15, 2004 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 1. When 
proposing changes in IPF payment policy, a proposed rule would be 
issued in the spring, and the final rule in the summer to be effective 
on October 1. 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, 2020 in the Federal Register titled, ``Medicare Program; 
FY 2021 Inpatient Psychiatric Facilities Prospective Payment System and 
Special Requirements for Psychiatric Hospitals for Fiscal Year 
Beginning October 1, 2020 (FY 2021)'' (85 FR 47042), which updated the 
IPF PPS payment rates for FY 2021. That final rule updated the IPF PPS 
Federal per diem base rates that were published in the FY 2020 IPF PPS 
Rate Update final rule (84 FR 38424) in accordance with our established 
policies.

III. Provisions of the FY 2022 IPF PPS Proposed Rule

A. Proposed Update to the FY 2021 Market Basket 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

[[Page 19483]]

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 2022 IPF Market Basket Update
    For FY 2022 (beginning October 1, 2021 and ending September 30, 
2022), we are proposing to use an estimate of the 2016-based IPF market 
basket increase factor to update the IPF PPS base payment rate. 
Consistent with historical practice, we are proposing to estimate the 
market basket update for the IPF PPS based on IHS Global Inc.'s (IGI) 
forecast (see section III.A.3 of this proposed rule for a discussion of 
a proposed technical update to one price proxy that is part of the 
2016-based IPF market basket). IGI is a nationally recognized economic 
and financial forecasting firm that contracts with the CMS to forecast 
the components of the market baskets and multifactor productivity 
(MFP). For the proposed rule, based on IGI's fourth quarter 2020 
forecast with historical data through the third quarter of 2020, the 
2016-based IPF market basket increase factor for FY 2022 is 2.3 
percent. Therefore, we are proposing that the 2016-based IPF market 
basket update for FY 2022 would be 2.3 percent.
    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 2022 IPF PPS 
proposed rule, based on IGI's fourth quarter 2020 forecast, the 
proposed MFP adjustment for FY 2022 (the 10-year moving average of MFP 
for the period ending FY 2022) is projected to be 0.2 percent. We are 
proposing to reduce the proposed 2.3 percent IPF market basket update 
by this 0.2 percentage point productivity adjustment, as mandated by 
the Act. This results in a proposed estimated FY 2022 IPF PPS payment 
rate update of 2.1 percent (2.3 - 0.2 = 2.1). We are also proposing 
that if more recent data become available, we would use such data, if 
appropriate, to determine the FY 2022 IPF market basket update and MFP 
adjustment for the final rule. For more information on the productivity 
adjustment, we refer readers to the discussion in the FY 2016 IPF PPS 
final rule (80 FR 46675).
3. Proposed Update to IPF Market Basket Price Proxies
    As discussed in section III.A.1. of this proposed rule, the IPF 
market basket is an input price index that consists of cost category 
weights and price proxies derived from the mix of goods and services 
used in providing health care. For FY 2022, for the For-profit Interest 
cost category of the 2016-based IPF market basket, we are proposing to 
use the iBoxx AAA Corporate Bond Yield index instead of the Moody's AAA 
Corporate Bond Yield index. Effective for December 2020, the Moody's 
AAA Corporate Bond series is no longer available for use under license 
to IGI, which is the nationally-recognized economic and financial 
forecasting firm with which we contract to forecast the components of 
the market baskets and MFP.
    We compared the iBoxx AAA Corporate Bond Yield index with the 
Moody's AAA Corporate Bond Yield index and found that the average 
growth rates in the history of the two series are very similar. Over 
the historical time period of FY 2001 to FY 2020, the 4-quarter percent 
change moving average growth in the iBoxx series was approximately 0.1 
percentage point higher, on average, than the Moody's series. However, 
given the relatively small weight for this cost category, replacing the 
Moody's series with the iBoxx series would not impact the historical 
top-line market basket increases when rounded to the nearest tenth of a 
percentage point over the past 10 fiscal years (FY 2011 to FY 2020). 
Therefore, because the iBoxx AAA Corporate Bond Yield index captures 
the same technical concept as the current corporate bond proxy and 
tracks similarly to the current measure that is no longer available, we 
believe that using the iBoxx AAA Corporate Bond Yield index is 
technically appropriate to use in the 2016-based IPF market basket.
4. Proposed FY 2022 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; All Other: Labor-related 
Services; and a portion of the Capital-Related cost weight (46 percent) 
from the 2016-based IPF market basket. The relative importance reflects 
the different rates of price change for these cost categories between 
the base year (FY 2016) and FY 2022. Using IGI's fourth quarter 2020 
forecast for the 2016-based IPF market basket, the proposed IPF labor-
related share for FY 2022 is the sum of the FY 2022 relative importance 
of each labor-related cost category. 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). For FY 2022, the proposed 
labor-related share based on IGI's fourth quarter 2020 forecast of the 
2016-based IPF PPS market basket is 77.1 percent. We are also proposing 
that if more recent data become available, we would use such data, if 
appropriate, to determine the FY 2022 labor-related share for the final 
rule.

B. Proposed Updates to the IPF PPS Rates for FY Beginning October 1, 
2021

    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-

[[Page 19484]]

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. In addition, 
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 Sec.  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/.
    IPFs must include a valid procedure code for ECT services provided 
to IPF beneficiaries in order to bill for ECT services, as described in 
our Medicare Claims Processing Manual, Chapter 3, Section 190.7.3 
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf.) There were no changes to the ECT 
procedure codes used on IPF claims as a result of the proposed update 
to the ICD-10-PCS code set for FY 2022. Addendum B to this proposed 
rule shows the ECT procedure codes for FY 2022 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 2021) Federal per diem base rate is $815.22 and the 
ECT payment per treatment is $350.97. For the proposed FY 2022 Federal 
per diem base rate, we applied the payment rate update of 2.1 percent--
that is, the 2016-based IPF market basket increase for FY 2022 of 2.3 
percent less the productivity adjustment of 0.2 percentage point--and 
the wage index budget-neutrality factor of 1.0014 (as discussed in 
section III.D.1 of this proposed rule) to the FY 2021 Federal per diem 
base rate of $815.22, yielding a proposed Federal per diem base rate of 
$833.50 for FY 2022. Similarly, we applied the 2.1 percent payment rate 
update and the 1.0014 wage index budget-neutrality factor to the FY 
2021 ECT payment per treatment of $350.97, yielding a proposed ECT 
payment per treatment of $358.84 for FY 2022.
    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 requirements under the IPFQR Program, 
we applied a 0.1 percent payment rate update--that is, the IPF market 
basket increase for FY 2022 of 2.3 percent less the productivity 
adjustment of 0.2 percentage point for an update of 2.1 percent, and 
further reduced by 2 percentage points in accordance with section 
1886(s)(4)(A)(i) of the Act--and the wage index budget-neutrality 
factor of 1.0014 to the FY 2021 Federal per diem base rate of $815.22, 
yielding a Federal per diem base rate of $817.18 for FY 2022.
     For IPFs that fail to meet requirements under the IPFQR 
Program, we applied the 0.1 percent annual payment rate update and the 
1.0014 wage index budget-neutrality factor to the FY 2021 ECT payment 
per treatment of $350.97, yielding an ECT payment per treatment of 
$351.81 for FY 2022.

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 continue to use the existing regression-derived adjustment factors 
established in 2005 for FY 2022. 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

[[Page 19485]]

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 2022, we are not proposing any changes to the 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 2022, 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 would still receive the Federal per diem base rate and all other 
applicable adjustments, but the payment would not include an MS-DRG 
adjustment.
    The diagnoses for each IPF MS-DRG would be updated as of October 1, 
2021, using the final IPPS FY 2022 ICD-10-CM/PCS code sets. The FY 2022 
IPPS proposed rule includes tables of the proposed changes to the ICD-
10-CM/PCS code sets, which underlie the FY 2022 IPF MS-DRGs. Both the 
FY 2022 IPPS proposed rule and the tables of proposed changes to the 
ICD-10-CM/PCS code sets, which underlie the FY 2022 MS-DRGs are 
available on the IPPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/.
Code First
    As discussed in the ICD-10-CM Official Guidelines for Coding and 
Reporting, certain conditions have both an underlying etiology and 
multiple body system manifestations due to the underlying etiology. For 
such conditions, the ICD-10-CM has a coding convention that requires 
the underlying condition be sequenced first followed by the 
manifestation. Wherever such a combination exists, there is a ``use 
additional code'' note at the etiology code, and a ``code first'' note 
at the manifestation code. These instructional notes indicate the 
proper sequencing order of the codes (etiology followed by 
manifestation). In accordance with the ICD-10-CM Official Guidelines 
for Coding and Reporting, when a primary (psychiatric) diagnosis code 
has a ``code first'' note, the provider would follow the instructions 
in the ICD-10-CM text. The submitted claim goes through the CMS 
processing system, which will identify the primary 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 our 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 2018, FY 2019 and FY 2020, there were no 
changes to the final ICD-10-CM/PCS codes in the IPF Code First table. 
For FY 2021, there were 18 ICD-10-PCS codes deleted from the final IPF 
Code First table. For FY 2022 there are 18 codes proposed for deletion 
from the ICD-10-CM/PCS codes in the IPF Code First table. The proposed 
FY 2022 Code First table is shown in Addendum B on our 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

[[Page 19486]]

converted to ICD-10-CM/PCS in our FY 2015 IPF PPS final rule (79 FR 
45947 through 45955). The goal for converting the comorbidity 
categories is referred to as replication, meaning that the payment 
adjustment for a given patient encounter is the same after ICD-10-CM 
implementation as it would be if the same record had been coded in ICD-
9-CM and submitted prior to ICD-10-CM/PCS implementation on October 1, 
2015. All conversion efforts were made with the intent of achieving 
this goal. For FY 2022, we are proposing to continue to use the same 
comorbidity adjustment factors in effect in FY 2021, which are found in 
Addendum A, available on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
    We have updated the ICD-10-CM/PCS codes, which are associated with 
the existing IPF PPS comorbidity categories, based upon the proposed FY 
2022 update to the ICD-10-CM/PCS code set. The proposed FY 2022 ICD-10-
CM/PCS updates include: 8 ICD-10-CM diagnosis codes added to the 
Poisoning comorbidity category, 4 codes deleted, and 4 changes to 
Poisoning comorbidity long descriptions; 2 ICD-10-CM diagnosis codes 
added to the Developmental Disabilities comorbidity category and 1 code 
deleted; and 3 ICD-10-PCS codes added to the Oncology Procedures 
comorbidity category. In addition, we are proposing to delete 18 ICD-
10-PCS codes from the Code First Table. These updates are detailed in 
Addenda B of this proposed rule, which are available on our 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 2022 
ICD-10-CM codes to remove codes that were site ``unspecified'' in terms 
of laterality from the FY 2022 ICD-10-CM/PCS codes in instances where 
more specific codes are available. As we stated in the FY 2015 IPF PPS 
final rule, we believe that specific diagnosis codes that narrowly 
identify anatomical sites where disease, injury, or a condition exists 
should be used when coding patients' diagnoses whenever these codes are 
available. We finalized in the FY 2015 IPF PPS rule, that we would 
remove site ``unspecified'' codes from the IPF PPS ICD-10-CM/PCS codes 
in instances when laterality codes (site specified codes) are 
available, as the clinician should be able to identify a more specific 
diagnosis based on clinical assessment at the medical encounter. None 
of the proposed additions to the FY 2022 ICD-10-CM/PCS codes were site 
``unspecified'' by laterality, therefore, we are not removing 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 2022, we are proposing to continue to 
use the patient age adjustments currently in effect in FY 2021, 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 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 rule.
    For FY 2022, we are proposing to continue to use the variable per 
diem adjustment factors currently in effect, as shown in Addendum A of 
this rule (available 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 Sec.  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 15, 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 taking into account 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 Sec.  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.

[[Page 19487]]

    When the IPF PPS was implemented in the November 15, 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 would be based on the FY 2020 pre-
floor, pre-reclassified IPPS hospital wage index rather than on the FY 
2019 pre-floor, pre-reclassified IPPS hospital wage index.
    We explained in the FY 2020 proposed rule (84 FR 16973), that using 
the concurrent pre-floor, pre-reclassified IPPS hospital wage index 
would result in the most up-to-date wage data being the basis for the 
IPF wage index. It would also result in more consistency and parity in 
the wage index methodology used by other Medicare payment systems. The 
Medicare SNF PPS already used the concurrent IPPS hospital wage index 
data as the basis for the SNF PPS wage index. Thus, the wage adjusted 
Medicare payments of various provider types would be based upon wage 
index data from the same timeframe. CMS proposed 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. For FY 2022, we are proposing to continue to 
use the concurrent pre-floor, pre-reclassified IPPS hospital wage index 
as the basis for the IPF wage index.
    We would apply the IPF wage index adjustment to the labor-related 
share of the national base rate and ECT payment per treatment. The 
labor-related share of the national rate and ECT payment per treatment 
would change from 77.3 percent in FY 2021 to 77.1 percent in FY 2022. 
This percentage reflects the labor-related share of the 2016-based IPF 
market basket for FY 2022 (see section III.A.4 of this rule).
b. Office of Management and Budget (OMB) Bulletins
i. 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.
    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).
    On February 28, 2013, OMB issued OMB Bulletin No. 13-01 which 
established revised delineations for Metropolitan Statistical Areas, 
Micropolitan Statistical Areas, and Combined Statistical Areas in the 
United States (U.S.) and Puerto Rico based on the 2010 Census, and 
provided guidance on the use of the delineations of these statistical 
areas using standards published in the June 28, 2010 Federal Register 
(75 FR 37246 through 37252). These OMB Bulletin changes were reflected 
in the FY 2015 pre-floor, pre-reclassified IPPS hospital wage index, 
upon which the FY 2016 IPF wage index was based. We adopted these new 
OMB CBSA delineations in the FY 2016 IPF wage index and subsequent IPF 
wage indexes. We refer readers to the FY 2016 IPF PPS final rule (80 FR 
46682 through 46689) for a full discussion of our implementation of the 
OMB labor market area delineations beginning with the FY 2016 wage 
index.
    On July 15, 2015, OMB issued OMB Bulletin No. 15-01, which provided 
updates to and superseded OMB Bulletin No. 13-01 that was issued on 
February 28, 2013. The attachment to OMB Bulletin No. 15-01 provided 
detailed information on the update to statistical areas since February 
28, 2013. The updates provided in OMB Bulletin No. 15-01 were based on 
the application of the 2010 Standards for Delineating Metropolitan and 
Micropolitan Statistical Areas to Census Bureau population estimates 
for July 1, 2012 and July 1, 2013. The complete list of statistical 
areas incorporating these changes is provided in OMB Bulletin No. 15-
01. A copy of this bulletin may be obtained at https://

[[Page 19488]]

www.whitehouse.gov/omb/information-for-agencies/bulletins/.
    OMB Bulletin No. 15-01 established revised delineations for the 
Nation's Metropolitan Statistical Areas, Micropolitan Statistical 
Areas, and Combined Statistical Areas. The bulletin also provided 
delineations of Metropolitan Divisions as well as delineations of New 
England City and Town Areas. As discussed in the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 56913), the updated labor market area definitions 
from OMB Bulletin 15-01 were implemented under the IPPS beginning on 
October 1, 2016 (FY 2017). Therefore, we implemented these revisions 
for the IPF PPS beginning October 1, 2017 (FY 2018), consistent with 
our historical practice of modeling IPF PPS adoption of the labor 
market area delineations after IPPS adoption of these delineations 
(historically the IPF wage index has been based upon the pre-floor, 
pre-reclassified IPPS hospital wage index from the prior year).
    On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which 
provided updates to and superseded OMB Bulletin No. 15-01 that was 
issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01 
provide detailed information on the update to statistical areas since 
July 15, 2015, and are based on the application of the 2010 Standards 
for Delineating Metropolitan and Micropolitan Statistical Areas to 
Census Bureau population estimates for July 1, 2014 and July 1, 2015. 
In the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), we 
adopted the updates set forth in OMB Bulletin No. 17-01 effective 
October 1, 2019, beginning with the FY 2020 IPF wage index. Given that 
the loss of the rural adjustment was mitigated in part by the increase 
in wage index value, and that only a single IPF was affected by this 
change, we did not believe it was necessary to transition this provider 
from its rural to newly urban status. We refer readers to the FY 2020 
IPF PPS final rule (84 FR 38453 through 38454) for a more detailed 
discussion about the decision to forego a transition plan in FY 2020.
    On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which 
superseded the August 15, 2017 OMB Bulletin No. 17-01, and on September 
14, 2018, OMB issued, OMB Bulletin No. 18-04, which superseded the 
April 10, 2018 OMB Bulletin No. 18-03. These bulletins established 
revised delineations for Metropolitan Statistical Areas, Micropolitan 
Statistical Areas, and Combined Statistical Areas, and provided 
guidance on the use of the delineations of these statistical areas. A 
copy of OMB Bulletin No. 18-04 may be obtained at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf.
    In the FY 2021 IPF PPS final rule (85 FR 47051 through 47059), we 
adopted the updates set forth in OMB Bulletin No. 18-04 effective 
October 1, 2020, beginning with the FY 2021 IPF wage index. These 
updates included material changes to the OMB statistical area 
delineations which included 34 urban counties that became rural, 47 
rural counties that became urban, and 19 counties that moved to a new 
or modified CBSA.
    Given the scope of changes involved in adopting the CBSA 
delineations for FY 2021, we finalized a 2-year transition policy 
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, 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 are 
not proposing to adopt OMB Bulletin 20-01.
ii. 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 the reader 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 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 2022, we are proposing to continue to apply a 17 percent payment 
adjustment for IPFs located in a rural area as defined at Sec.  
412.64(b)(1)(ii)(C) (see 69 FR 66954 for a complete discussion of the 
adjustment for rural locations).
d. 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 2022, 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 2022 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 2022 update to the wage indexes (based on the 
FY 2018 hospital cost report data) and the labor-related share in a 
budget-neutral manner:
    Step 1: Simulate estimated IPF PPS payments, using the FY 2021 IPF 
wage index values (available on the CMS website) and labor-related 
share (as published in the FY 2021 IPF PPS final rule (85 FR 47043).
    Step 2: Simulate estimated IPF PPS payments using the proposed FY 
2022 IPF wage index values (available on the CMS website) and proposed 
FY 2022 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 FY

[[Page 19489]]

2022 budget-neutral wage adjustment factor of 1.0014.
    Step 4: Apply the FY 2022 budget-neutral wage adjustment factor 
from step 3 to the FY 2021 IPF PPS Federal per diem base rate after the 
application of the market basket update described in section III.A of 
this rule, to determine the FY 2022 IPF PPS Federal per diem base rate.
2. Proposed Teaching Adjustment
a. Background
    In the November 2004 IPF PPS final rule, we implemented regulations 
at Sec.  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).
    Medicare makes direct GME payments (for direct costs such as 
resident and teaching physician salaries, and other direct teaching 
costs) to all teaching hospitals including those paid under a PPS, and 
those paid under the TEFRA rate-of-increase limits. These direct GME 
payments are made separately from payments for hospital operating costs 
and are not part of the IPF PPS. The direct GME payments do not address 
the estimated higher indirect operating costs teaching hospitals may 
face.
    The results of the regression analysis of FY 2002 IPF data 
established the basis for the payment adjustments included in the 
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 0.5150 power to result in the teaching 
adjustment. This formula is subject to the limitations on the number of 
FTE residents, which are described in this section of this rule.
    We established the teaching adjustment in a manner that limited the 
incentives for IPFs to add FTE residents for the purpose of increasing 
their teaching adjustment. We imposed a cap on the number of FTE 
residents that may be counted for purposes of calculating the teaching 
adjustment. The cap limits the number of FTE residents that teaching 
IPFs may count for the purpose of calculating the IPF PPS teaching 
adjustment, not the number of residents teaching institutions can hire 
or train. We calculated the number of FTE residents that trained in the 
IPF during a ``base year'' and used that FTE resident number as the 
cap. An IPF's FTE resident cap is ultimately determined based on the 
final settlement of the IPF's most recent cost report filed before 
November 15, 2004 (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 
section III.D.2.b of this proposed rule, we discuss proposed updates to 
the IPF policy on temporary adjustment to the FTE cap.
    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 2022 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.
b. Proposed Update to IPF Teaching Policy on IPF Program Closures and 
Displaced Residents
    For FY 2022, we are proposing to change the IPF policy regarding 
displaced residents from IPF closures and closures of IPF teaching 
programs. Specifically, we are proposing to adopt conforming changes to 
the IPF PPS teaching policy to align with the policy changes that the 
IPPS finalized in the FY 2021 IPPS final rule (85 FR 58865 through 
58870). We believe that the IPF IME policy relating to hospital closure 
and displaced students is susceptible to the same vulnerabilities as 
IPPS GME policy. Hence, if an IPF with a large number of residents 
training in its residency program announces it is closing, these 
residents will become displaced and will need to find alternative 
positions at other IPF hospitals or risk being unable to become Board 
certified. Although we propose to adopt a policy under the IPF PPS that 
is consistent with an applicable policy under the IPPS, the actual caps 
under the two payment systems may not be commingled. In other words, 
the resident cap applicable under the IPPS is separate from the 
resident cap applicable under the IPF PPS; moreover, a provider cannot 
add its IPF resident cap to its IPPS resident cap in order to increase 
the number of residents it receives payment for under either payment 
system.
    Section 124 of the BBRA gives the Secretary broad discretion to 
determine the appropriate adjustment factors for the IPF PPS. We are 
proposing to implement the policy discussed in this section to remain 
consistent with the way that the IPPS teaching policy calculates FTE 
resident caps in the case of a receiving hospital that obtains a 
temporary IME and direct GME cap adjustment for assuming the training 
of displaced residents due to another hospital or residency program's 
closure. We are also proposing that in the future, we would deviate 
from IPPS teaching policy as it pertains to counting displaced 
residents for the purposes of the IPF teaching adjustment only when it 
is necessary and appropriate for the IPF PPS.
    As stated in the November 2004 IPF PPS final rule (69 FR 66922), we 
implemented regulations at Sec.  412.424(d)(1)(iii) to establish a 
facility-level adjustment for IPFs that are, or are part of, teaching 
hospitals. The facility-level adjustment we are providing for teaching 
hospitals under IPF PPS parallels the IME payments paid under the IPPS. 
Both payments are add on adjustments to the amount per case and both 
are based in part on the number of full-time equivalent (FTE) residents 
training at the facility.
    The regulation at 42 CFR 412.424(d)(1)(iii)(F) permits an IPF to 
temporarily adjust its FTE cap to reflect residents added because of 
another hospital or program's closure. We first implemented regulations 
regarding residents displaced by teaching hospital and program closures 
in the May 6, 2011 IPF PPS final rule (76 FR 26431). In that final 
rule, we adopted the IPPS definition of ``closure of a hospital'' at 42 
CFR 413.79(h)(1)(i) to apply to IPF closures as well, and to mean that 
the IPF terminates its Medicare provider agreement as specified in 42 
CFR

[[Page 19490]]

489.52. In this proposed rule, we are proposing to codify this 
definition, as well as the definition of an IPF program closure, at 
Sec.  412.402.
    Although not explicitly stated in regulations text, our current 
policy is that a displaced resident is one that is physically present 
at the hospital training on the day prior to or the day of hospital or 
program closure. This longstanding policy derived from the fact that in 
the regulations text, there are requirements that the receiving 
hospital identifies the residents' ``who have come from the closed 
IPF'' (Sec.  412.424(d)(1)(iii)(F)(1)(ii)) or `identifies the residents 
``who have come from another IPF's closed program'' (Sec.  
412.424(d)(1)(iii)(F)(2)(i)), and that the IPF that closed its program 
identifies '' the residents who were in training at the time of the 
program's closure'' (Sec.  412.424(d)(1)(iii)(F)(2)(ii)). We considered 
the residents who were physically present at the IPF to be those 
residents who were ``training at the time of the program's closure,'' 
thereby granting them the status of ``displaced residents.'' Although 
we did not want to limit the ``displaced residents'' to only those 
physically present at the time of closure, it becomes much more 
administratively challenging for the following groups of residents at 
closing IPFs/programs to continue their training: (1) Residents who 
leave the program after the closure is publicly announced to continue 
training at another IPF, but before the actual closure; (2) residents 
assigned to and training at planned rotations at other IPFs who will be 
unable to return to their rotations at the closing IPF or program; and 
(3) individuals (such as medical students or would-be fellows) who 
matched into resident programs at the closing IPF or program but have 
not yet started training at the closing IPF or program. Other groups of 
residents who, under current policy, are already considered ``displaced 
residents'' include--(1) residents who are physically training in the 
IPF on the day prior to or day of program or IPF closure; and (2) 
residents who would have been at the closing IPF or IPF program on the 
day prior to or of closure but were on approved leave at that time, and 
are unable to return to their training at the closing IPF or IPF 
program.
    We are proposing to amend the IPF policy with regard to closing 
teaching IPFs and closing residency programs to address the needs of 
residents attempting to find alternative IPFs in which to complete 
their training. Additionally, this proposal addresses the incentives of 
originating and receiving IPFs with regard to ensuring we appropriately 
account for their indirect teaching costs by way of an appropriate IPF 
teaching adjustment based on each program's resident FTEs. We are 
proposing to change two aspects of the current IPF policy, which are 
discussed in the following section.
    First, rather than link the status of displaced residents for the 
purpose of the receiving IPF's request to increase their FTE cap to the 
resident's presence at the closing IPF or program on the day prior to 
or the day of program or IPF closure, we propose that the ideal day 
would be the day that the closure was publicly announced, (for example, 
via a press release or a formal notice to the Accreditation Council on 
Graduate Medical Education (ACGME)). This would provide greater 
flexibility for the residents to transfer while the IPF operations or 
residency programs were winding down, rather than waiting until the 
last day of IPF or program operation. This would address the needs of 
the first group of residents as previously described: Residents who 
would leave the IPF program after the closure was publicly announced to 
continue training at another IPF, but before the day of actual closure.
    Second, by removing the link between the status of displaced 
residents and their presence at the closing IPF or program on the day 
prior to or the day of program or IPF closure, we propose to also allow 
the second and third group of residents who are not physically at the 
closing IPF/closing program, but had intended to train at (or return to 
training at, in the case of residents on rotation) to be considered a 
displaced resident. Thus, we are proposing to revise our teaching 
policy with regard to which residents can be considered ``displaced'' 
for the purpose of the receiving IPF's request to increase their FTE 
cap in the situation where an IPF announces publicly that it is 
closing, and/or that it is closing an IPF residency program(s). 
Specifically, we are proposing to adopt the definitions of ``closure of 
a hospital'', ``closure of a hospital residency training program'', and 
``displaced resident'' as defined at 42 CFR 413.79(h) but with respect 
to IPFs and for the purposes of accounting for indirect teaching costs.
    In addition, we are proposing to change another detail of the IPF 
teaching policy specific to the requirements for the receiving IPF. To 
apply for the temporary increase in the FTE resident cap, the receiving 
IPF would have to submit a letter to its Medicare Administrative 
Contractor (MAC) within 60 days of beginning the training of the 
displaced residents. As established under existing regulation at Sec.  
412.424(d)(1)(iii)(F)(1)(ii) and Sec.  412.424(d)(1)(iii)(F)(2)(i), 
this letter must identify the residents who have come from the closed 
IPF or program and have caused the receiving IPF to exceed its cap, and 
must specify the length of time the adjustment is needed. Moreover, we 
want to propose clarifications on how the information would be 
delivered in this letter. Consistent with IPPS teaching policy, we are 
proposing that the letter from the receiving IPF would have to include: 
(1) The name of each displaced resident; (2) the last four digits of 
each displaced resident's social security number; (3) the IPF and 
program in which each resident was training previously; and (4) the 
amount of the cap increase needed for each resident (based on how much 
the receiving IPF is in excess of its cap and the length of time for 
which the adjustments are needed). We are proposing to require the 
receiving hospital to only supply the last four digits of each 
displaced resident's social security number to reduce the amount of 
personally identifiable information (PII) included in these agreements.
    We are also clarifying that, as we previously discussed in the May 
6, 2011 IPF PPS final rule (76 FR 26455), the maximum number of FTE 
resident cap slots that could be transferred to all receiving IPFs is 
the number of FTE resident cap slots belonging to the IPF that has the 
closed program or that is closing. Therefore, if the originating IPF is 
training residents in excess of its cap, then being a displaced 
resident does not guarantee that a cap slot will be transferred along 
with that resident. Therefore, we are proposing that if there are more 
IPF displaced residents than available cap slots, the slots may be 
apportioned according to the closing IPF's discretion. The decision to 
transfer a cap slot if one is available would be voluntary and made at 
the sole discretion of the originating IPF. However, if the originating 
IPF decides to do so, then it would be the originating IPF's 
responsibility to determine how much of an available cap slot would go 
with a particular resident (if any). We also note that, as we 
previously discussed in the May 6, 2011 IPF PPS final rule (76 FR 
25455), only to the extent a receiving IPF would exceed its FTE cap by 
training displaced residents would it be eligible for a temporary 
adjustment to its resident FTE cap. Displaced residents are factored 
into the receiving IPF's ratio of resident FTEs to the facility's 
average daily census.

[[Page 19491]]

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 would 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 think 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 updated for FY 2018, the COLA factors were 
updated in FY 2018 IPPS/LTCH rulemaking (82 FR 38529). As such, we also 
updated the IPF PPS COLA factors for FY 2018 (82 FR 36780 through 
36782) to reflect the updated COLA factors finalized in the FY 2018 
IPPS/LTCH rulemaking.
    For FY 2022, we are proposing to update the COLA factors published 
by OPM for 2009 (as these are the last COLA factors OPM published prior 
to transitioning from COLAs to locality pay) using the methodology that 
we finalized in the FY 2013 IPPS/LTCH PPS final rule and adopted for 
the IPF PPS in the FY 2015 IPF final rule. Specifically, we are 
proposing to update the 2009 OPM COLA factors by a comparison of the 
growth in the Consumer Price Indices (CPIs) for the areas of Urban 
Alaska and Urban Hawaii, relative to the growth in the CPI for the 
average U.S. city as published by the Bureau of Labor Statistics (BLS). 
We note that for the prior update to the COLA factors, we used the 
growth in the CPI for Anchorage and the CPI for Honolulu. Beginning in 
2018, these indexes were renamed to the CPI for Urban Alaska and the 
CPI for Urban Hawaii due to the BLS updating its sample to reflect the 
data from the 2010 Decennial Census on the distribution of the urban 
population (https://www.bls.gov/regions/west/factsheet/2018cpirevisionwest.pdf, accessed January 22, 2021). The CPI for Urban 
Alaska area covers Anchorage and Matanuska-Susitna Borough in the State 
of Alaska and the CPI for Urban Hawaii covers Honolulu in the State of 
Hawaii. BLS notes that the indexes are considered continuous over time, 
regardless of name or composition changes.
    Because BLS publishes CPI data for only Urban Alaska and Urban 
Hawaii, using the methodology we finalized in the FY 2013 IPPS/LTCH PPS 
final rule and adopted for the IPF PPS in the FY 2015 IPF final rule, 
we are proposing to use the comparison of the growth in the overall CPI 
relative to the growth in the CPI for those areas to update the COLA 
factors for all areas in Alaska and Hawaii, respectively. We believe 
that the relative price differences between these urban areas and the 
U.S. (as measured by the CPIs mentioned above) are appropriate proxies 
for the relative price differences between the ``other areas'' of 
Alaska and Hawaii and the U.S.
    BLS publishes the CPI for All Items for Urban Alaska, Urban Hawaii, 
and for the average U.S. city. However, consistent with our methodology 
finalized in the FY 2013 IPPS/LTCH PPS final rule and adopted for the 
IPF PPS in the FY 2015 IPF final rule, we are proposing to create 
reweighted CPIs for each of the respective areas to reflect the 
underlying composition of the IPPS market basket nonlabor-related 
share. The current composition of the CPI for All Items for all of the 
respective areas is approximately 40 percent commodities and 60 percent 
services. However, the IPPS nonlabor-related share is comprised of a 
different mix of commodities and services. Therefore, we are proposing 
to create reweighted indexes for Urban Alaska, Urban Hawaii, and the 
average U.S. city using the respective CPI commodities index and CPI 
services index and proposed shares of 57 percent commodities/43 
percent. We created reweighted indexes using BLS data for 2009 through 
2020--the most recent data available at the time of this proposed 
rulemaking. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38530), we 
created reweighted indexes based on the 2014-based IPPS market basket 
(which was adopted for the FY 2018 IPPS update) and BLS data for 2009 
through 2016 (the most recent BLS data at the time of the FY 2018

[[Page 19492]]

IPPS/LTCH PPS rulemaking), and we updated the IPF PPS COLA factors 
accordingly for FY 2018.
    We continue to believe this methodology is appropriate because we 
continue to make a COLA for hospitals located in Alaska and Hawaii by 
multiplying the nonlabor-related portion of the standardized amount by 
a COLA factor. We note that OPM's COLA factors were calculated with a 
statutorily mandated cap of 25 percent. As stated in the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38530), under the COLA update methodology we 
finalized in the FY 2013 IPPS/LTCH PPS final rule, we exercised our 
discretionary authority to adjust payments to hospitals in Alaska and 
Hawaii by incorporating this cap. In applying this finalized 
methodology for updating the COLA factors, for FY 2022, we are 
proposing to continue to use such a cap, as our policy is based on 
OPM's COLA factors (updated by the methodology described above).
    Applying this methodology, the COLA factors that we are proposing 
to establish for FY 2022 to adjust the nonlabor-related portion of the 
standardized amount for IPFs located in Alaska and Hawaii are shown in 
the Table 1 below. For comparison purposes, we also are showing the 
COLA factors effective for FY 2018 through FY 2021.

 Table 1--Comparison of IPF PPS Cost-of-Living Adjustment Factors: IPFs
                      Located in Alaska and Hawaii
------------------------------------------------------------------------
                                                              FY 2022
                                              FY 2018       through FY
                  Area                      through FY         2025
                                               2021         (proposed)
------------------------------------------------------------------------
Alaska:
    City of Anchorage and 80-kilometer              1.25            1.22
     (50-mile) radius by road...........
    City of Fairbanks and 80-kilometer              1.25            1.22
     (50-mile) radius by road...........
    City of Juneau and 80-kilometer (50-            1.25            1.22
     mile) radius by road...............
    Rest of Alaska......................            1.25            1.24
Hawaii:
    City and County of Honolulu.........            1.25            1.25
    County of Hawaii....................            1.21            1.22
    County of Kauai.....................            1.25            1.25
    County of Maui and County of Kalawao            1.25            1.25
------------------------------------------------------------------------

    The proposed IPF PPS COLA factors for FY 2022 are also shown in 
Addendum A to this proposed rule, and is available 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 Sec.  
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 Sec.  
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 2022, 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).

F. Other Proposed Payment Adjustments and Policies

1. Outlier Payment Overview
    The IPF PPS includes an outlier adjustment to promote access to IPF 
care for those patients who require expensive care and to limit the 
financial risk of IPFs treating unusually costly patients. In the 
November 2004 IPF PPS final rule, we implemented regulations at Sec.  
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

[[Page 19493]]

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 Sec.  
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. For this proposed rulemaking, 
the most recent available data would be the FY 2020 claims. However, 
during FY 2020, the U.S. healthcare system undertook an unprecedented 
response to the Public Health Emergency (PHE) declared by the Health 
and Human Services Secretary on January 31, 2020 in response to the 
outbreak of respiratory disease caused by a novel (new) coronavirus 
that has been named ``SARS CoV 2'' and the disease it causes, which has 
been named ``coronavirus disease 2019'' (abbreviated ``COVID-19''). 
Therefore, as discussed in section VI.C.3 of this proposed rule, we 
considered whether the most recent available year of claims, FY 2020, 
or the prior year, FY 2019, would be the best for estimating IPF PPS 
payments in FY 2021 and FY 2022. We compared the two years' claims 
distributions as well as the impact results, and based on that analysis 
determined that the FY 2019 claims appear to be the best available data 
at this time. We refer the reader to section VI.C.3 of this proposed 
rule for a detailed discussion of that analysis.
    Based on an analysis of the June 2020 update of FY 2019 IPF claims 
and the FY 2021 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 2022 
using FY 2019 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 
2021. Based on an analysis of these updated data, we estimate that IPF 
outlier payments as a percentage of total estimated payments are 
approximately 1.8 percent in FY 2021. Therefore, we are proposing to 
update the outlier threshold amount to $14,030 to maintain estimated 
outlier payments at 2 percent of total estimated aggregate IPF payments 
for FY 2022. This proposed update is a decrease from the FY 2021 
threshold of $14,630. In contrast, using the FY 2020 claims to estimate 
payments, the proposed outlier fixed dollar loss threshold for FY 2022 
would be $19,840, an increase from the FY 2021 threshold of $14,630. We 
refer the reader to section VI.C.3 of this proposed rule for a detailed 
discussion of the estimated impacts of the proposed update to the 
outlier fixed dollar loss threshold, and we invite comments on this 
analysis.
    We note that our proposed use of the FY 2019 claims to set the 
proposed outlier fixed dollar loss threshold for FY 2022 would deviate 
from what has been our longstanding practice of using the most recent 
available year of claims, which is FY 2020 data. However, this proposal 
remains consistent with the established outlier update methodology. As 
discussed in this section and in section VI.C.3 of this proposed rule, 
we are proposing to update the outlier fixed dollar loss threshold 
based on FY 2019 IPF claims in order to maintain the appropriate 
outlier percentage in FY 2022. We are proposing to deviate from our 
longstanding practice of using the most recent available year of claims 
only because and only to the extent that the COVID-19 PHE appears to 
have significantly impacted the FY 2020 IPF claims. As we are able to 
analyze more recent available IPF claims data and better understand 
both the short-term and long-term effects of the COVID-19 PHE on IPFs, 
we intend to re-assess the appropriateness of using FY 2019 IPF claims 
rather than FY 2020 IPF claims for the FY 2022 update.
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 2022, we are proposing 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 2022 is 2.0398 for rural IPFs, and 1.6126 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,

[[Page 19494]]

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 2022 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 2022, to be used 
in each of the three situations listed previously, using the most 
recent CCRs entered in the CY 2021 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. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background and Statutory Authority

    We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589) 
for a discussion of the background and statutory authority \1\ of the 
IPFQR Program.
---------------------------------------------------------------------------

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

B. Covered Entities

    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we 
established that the IPFQR Program's quality reporting requirements 
cover those psychiatric hospitals and psychiatric units paid under 
Medicare's IPF PPS (Sec.  412.404(b)). Generally, psychiatric hospitals 
and psychiatric units within acute care and critical access hospitals 
that treat Medicare patients are paid under the IPF PPS. Consistent 
with previous regulations, we continue to use the terms ``facility'' or 
IPF to refer to both inpatient psychiatric hospitals and psychiatric 
units. This usage follows the terminology in our IPF PPS regulations at 
Sec.  412.402. For more information on covered entities, we refer 
readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645).

C. Previously Finalized Measures and Administrative Procedures

    The current IPFQR Program includes 14 measures. For more 
information on these measures, we refer readers to Table 4 of this 
proposed rule and the following final rules:
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through 
53652);
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through 
50897);
     The FY 2015 IPF PPS final rule (79 FR 45963 through 
45975);
     The FY 2016 IPF PPS final rule (80 FR 46695 through 
46714);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57238 through 
57247);
     The FY 2019 IPF PPS final rule (83 FR 38590 through 
38606); and
     The FY 2020 IPF PPS final rule (84 FR 38459 through 
38467).
    For more information on previously adopted procedural requirements, 
we refer readers to the following rules:
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53653 through 
53660);
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through 
50903);
     The FY 2015 IPF PPS final rule (79 FR 45975 through 
45978);
     The FY 2016 IPF PPS final rule (80 FR 46715 through 
46719);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 through 
57249);
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 through 
38474);
     The FY 2019 IPF PPS final rule (83 FR 38606 through 
38608); and
     The FY 2020 IPF PPS final rule (84 FR 38467 through 
38468).

D. Closing the Health Equity Gap in CMS Quality Programs--Request for 
Information (RFI)

    Persistent inequities in health care outcomes exist in the U.S., 
including among Medicare patients. In recognition of persistent health 
disparities and the importance of closing the health equity gap, we 
request information on revising several CMS programs to make reporting 
of health disparities based on social risk factors and race and 
ethnicity more comprehensive and actionable for facilities, providers, 
and patients. The following is part of an ongoing effort across CMS to 
evaluate appropriate initiatives to reduce health disparities. Feedback 
will be used to inform the creation of a future, comprehensive, RFI 
focused on closing the health equity gap in CMS programs and policies.
    This RFI contains four parts:
     Background: This section provides information describing 
our commitment to health equity, and existing initiatives with an 
emphasis on reducing health disparities.
     Current CMS Disparity Methods: This section describes the 
methods, measures, and indicators of social risk currently used with 
the CMS Disparity Methods.
     Future potential stratification of quality measure 
results: This section describes four potential future expansions of the 
CMS Disparity Methods, including (1) Stratification of Quality Measure 
Results--Dual Eligibility; (2) Stratification of Quality Measure 
Results--Race and Ethnicity; (3) Improving Demographic Data Collection; 
and (4) Potential Creation of a Facility Equity Score to Synthesize 
Results Across Multiple Social Risk Factors.
     Solicitation of public comment: This section specifies 12 
requests for feedback on the above topics. We look forward to receiving 
feedback on these topics, and note our intention for an additional RFI 
or rulemaking on this topic in the future.
1. Background
    Significant and persistent inequities in health care outcomes exist 
in the U.S. Belonging to a racial or ethnic minority group; living with 
a disability; being a member of the lesbian, gay, bisexual, 
transgender, and queer (LGBTQ+) community; living in a rural area; or 
being near or below the poverty level, is often associated with worse 
health outcomes.^{2 3 4 5 6 7 8 9} Such disparities in

[[Page 19495]]

health outcomes are the result of number of factors, but importantly 
for CMS programs, although not the sole determinant, poor access and 
provision of lower quality health care contribute to health 
disparities. For instance, numerous studies have shown that among 
Medicare beneficiaries, racial and ethnic minority individuals often 
receive lower quality of care, report lower experiences of care, and 
experience more frequent hospital readmissions and operative 
complications.^{10 11 12 13 14 15} Readmission rates for common 
conditions in the Hospital Readmissions Reduction Program are higher 
for Black Medicare beneficiaries and higher for Hispanic Medicare 
beneficiaries with Congestive Heart Failure and Acute Myocardial 
Infarction.^{16 17 18 19 20} Studies have also shown that 
African Americans are significantly more likely than white Americans to 
die prematurely from heart disease and stroke.\21\ The COVID-19 
pandemic has further illustrated many of these longstanding health 
inequities with higher rates of infection, hospitalization, and 
mortality among Black, Latino, and Indigenous and Native American 
persons relative to White persons.^{22 23} As noted by the 
Centers for Disease Control ``long-standing systemic health and social 
inequities have put many people from racial and ethnic minority groups 
at increased risk of getting sick and dying from COVID-19.'' \24\ One 
important strategy for addressing these important inequities is 
improving data collection to allow for better measurement and reporting 
on equity across our programs and policies.
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    \2\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \3\ Lindenauer PK, Lagu T, Rothberg MB, et al. Income Inequality 
and 30 Day Outcomes After Acute Myocardial Infarction, Heart 
Failure, and Pneumonia: Retrospective Cohort Study. British Medical 
Journal. 2013;346.
    \4\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity 
of Care in U.S. Hospitals. New England Journal of Medicine. 
2014;371(24):2298-2308.
    \5\ Polyakova, M., et al. Racial Disparities In Excess All-Cause 
Mortality During The Early COVID-19 Pandemic Varied Substantially 
Across States. Health Affairs. 2021; 40(2): 307-316.
    \6\ Rural Health Research Gateway. Rural Communities: Age, 
Income, and Health Status. Rural Health Research Recap. November 
2018.
    \7\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \8\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \9\ Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID-19 
Vulnerability of Transgender Women With and Without HIV Infection in 
the Eastern and Southern U.S. Preprint. medRxiv. 
2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/
2020.07.21.20159327.
    \10\ Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K, 
Burkhart, Q, Klein, DJ, Gildner, J, and Haviland, AM. Racial, 
Ethnic, and Gender Disparities in Health Care in Medicare Advantage. 
Baltimore, MD: CMS Office of Minority Health. 2020.
    \11\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \12\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. Racial 
disparities in knee and hip total joint arthroplasty: An 18-year 
analysis of national Medicare data. Ann Rheum Dis. 2014 
Dec;73(12):2107-15.
    \13\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial 
Disparities in Readmission Rates among Patients Discharged to 
Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672-
1679.
    \14\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \15\ Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day 
readmission rates for Medicare beneficiaries by race and site of 
care. Ann Surg. Jun 2014;259(6):1086-1090.
    \16\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. 
Readmission rates for Hispanic Medicare beneficiaries with heart 
failure and acute myocardial infarction. Am Heart J. Aug 
2011;162(2):254-261 e253.
    \17\ Centers for Medicare and Medicaid Services. Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures; 
2014.
    \18\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \19\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. 
Chronic obstructive pulmonary disease readmissions at minority-
serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680-684.
    \20\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \21\ HHS. Heart disease and African Americans. (March 29, 2021). 
https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \22\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
    \23\ Ochieng N, Cubanski J, Neuman T, Artiga S, and Damico A. 
Racial and Ethnic Health Inequities and Medicare. Kaiser Family 
Foundation. Februray 2021. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
    \24\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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    We are committed to achieving equity in health care outcomes for 
our beneficiaries by supporting providers in quality improvement 
activities to reduce health inequities, enabling them to make more 
informed decisions, and promoting provider accountability for health 
care disparities.\25\ For the purposes of this proposed rule, we are 
using a definition of equity established in Executive Order 13985, as 
``the consistent and systematic fair, just, and impartial treatment of 
all individuals, including individuals who belong to underserved 
communities that have been denied such treatment, such as Black, 
Latino, and Indigenous and Native American persons, Asian Americans and 
Pacific Islanders and other persons of color; members of religious 
minorities; lesbian, gay, bisexual, transgender, and queer (LGBTQ+) 
persons; persons with disabilities; persons who live in rural areas; 
and persons otherwise adversely affected by persistent poverty or 
inequality.'' \26\ We note that this definition was recently 
established by the current administration, and provides a useful, 
common definition for equity across different areas of government, 
although numerous other definitions of equity exist.
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    \25\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \26\ https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-Federal-government.
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    Our ongoing commitment to closing the equity gap in CMS quality 
programs is demonstrated by a portfolio of programs aimed at making 
information on the quality of health care providers and services, 
including disparities, more transparent to consumers and providers. The 
CMS Equity Plan for Improving Quality in Medicare outlines a path to 
equity which aims to support Quality Improvement Networks and Quality 
Improvement Organizations (QIN-QIOs); Federal, state, local, and tribal 
organizations; providers; researchers; policymakers; beneficiaries and 
their families; and other stakeholders in activities to achieve health 
equity.\27\ The CMS Equity Plan for Improving Quality in Medicare 
focuses on three core priority areas which inform our policies and 
programs: (1) Increasing understanding and awareness of health 
disparities; (2) developing and disseminating solutions to achieve 
health equity; and (3) implementing sustainable actions to achieve 
health equity.\28\ The CMS Quality Strategy \29\ and Meaningful 
Measures Framework \30\ include elimination of racial and ethnic 
disparities as a central principle. Our efforts aimed at closing the 
health equity gap to date have included both providing transparency 
about health disparities, supporting providers with evidence-informed 
solutions to achieve health equity, and reporting to providers

[[Page 19496]]

on gaps in quality through the following reports and programs:
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    \27\ Centers for Medicare and Medicaid Services Office of 
Minority Health. The CMS Equity Plan for Improving Quality in 
Medicare. 2015. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \28\ Centers for Medicare and Medicaid Services Office of 
Minority Health. The CMS Equity Plan for Improving Quality in 
Medicare. 2015. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \29\ Centers for Medicare Services. CMS Quality Strategy. 2016. 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \30\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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     The CMS Mapping Medicare Disparities Tool, which is an 
interactive map that identifies areas of disparities and a starting 
point to understand and investigate geographical, racial and ethnic 
differences in health outcomes for Medicare patients.\31\
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    \31\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
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     The Racial, Ethnic, and Gender Disparities in Health Care 
in Medicare Advantage Stratified Report, which highlights racial and 
ethnic differences in health care experiences and clinical care, 
compares quality of care for women and men, and looks at racial and 
ethnic differences in quality of care among women and men separately 
for Medicare Advantage plans.\32\
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    \32\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
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     The Rural-Urban Disparities in Health Care in Medicare 
Report, which details rural-urban differences in health care 
experiences and clinical care.\33\
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    \33\ Centers for Medicare and Medicaid Services. Rural-Urban 
Disparities in Health Care in Medicare. 2019. https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Rural-Urban-Disparities-in-Health-Care-in-Medicare-Report.pdf.
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     The Standardized Patient Assessment Data Elements for 
certain post-acute care Quality Reporting Programs, which now includes 
data reporting for race and ethnicity and preferred language, in 
addition to screening questions for social needs (84 FR 42536 through 
42588).
     The CMS Innovation Center's Accountable Health Communities 
Model, which include standardized data collection of health-related 
social needs data.
     The Guide to Reducing Disparities which provides an 
overview of key issues related to disparities in readmissions and 
reviews sets of activities that can help hospital leaders reduce 
readmissions in diverse populations.\34\
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    \34\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
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     The CMS Disparity Methods, which provide hospital-level 
confidential results stratified by dual eligibility for condition-
specific readmission measures currently included in the Hospital 
Readmission Reduction Program (84 FR 42496 through 42500).
    These programs are informed by reports by the National Academies of 
Science, Engineering and Medicine (NASEM) \35\ and the Office of the 
Assistant Secretary for Planning and Evaluation (ASPE) \36\ which have 
examined the influence of social risk factors on several of our quality 
programs. In this RFI, we address only the sixth initiative listed, the 
CMS Disparity Methods, which we have implemented for measures in the 
Hospital Readmissions Reduction Program and are considering in other 
programs, including the IPFQR Program. We discuss the implementation of 
these methods to date and present considerations for continuing to 
improve and expand these methods to provide providers and ultimately 
consumers with actionable information on disparities in health care 
quality to support efforts at closing the equity gap.
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    \35\ National Academies of Sciences, Engineering, and Medicine. 
2016. Accounting for Social Risk Factors in Medicare Payment: 
Identifying Social Risk Factors. Washington, DC: The National 
Academies Press. https://doi.org/10.17226/21858.
    \36\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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2. Current CMS Disparity Methods
    We first sought public comment on potential confidential and public 
reporting of IPFQR program measure data stratified by social risk 
factors in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 20121). We 
initially focused on stratification by dual eligibility, which is 
consistent with recommendations from ASPE's First Report to Congress 
which was required by the Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 (Pub. L. 113-185).\37\ This report 
found that in the context of value-based purchasing (VBP) programs, 
dual eligibility was among the most powerful predictors of poor health 
outcomes among those social risk factors that ASPE examined and tested.
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    \37\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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    In the FY 2018 IPPS/LTCH PPS final rule we also solicited feedback 
on two potential methods for illuminating differences in outcomes rates 
among patient groups within a provider's patient population that would 
also allow for a comparison of those differences, or disparities, 
across providers for the Hospital IQR Program (82 FR 38403 through 
38409). The first method (the Within-Hospital disparity method) 
promotes quality improvement by calculating differences in outcome 
rates among patient groups within a hospital while accounting for their 
clinical risk factors. This method also allows for a comparison of the 
magnitude of disparity across hospitals, permitting hospitals to assess 
how well they are closing disparity gaps compared to other hospitals. 
The second methodological approach (the Across-Hospital method) is 
complementary and assesses hospitals' outcome rates for dual-eligible 
patients only, across hospitals, allowing for a comparison among 
hospitals on their performance caring for their patients with social 
risk factors. In the FY 2018 IPPS/LTCH PPS proposed rule under the 
IPFQR Program (82 FR 20121), we also specifically solicited feedback on 
which social risk factors provide the most valuable information to 
stakeholders. Overall, comments supported the use of dual eligibility 
as a proxy for social risk, although commenters also suggested 
investigation of additional social risk factors, and we continue to 
consider which risk factors provide the most valuable information to 
stakeholders.
    Concurrent with our comment solicitation on stratification in the 
IPFQR Program, we have considered methods for stratifying measure 
results for other quality reporting programs. For example, FY 2019 
IPPS/LTCH PPS final rule (82 FR 41597 through 41601), we finalized 
plans to provide confidential hospital-specific reports (HSRs) 
containing stratified results of the Pneumonia Readmission (NQF #0506) 
and Pneumonia Mortality (NQF #0468) measures including both the Across-
Hospital Disparity Method and the Within-Hospital Disparity Method 
(disparity methods), stratified by dual eligibility. In the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41554 through 41556), we also removed 
six condition/procedure specific readmissions measures, including the 
Pneumonia Readmission measure (NQF #0506) and five mortality measures, 
including the Pneumonia Mortality measure (NQF #0468) (83 FR 41556 
through 41558) from the Hospital IQR Program. However, the Pneumonia 
Readmission (NQF #0506) and the other condition/procedure measures 
remained in the Hospital Readmissions Reduction Program. In 2019, we 
provided hospitals with results of the Pneumonia Readmission measure 
(NQF #0506) stratified using dual eligibility. We provided this 
information in annual confidential HSRs for claims-based measures.
    We then, in the FY 2020 IPPS/LTCH PPS Final Rule (84 FR 42388 
through 42390), finalized the proposal to provide confidential hospital 
specific reports (HSRs) containing data stratified by dual-eligible 
status for all six readmission measures included in the

[[Page 19497]]

Hospital Readmission Reduction Program.
3. Potential Expansion of the CMS Disparity Methods
    We are committed to advancing health equity by improving data 
collection to better measure and analyze disparities across programs 
and policies.\38\ As we previously noted, we have been considering, 
among other things, expanding our efforts to provide stratified data 
for additional social risk factors and measures, optimizing the ease-
of-use of the results, enhancing public transparency of equity results, 
and building towards provider accountability for health equity. We are 
seeking public comment on the potential stratification of quality 
measures in the IPFQR Program across two social risk factors: Dual 
eligibility and race/ethnicity.
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    \38\ Centers for Medicare Services. CMS Quality Strategy. 2016. 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
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a. Stratification of Quality Measure Results--Dual Eligibility
    As described above, landmark reports by the National Academies of 
Science, Engineering and Medicine (NASEM) \39\ and the Office of the 
Assistant Secretary for Planning and Evaluation (ASPE),\40\ which have 
examined the influence of social risk factors on several of our quality 
programs, have shown that in the context of value-based purchasing 
(VBP) programs, dual eligibility, as an indicator of social risk, is a 
powerful predictor of poor health outcomes. We note that the patient 
population of IPFs has a higher percentage of dually eligible patients 
than the general Medicare population. Specifically, over half (56 
percent) of Medicare patients in IPFs are dually eligible \41\ while 
approximately 20 percent of all Medicare patients are dually 
eligible.\42\ We are considering stratification of quality measure 
results in the IPFQR Program and are considering which measures would 
be most appropriate for stratification and if dual eligibility would be 
a meaningful social risk factor for stratification.
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    \39\ National Academies of Sciences, Engineering, and Medicine. 
2016. Accounting for Social Risk Factors in Medicare Payment: 
Identifying Social Risk Factors. Washington, DC: The National 
Academies Press. https://doi.org/10.17226/21858.
    \40\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
    \41\ https://aspe.hhs.gov/basic-report/transitions-care-and-service-use-among-medicare-beneficiaries-inpatient-psychiatric-facilities-issue-brief.
    \42\ https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/DataStatisticalResources/Downloads/MedicareMedicaidDualEnrollmentEverEnrolledTrendsDataBrief2006-2018.pdf.
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    For the IPFQR Program, we would consider disparity reporting using 
two disparity methods derived from the Within-Hospital and Across-
Hospital methods, described above. The first method (based on the 
Within-Facility disparity method) would aim to promote quality 
improvement by calculating differences in outcome rates between dual 
and non-dual eligible patient groups within a facility while accounting 
for their clinical risk factors. This method would allow for a 
comparison of those differences, or disparities, across facilities, so 
facilities could assess how well they are closing disparity gaps 
compared to other facilities. The second approach (based the Across-
Facility method) would be complementary and assesses facilities' 
outcome rates for subgroups of patients, such as dual eligible 
patients, across facilities, allowing for a comparison among facilities 
on their performance caring for their patients with social risk 
factors.
b. Stratification of Quality Measure Results--Race and Ethnicity
    The Administration's Executive Order on Advancing Racial Equity and 
Support for Underserved Communities Through the Federal Government 
directs agencies to assess potential barriers that underserved 
communities and individuals may face to enrollment in and access to 
benefits and services in Federal Programs. As summarized above, studies 
have shown that among Medicare beneficiaries, racial and ethnic 
minority persons often experience worse health outcomes, including more 
frequent hospital readmissions and operative complications. An 
important part of identifying and addressing inequities in health care 
is improving data collection to allow us to better measure and report 
on equity across our programs and policies. We are considering 
stratification of quality measure results in the IPFQR Program by race 
and ethnicity and are considering which measures would be most 
appropriate for stratification.
    As outlined in the 1997 Office of Management and Budget (OMB) 
Revisions to the Standards for the Collection of Federal Data on Race 
and Ethnicity, the racial and ethnic categories, which may be used for 
reporting the disparity methods are considered to be social and 
cultural, not biological or genetic.\43\ The 1997 OMB Standard lists 
five minimum categories of race: (1) American Indian or Alaska Native; 
(2) Asian; (3) Black or African American; (4) Native Hawaiian or Other 
Pacific Islander; (5) and White. In the OMB standards, Hispanic or 
Latino is the only ethnicity category included, and since race and 
ethnicity are two separate and distinct concepts, persons who report 
themselves as Hispanic or Latino can be of any race.\44\ Another 
example, the ``Race & Ethnicity--CDC'' code system in Public Health 
Information Network (PHIN) Vocabulary Access and Distribution System 
(VADS) \45\ permits a much more granular structured recording of a 
patient's race and ethnicity with its inclusion of over 900 concepts 
for race and ethnicity. The recording and exchange of patient race and 
ethnicity at such a granular level can facilitate the accurate 
identification and analysis of health disparities based on race and 
ethnicity. Further, the ``Race & Ethnicity--CDC'' code system has a 
hierarchy that rolls up to the OMB minimum categories for race and 
ethnicity and, thus, supports aggregation and reporting using the OMB 
standard. ONC includes both the CDC and OMB standards in its criterion 
for certified health IT products.\46\ For race and ethnicity, a 
certified health IT product must be able to express both detailed races 
and ethnicities using any of the 900 plus concepts in the ``Race & 
Ethnicity--CDC'' code system in the PHIN VADS, as well as aggregate 
each one of a patient's races and ethnicities to the categories in the 
OMB standard for race and ethnicity. This approach can reduce burden on 
providers recording demographics using certified products.
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    \43\ Executive Office of the President Office of Management and 
Budget, Office of Information and Regulatory Affairs. Revisions to 
the standards for the classification of Federal data on race and 
ethnicity. Vol 62. Federal Register. 1997:58782-58790.
    \44\ https://www.census.gov/topics/population/hispanic-origin/about.html.
    \45\ https://phinvads.cdc.gov/vads/ViewValueSet.action?id=67D34BBC-617F-DD11-B38D-00188B398520.
    \46\ ONC criteria for certified health IT products: https://www.healthit.gov/isa/representing-patient-race-and-ethnicity.
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    Self-reported race and ethnicity data remain the gold standard for 
classifying an individual according to race or ethnicity. However, CMS 
does not consistently collect self-reported race and ethnicity for the 
Medicare program, but instead gets the data from the Social Security 
Administration (SSA) and the data accuracy and comprehensiveness have 
proven challenging despite capabilities in the marketplace via

[[Page 19498]]

certified health IT products. Historical inaccuracies in Federal data 
systems and limited collection classifications have contributed to the 
limited quality of race and ethnicity information in Medicare's 
administrative data systems.\47\ In recent decades, to address these 
data quality issues, we have undertaken numerous initiatives, including 
updating to data taxonomies and conducting direct mailings to some 
beneficiaries to enable more comprehensive race and ethnic 
identification.\48\ \49\ Despite those efforts, studies reveal varying 
data accuracy in identification of racial and ethnic groups in Medicare 
administrative data, with higher sensitivity for correctly identifying 
White and Black individuals, and lower sensitivity for correctly 
identifying individuals of Hispanic ethnicity or of Asian/Pacific 
Islander and American Indian/Alaskan Native race.\50\ Incorrectly 
classified race or ethnicity may result in overestimation or 
underestimation in the quality of care received by certain groups of 
beneficiaries.
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    \47\ Eicheldinger, C., & Bonito, A. (2008). More accurate racial 
and ethnic codes for Medicare administrative data. Health Care 
Financing Review, 29(3), 27-42.
    \48\ Filice CE, Joynt KE. Examining Race and Ethnicity 
Information in Medicare Administrative Data. Med Care. 
2017;55(12):e170-e176. doi:10.1097/MLR.0000000000000608.
    \49\ Eicheldinger, C., & Bonito, A. (2008). More accurate racial 
and ethnic codes for Medicare administrative data. Health Care 
Financing Review, 29(3), 27-42.
    \50\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities Inventory of Resources 
for Standardized Demographic and Language Data Collection. 2020. 
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
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    We continue to work with Federal and private partners to better 
collect and leverage data on social risk to improve our understanding 
of how these factors can be better measured in order to close the 
health equity gap. Among other things, we have developed an Inventory 
of Resources for Standardized Demographic and Language Data Collection 
\51\ and supported collection of specialized International 
Classification of Disease, 10th Edition, Clinical Modification (ICD-10-
CM) codes for describing the socioeconomic, cultural, and environmental 
determinants of health, and sponsored several initiatives to 
statistically estimate race and ethnicity information when it is 
absent.\52\ The Office of the National Coordinator for Health 
Information Technology (ONC) included social, psychological, and 
behavioral standards in the 2015 Edition health information technology 
(IT) certification criteria (2015 Edition), providing interoperability 
standards (LOINC (Logical Observation Identifiers Names and Codes) and 
SNOMED CT (Systematized Nomenclature of Medicine--Clinical Terms)) for 
financial strain, education, social connection and isolation, and 
others. Additional stakeholder efforts underway to expand capabilities 
to capture additional social determinants of health data elements 
include the Gravity Project to identify and harmonize social risk 
factor data for interoperable electronic health information exchange 
for EHR fields, as well as proposals to expand the ICD-10 
(International Classification of Diseases, Tenth Revision) z-codes, the 
alphanumeric codes used worldwide to represent diagnoses.\53\
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    \51\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities Inventory of Resources 
for Standardized Demographic and Language Data Collection. 2020. 
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
    \52\ https://pubmed.ncbi.nlm.nih.gov/18567241/, https://
pubmed.ncbi.nlm.nih.gov/30506674/, Eicheldinger C, Bonito A. More 
accurate racial and ethnic codes for Medicare administrative data. 
Health Care Finance Rev. 2008;29(3):27-42. Haas A, Elliott MN, 
Dembosky JW, et al. Imputation of race/ethnicity to enable 
measurement of HEDIS performance by race/ethnicity. Health Serv Res. 
2019;54(1):13-23. doi:10.1111/1475-6773.13099.
    \53\ https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
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    While development of sustainable and consistent programs to collect 
data on social determinants of health can be considerable undertakings, 
we recognize that another method to identify better race and ethnicity 
data is needed in the short term to address the need for reporting on 
health equity. In working with our contractors, two algorithms have 
been developed to indirectly estimate the race and ethnicity of 
Medicare beneficiaries (as described further in the following 
paragraphs). We feel that using indirect estimation can help to 
overcome the current limitations of demographic information and enable 
timelier reporting of equity results until longer term collaborations 
to improve demographic data quality across the health care sector 
materialize. The use of indirectly estimated race and ethnicity for 
conducting stratified reporting does not place any additional 
collection or reporting burdens on facilities as these data are derived 
using existing administrative and census-linked data.
    Indirect estimation relies on a statistical imputation method for 
inferring a missing variable or improving an imperfect administrative 
variable using a related set of information that is more readily 
available.\54\ Indirectly estimated data are most commonly used at the 
population level (such as the facility or health plan-level), where 
aggregated results form a more accurate description of the population 
than existing, imperfect data sets. These methods often estimate race 
and ethnicity using a combination of other data sources which are 
predictive of self-identified race and ethnicity, such as language 
preference, information about race and ethnicity in our administrative 
records, first and last names matched to validated lists of names 
correlated to specific national origin groups, and the racial and 
ethnic composition of the surrounding neighborhood. Indirect estimation 
has been used in other settings to support population-based equity 
measurement when self-identified data are not available.\55\
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    \54\ IOM. 2009. Race, Ethnicity, and Language Data: 
Standardization for Health Care Quality Improvement. Washington, DC: 
The National Academies Press.
    \55\ IOM. 2009. Race, Ethnicity, and Language Data: 
Standardization for Health Care Quality Improvement. Washington, DC: 
The National Academies Press.
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    As described above, we have previously supported the development of 
two such methods of indirect estimation of race and ethnicity of 
Medicare beneficiaries. One indirect estimation approach, developed by 
our contractor, uses Medicare administrative data, first name and 
surname matching, derived from the U.S. Census and other sources, with 
beneficiary language preference, state of residence, and the source of 
the race and ethnicity code in Medicare administrative data to 
reclassify some beneficiaries as Hispanic or Asian/Pacific Islander 
(API).\56\ In recent years, we have also worked with another contractor 
to develop a new approach, the Medicare Bayesian Improved Surname 
Geocoding (MBISG), which combines Medicare administrative data, first 
and surname matching, geocoded residential address linked to the 2010 
U.S. Census, and uses both Bayesian updating and multinomial logistic 
regression to estimate the probability of belonging to each of six 
racial/ethnic groups.\57\
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    \56\ Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of 
New Race-Ethnicity Codes and Socioeconomic Status (SES) Indicators 
for Medicare Beneficiaries. Final Report, Sub-Task 2. (Prepared by 
RTI International for the Centers for Medicare and Medicaid Services 
through an interagency agreement with the Agency for Healthcare 
Research and Policy, under Contract No. 500-00-0024, Task No. 21) 
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for 
Healthcare Research and Quality. January 2008.
    \57\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.

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[[Page 19499]]

    The MBISG model is currently used to conduct the national, 
contract-level, stratified reporting of Medicare Part C & D performance 
data for Medicare Advantage Plans by race and ethnicity.\58\ Validation 
testing reveals concordances of 0.88 through 0.95 between indirectly 
estimated and self-report among individuals who identify as White, 
Black, Hispanic and API for the MIBSG version 2.0 and concordances with 
self-reported race and ethnicity of 0.96 through 0.99 for these same 
groups for MBISG version 2.1.\59\ \60\ The algorithms under 
consideration are considerably less accurate for individuals who self-
identify as American Indian/Alaskan Native or multiracial.\61\ Indirect 
estimation can be a statistically reliable approach for calculating 
population-level equity results for groups of individuals (such as the 
facility-level) and is not intended, nor being considered, as an 
approach for inferring the race and ethnicity of an individual.
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    \58\ The Office of Minority Health (2020). Racial, Ethnic, and 
Gender Disparities in Health Care in Medicare Advantage, The Centers 
for Medicare and Medicaid Services, (pg vii). https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
    \59\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.
    \60\ MBISG 2.1 validation results performed under contract #GS-
10F-0012Y/HHSM-500-2016-00097G). Pending public release of the 2021 
Part C and D Performance Data Stratified by Race, Ethnicity, and 
Gender Report, available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
    \61\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23 and Bonito AJ, Bann C, 
Eicheldinger C, Carpenter L. Creation of New Race-Ethnicity Codes 
and Socioeconomic Status (SES) Indicators for Medicare 
Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI 
International for the Centers for Medicare and Medicaid Services 
through an interagency agreement with the Agency for Healthcare 
Research and Policy, under Contract No. 500-00-0024, Task No. 21) 
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for 
Healthcare Research and Quality. January 2008.
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    However, despite the high degree of statistical accuracy of the 
indirect estimation algorithms under consideration there remains the 
small risk of unintentionally introducing bias. For example, if the 
indirect estimation is not as accurate in correctly estimating race and 
ethnicity in certain geographies or populations it could lead to some 
bias in the method results. Such bias might result in slight 
overestimation or underestimation of the quality of care received by a 
given group. We feel this amount of bias is considerably less than 
would be expected if stratified reporting was conducted using the race 
and ethnicity currently contained in our administrative data. Indirect 
estimation of race and ethnicity is envisioned as an intermediate step, 
filling the pressing need for more accurate demographic information for 
the purposes of exploring inequities in service delivery, while 
allowing newer approaches, as described in the next section, for 
improving demographic data collection to progress. We are interested in 
learning more about, and soliciting comments about, the potential 
benefits and challenges associated with measuring facility equity using 
an imputation algorithm to enhance existing administrative data quality 
for race and ethnicity until self-reported information is sufficiently 
available.
c. Improving Demographic Data Collection
    Stratified facility-level reporting using dual eligibility and 
indirectly estimated race and ethnicity would represent an important 
advance in our ability to provide equity reports to facilities. 
However, self-reported race and ethnicity data remain the gold standard 
for classifying an individual according to race or ethnicity. The CMS 
Quality Strategy outlines our commitment to strengthening 
infrastructure and data systems by ensuring that standardized 
demographic information is collected to identify disparities in health 
care delivery outcomes.\62\ Collection and sharing of a standardized 
set of social, psychological, and behavioral data by facilities, 
including race and ethnicity, using electronic data definitions which 
permit nationwide, interoperable health information exchange, can 
significantly enhance the accuracy and robustness of our equity 
reporting.\63\ This could potentially include expansion to additional 
social risk factors, such as disability status, where accuracy of 
administrative data is currently limited. We are mindful that 
additional resources, including data collection and staff training may 
be necessary to ensure that conditions are created whereby all patients 
are comfortable answering all demographic questions, and that 
individual preferences for non-response are maintained.
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    \62\ The Centers for Medicare & Medicaid Services. CMS Quality 
Strategy. 2016. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \63\ The Office of the National Coordinator for Health 
Information Technology. United State Core Data for Interoperability 
Draft Version 2. 2021. https://www.healthit.gov/isa/sites/isa/files/2021-01/Draft-USCDI-Version-2-January-2021-Final.pdf.
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    We are also interested in learning about and are soliciting 
comments on current data collection practices by facilities to capture 
demographic data elements (such as race, ethnicity, sex, sexual 
orientation and gender identity (SOGI), primary language, and 
disability status). Further, we are interested in potential challenges 
facing facility collection, at the time of admission, of a minimum set 
of demographic data elements in alignment with national data collection 
standards (such as the standards finalized by the Affordable Care Act) 
\64\ and standards for interoperable exchange (such as the U.S. Core 
Data for Interoperability incorporated into certified health IT 
products as part of the 2015 Edition of health IT certification 
criteria).\65\ Advancing data interoperability through collection of a 
minimum set of demographic data collection, and incorporation of this 
demographic information into quality measure specifications, has the 
potential for improving the robustness of the disparity method results, 
potentially permitting reporting using more accurate, self-reported 
information, such as race and ethnicity, and expanding reporting to 
additional dimensions of equity, including stratified reporting by 
disability status.
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    \64\ https://minorityhealth.hhs.gov/assets/pdf/checked/1/Fact_Sheet_Section_4302.pdf.
    \65\ https://www.healthit.gov/sites/default/files/2020-08/2015EdCures_Update_CCG_USCDI.pdf.
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d. Potential Creation of a Facility Equity Score To Synthesize Results 
Across Multiple Social Risk Factors
    As we describe in section IV.D.3.a of this proposed rule, we are 
considering expanding the disparity methods to IPFs and to include two 
social risk factors (dual eligibility and race/ethnicity). This 
approach would improve the comprehensiveness of health equity 
information provided to facilities. Aggregated results from multiple 
measures and multiple social risk factors, from the CMS Disparity 
Methods, in the format of a summary score, can improve the usefulness 
of the equity results. In working with our contractors, we recently 
developed an equity summary score for Medicare Advantage contract/
plans, the Health Equity Summary Score (HESS), with application to 
stratified reporting using two social risk factors: dual eligibility 
and race and as described in Incentivizing Excellent Care to At-Risk 
Groups with a Health Equity Summary Score.\66\
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    \66\ Agniel D, Martino SC, Burkhart Q, et al. Incentivizing 
Excellent Care to At-Risk Groups with a Health Equity Summary Score. 
J Gen Intern Med. Published online November 11, 2019 Nov 11. doi: 
10.1007/s11606-019-05473-x.

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[[Page 19500]]

    The HESS calculates standardized and combined performance scores 
blended across the two social risk factors. The HESS also combines 
results of the within-plan (similar to the Within-Facility method) and 
across-plan method (similar to the Across-Facility method) across 
multiple performance measures.
    We are considering building a ``Facility Equity Score,'' not yet 
developed, which would be modeled off the HESS but adapted to the 
context of risk-adjusted facility outcome measures and potentially 
other IPF quality measures. We envision that the Facility Equity Score 
would synthesize results for a range of measures and using multiple 
social risk factors, using measures and social risk factors, which 
would be reported to facilities as part of the CMS Disparity Methods. 
We believe that creation of the Facility Equity Score has the potential 
to supplement the overall measure data already reported on the Care 
Compare or successor website, by providing easy to interpret 
information regarding disparities measured within individual facilities 
and across facilities nationally. A summary score would decrease burden 
by minimizing the number of measure results provided and providing an 
overall indicator of equity.
    The Facility Equity Score under consideration would potentially:
     Summarize facility performance across multiple social risk 
factors (initially dual eligibility and indirectly estimated race and 
ethnicity, as described above); and
     Summarize facility performance across the two disparity 
methods (that is, the Within-Facility Disparity Method and the Across-
Facility Disparity Method) and potentially for multiple measures.
    Prior to any future public reporting, if we determine that a 
Facility Equity Score can be feasibly and accurately calculated, we 
would provide results of the Facility Equity Score, in confidential 
facility specific reports, which facilities and their QIN-QIOs would be 
able to download. Any potential future proposal to display the Facility 
Equity Score on the Care Compare or successor website would be made 
through future RFI or rulemaking.
c. Solicitation of Public Comment
    We are soliciting public comments on the possibility of stratifying 
IPFQR Program measures by dual eligibility and race and ethnicity. We 
are also soliciting public comments on mechanisms of incorporating co-
occurring disability status into such stratification as well. We are 
soliciting public comments on the application of the within-facility or 
across-facility disparities methods IPFQR Program measures if we were 
to stratify IPFQR Program measures. We are also seeking comment on the 
possibility of facility collection of standardized demographic 
information for the purposes of potential future quality reporting and 
measure stratification. In addition, we are soliciting public comments 
on the potential design of a facility equity score for calculating 
results across multiple social risk factors and measures, including 
race and disability. Any data pertaining to these areas that are 
recommended for collection for measure reporting for a CMS program and 
any potential public disclosure on Care Compare or successor website 
would be addressed through a separate and future notice- and-comment 
rulemaking. We plan to continue working with ASPE, facilities, the 
public, and other key stakeholders on this important issue to identify 
policy solutions that achieve the goals of attaining health equity for 
all patients and minimizing unintended consequences. We look forward to 
receiving feedback on these topics. We also note our intention for 
additional RFIs or rulemaking on this topic in the future.
    Specifically, we are soliciting public comment on the following:
Future Potential Stratification of Quality Measure Results
     The possible stratification of facility-specific reports 
for IPFQR program measure data by dual-eligibility status given that 
over half of the patient population in IPFs are dually eligible, 
including, which measures would be most appropriate for stratification;
     The potential future application of indirect estimation of 
race and ethnicity to permit stratification of measure data for 
reporting facility-level disparity results until more accurate forms of 
self-identified demographic information are available;
     Appropriate privacy safeguards with respect to data 
produced from the indirect estimation of race and ethnicity to ensure 
that such data are properly identified if/when it is shared with 
providers.
     Ways to address the challenges of defining and collecting 
accurate and standardized self-identified demographic information, 
including information on race and ethnicity and disability, for the 
purposes of reporting, measure stratification and other data collection 
efforts relating to quality.
     Recommendations for other types of readily available data 
elements for measuring disadvantage and discrimination for the purposes 
of reporting, measure stratification and other data collection efforts 
relating to quality, in addition, or in combination with race and 
ethnicity.
     Recommendations for types of quality measures or 
measurement domains to prioritize for stratified reporting by dual 
eligibility, race and ethnicity, and disability.
     Examples of approaches, methods, research, and/or 
considerations for use of data-driven technologies that do not 
facilitate exacerbation of health inequities, recognizing that biases 
may occur in methodology or be encoded in datasets.
Improving Demographic Data Collection
     Experiences of users of certified health IT regarding 
local adoption of practices for collection of social, psychological, 
and behavioral data elements, the perceived value of using these data 
for improving decision-making and care delivery, and the potential 
challenges and benefits of collecting more granular, structured 
demographic information, such as the ``Race & Ethnicity--CDC'' code 
system.
     The possible collection of a minimum set of social, 
psychological, and behavioral data elements by hospitals at the time of 
admission using structured, interoperable data standards, for the 
purposes of reporting, measure stratification and other data collection 
efforts relating to quality.
Potential Creation of a Facility Equity Score To Synthesize Results 
Across Multiple Social Risk Factors
     The possible creation and confidential reporting of a 
Facility Equity Score to synthesize results across multiple social risk 
factors and disparity measures.
     Interventions facilities could institute to improve a low 
facility equity score and how improved demographic data could assist 
with these efforts.

E. Measure Adoption

    We strive to put consumers and caregivers first, ensuring they are 
empowered to make decisions about their own healthcare along with their 
clinicians using information from data-driven insights that are 
increasingly aligned with meaningful quality measures. We support 
technology that reduces burden and allows clinicians to focus on 
providing high-quality healthcare for their patients. We also

[[Page 19501]]

support innovative approaches to improve quality, accessibility, and 
affordability of care while paying particular attention to improving 
clinicians' and beneficiaries' experiences when interacting with our 
programs. In combination with other efforts across the Department of 
Health and Human Services (HHS), we believe the IPFQR Program helps to 
incentivize facilities to improve healthcare quality and value while 
giving patients and providers the tools and information needed to make 
the best decisions for them. Consistent with these goals, our objective 
in selecting quality measures is to balance the need for information on 
the full spectrum of care delivery and the need to minimize the burden 
of data collection and reporting. We have primarily focused on measures 
that evaluate critical processes of care that have significant impact 
on patient outcomes and support CMS and HHS priorities for improved 
quality and efficiency of care provided by IPFs. When possible, we also 
propose to incorporate measures that directly evaluate patient outcomes 
and experience. We refer readers to section VIII.F.4.a. of the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53645 through 53646) for a detailed 
discussion of the considerations taken into account in selecting 
quality measures.
1. Measure Selection Process
    Before being proposed for inclusion in the IPFQR Program, measures 
are placed on a list of measures under consideration (MUC), which is 
published annually on behalf of CMS by the National Quality Forum 
(NQF). Following publication on the MUC list, the Measure Applications 
Partnership (MAP), a multi-stakeholder group convened by the NQF, 
reviews the measures under consideration for the IPFQR Program, among 
other Federal programs, and provides input on those measures to the 
Secretary. We consider the input and recommendations provided by the 
MAP in selecting all measures for the IPFQR Program. In our evaluation 
of the IPFQR Program measure set, we identified two measures that we 
believe are appropriate to propose for the IPFQR Program.
2. Proposed Adoption of COVID-19 Vaccination Coverage Among Health Care 
Personnel (HCP) \67\ Measure for the FY2023 Payment Determination and 
Subsequent Years
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    \67\ This measure was previously titled, ``SARS-CoV-2 
Vaccination Coverage among Healthcare Personnel.''.
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a. Background
    On January 31, 2020, the Secretary declared a public health 
emergency (PHE) for the U.S. in response to the global outbreak of 
SARS-CoV-2, a novel (new) coronavirus that causes a disease named 
``coronavirus disease 2019'' (COVID-19).\68\ COVID-19 is a contagious 
respiratory illness \69\ that can cause serious illness and death. 
Older individuals and those with underlying medical conditions are 
considered to be at higher risk for more serious complications from 
COVID-19.\70\
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    \68\ U.S. Dept of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. (2020). 
Determination that a Public Health Emergency Exists. Available at: 
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \69\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \70\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
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    As of April 2, 2021, the U.S. has reported over 30 million cases of 
COVID-19 and over 550,000 COVID-19 deaths.\71\ Hospitals and health 
systems saw significant surges of COVID-19 patients as community 
infection levels increased.\72\ From December 2, 2020 through January 
30, 2021, more than 100,000 Americans were in the hospital with COVID-
19 at the same time.\73\
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    \71\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Accessed on April 3, 2021 at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \72\ Associated Press. Tired to the Bone. Hospitals Overwhelmed 
with Virus Cases. November 18, 2020. Accessed on December 16, 2020, 
at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also see: New York Times. 
Just how full are U.S. intensive care units? New data paints an 
alarming picture. November 18, 2020. Accessed on December 16, 2020, 
at: https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \73\ U.S. Currently Hospitalized [bond] The COVID Tracking 
Project https://covidtracking.com/data/charts/us-currently-hospitalized.
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    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\74\ The virus is typically 
transmitted through respiratory droplets or small particles created 
when someone who is infected with the virus coughs, sneezes, sings, 
talks, or breathes.\75\ Thus, the CDC advises that infections mainly 
occur through exposure to respiratory droplets when a person is in 
close contact with someone who has COVID-19.\76\ Experts believe that 
COVID-19 spreads less commonly through contact with a contaminated 
surface (although that is not thought to be a common way that COVID-19 
spreads),\77\ and that in certain circumstances, infection can occur 
through airborne transmission.\78\ According to the CDC, those at 
greatest risk of infection are persons who have had prolonged, 
unprotected close contact (that is, within 6 feet for 15 minutes or 
longer) with an individual with confirmed SARS-CoV-2 infection, 
regardless of whether the individual has symptoms.\79\ Although 
personal protective equipment (PPE) and other infection-control 
precautions can reduce the likelihood of transmission in health care 
settings, COVID-19 can spread between health care personnel (HCP) and 
patients, or from patient to patient given the close contact that may 
occur during the provision of care.\80\ The CDC has emphasized that 
health care settings, including long-term care settings, can be high-
risk places for COVID-19 exposure and transmission.\81\
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    \74\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \75\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \76\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \77\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \78\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \79\ Centers for Disease Control and Prevention. (2021). When to 
Quarantine. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/if-you-are-sick/quarantine.html.
    \80\ Centers for Disease Control and Prevention. (2020). Interim 
U.S. Guidance for Risk Assessment and Work Restrictions for 
Healthcare Personnel with Potential Exposure to COVID-19. Accessed 
on April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
    \81\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
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    Vaccination is a critical part of the nation's strategy to 
effectively counter the spread of COVID-19 and ultimately help restore 
societal functioning.\82\ On

[[Page 19502]]

December 11, 2020, the FDA issued the first Emergency Use Authorization 
(EUA) for a COVID-19 vaccine in the U.S.\83\ Subsequently, the FDA 
issued EUAs for additional COVID-19 vaccines.\84\
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    \82\ Centers for Disease Control and Prevention. (2020). COVID-
19 Vaccination Program Interim Playbook for Jurisdiction Operations. 
Accessed on April 3, 2021 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \83\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144412/download.
    \84\ U.S. Food and Drug Administration. (2020). Moderna COVID-19 
Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download; U.S. Food and Drug 
Administration. (2021). Janssen COVID-19 Vaccine EUA Letter of 
Authorization. Available at https://www.fda.gov/media/146303/download.
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    The FDA determined that it was reasonable to conclude that the 
known and potential benefits of each vaccine, when used as authorized 
to prevent COVID-19, outweighed its known and potential risks.\85\
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    \85\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144412/download and .S. Food and Drug 
Administration. (2020). Moderna COVID-19 Vaccine EUA Letter of 
Authorization. Available at https://www.fda.gov/media/144636/download; U.S. Food and Drug Administration. (2021). Janssen COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/download.
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    As part of its national strategy to address COVID-19, the Biden 
Administration stated that it would work with states and the private 
sector to execute an aggressive vaccination strategy and has outlined a 
goal of administering 200 million shots in 100 days,\86\ Although the 
goal of the U.S. government is to ensure that every American who wants 
to receive a COVID-19 vaccine can receive one, Federal agencies 
recommended that early vaccination efforts focus on those critical to 
the PHE response, including HCP providing direct care to patients with 
COVID-19, and individuals at highest risk for developing severe illness 
from COVID-19.\87\ For example, the CDC's Advisory Committee on 
Immunization Practices (ACIP) recommended that HCP should be among 
those individuals prioritized to receive the initial, limited supply of 
the COVID-19 vaccination given the potential for transmission in health 
care settings and the need to preserve health care system capacity.\88\ 
Research suggests most states followed this recommendation,\89\ and HCP 
began receiving the vaccine in mid-December of 2020.\90\
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    \86\ https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \87\ Health and Human Services, Department of Defense. (2020) 
From the Factory to the Frontlines: The Operation Warp Speed 
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18 
at: https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control 
(2020). COVID-19 Vaccination Program Interim Playbook for 
Jurisdiction Operations. Accessed December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \88\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb. 
Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also recommended that 
long-term care residents be prioritized to receive the vaccine, 
given their age, high levels of underlying medical conditions, and 
congregate living situations make them high risk for severe illness 
from COVID-19.
    \89\ Kates, J, Michaud, J, Tolbert, J. ``How Are States 
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser 
Family Foundation. December 14, 2020. Accessed on December 16 at 
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \90\ Associated Press. `Healing is Coming:' U.S. Health Workers 
Start Getting Vaccine. December 15, 2020. Accessed on December 16 
at: https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
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    There are approximately 18 million healthcare workers in the 
U.S.\91\ As of April 3, 2021 the CDC reported that over 162 million 
doses of COVID-19 vaccine had been administered, and approximately 60 
million people had received a complete vaccination course as described 
in IV.1.b.i of this proposed rule.\92\ President Biden indicated on 
March 2, 2021 that the U.S. is on track to have sufficient vaccine 
supply for every adult by the end of May 2021.\93\
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    \91\ https://www.cdc.gov/niosh/topics/healthcare/
default.html#:~:text=HEALTHCARE%20WORKERS,-
Related%20Pages&text=Healthcare%20is%20the%20fastest%2Dgrowing,of%20t
he%20healthcare%20work%20force.
    \92\ CDC. COVID Data Tracker. COVID-19 Vaccinations in the 
United States. Accessed on 2/18/21 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
    \93\ The White House. Remarks by President Biden on the 
Administration's COVID-19 Vaccination Efforts. Accessed March 18, 
2021 at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/02/remarks-by-president-biden-on-the-administrations-covid-19-vaccination-efforts/.
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    We believe it is important to require that IPFs report HCP 
vaccination in their facilities in order to assess whether they are 
taking steps to protect health care workers and to help sustain the 
ability of IPFs to continue serving their communities throughout the 
PHE and beyond. Therefore, we are proposing a new measure, COVID-19 
Vaccination Coverage Among HCP, beginning with the FY 2023 program 
year. For that program year, IPFs would be required to report data on 
the measure for the fourth quarter of 2021 (October 1, 2021 through 
December 31, 2021). For more information about the proposed reporting 
period, see section V.E.2.c of this proposed rule. The measure would 
assess the proportion of an IPF's health care workforce that has been 
vaccinated against COVID-19.
    Although at this time data to show the effectiveness of COVID-19 
vaccines to prevent asymptomatic infection or transmission of SARS-CoV-
2 are limited, we believe IPFs should report the level of vaccination 
among their HCP as part of their efforts to assess and reduce the risk 
of transmission of COVID-19 within their facilities. HCP vaccination 
can potentially reduce illness that leads to work absence and limit 
disruptions to care.\94\ Data from influenza vaccination demonstrates 
that provider uptake of the vaccine is associated with that provider 
recommending vaccination to patients,\95\ and we believe HCP COVID-19 
vaccination in IPFs could similarly increase uptake among that patient 
population. We also believe that publishing the HCP vaccination rates 
will be helpful to many patients, including those who are at high-risk 
for developing serious complications from COVID-19, as they choose 
facilities from which to seek treatment. Under CMS' Meaningful Measures 
Framework, the COVID-19 measure addresses the quality priority of 
``Promote Effective Prevention and Treatment of Chronic Disease'' 
through the Meaningful Measure Area of ``Preventive Care.''
---------------------------------------------------------------------------

    \94\ Centers for Disease Control and Prevention. Overview of 
Influenza Vaccination among Health Care Personnel. October 2020. 
(2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/long-term-care/why.htm.
    \95\ Measure Application Committee Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: https://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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b. Overview of Measure
    The COVID-19 Vaccination Coverage Among HCP measure (``COVID-19 HCP 
vaccination measure'') is a process measure developed by the CDC to 
track COVID-19 vaccination coverage among HCP in facilities such as 
IPFs.
(1). Measure Specifications
    The denominator is the number of HCP eligible to work in the IPF 
for at least 1 day during the reporting period, excluding persons with 
contraindications to COVID-19 vaccination that are described by the 
CDC.\96\
---------------------------------------------------------------------------

    \96\ Centers for Disease Control and Prevention. 
Contraindications and precautions. https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html#Contraindications.
---------------------------------------------------------------------------

    The numerator is the cumulative number of HCP eligible to work in 
the health care facility for at least 1 day

[[Page 19503]]

during the reporting period and who received a completed vaccination 
course against COVID-19 since the vaccine was first available or on a 
repeated interval if revaccination on a regular basis is needed.\97\ 
Vaccination coverage for the purposes of this measure is defined as the 
estimated percentage of HCP eligible to work at the IPF for at least 1 
day who received a completed vaccination course. A completed 
vaccination course may require one or more doses depending on the EUA 
for the specific vaccine used.
---------------------------------------------------------------------------

    \97\ Measure Application Partnership Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: https://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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    The finalized specifications for this measure will be available at 
https://www.cdc.gov/nhsn/nqf/.
(2). Review by the Measure Applications Partnership
    The COVID-19 HCP vaccination measure was included on the publicly 
available ``List of Measures under Consideration for December 21, 
2020,'' \98\ a list of measures under consideration for use in various 
Medicare programs. When the Measure Applications Partnership (MAP) 
Hospital Workgroup convened on January 11, 2021, it reviewed the MUC 
List and the COVID-19 HCP vaccination measure. The MAP recognized that 
the proposed measure represents a promising effort to advance 
measurement for an evolving national pandemic and that it would bring 
value to the IPFQR Program measure set by providing transparency about 
an important COVID-19 intervention to help prevent infections in HCP 
and patients.\99\ The MAP also stated that collecting information on 
COVID-19 vaccination coverage among HCP and providing feedback to 
facilities will allow facilities to benchmark coverage rates and 
improve coverage in their facility, and that reducing rates of COVID-19 
in HCP may reduce transmission among patients and reduce instances of 
staff shortages due to illness.\100\
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    \98\ https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94212.
    \99\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: https://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \100\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: https://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
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    In its preliminary recommendations, the MAP Hospital Workgroup did 
not support this measure for rulemaking, subject to potential for 
mitigation.\101\ To mitigate its concerns, the MAP believed that the 
measure needed well-documented evidence, finalized specifications, 
testing, and NQF endorsement prior to implementation.\102\ 
Subsequently, the MAP Coordinating Committee met on January 25, 2021, 
and reviewed the COVID-19 Vaccination Coverage Among HCP measure. In 
the 2020-2021 MAP Final Recommendations, the MAP offered conditional 
support for rulemaking contingent on CMS bringing the measures back to 
MAP once the specifications are further refined.\103\ The MAP 
specifically stated, ``the incomplete specifications require immediate 
mitigation and further development should continue.'' \104\ The 
spreadsheet of final recommendations no longer cited concerns regarding 
evidence, testing, or NQF endorsement.\105\ In response to the MAP 
final recommendation request that CMS bring the measure back to the MAP 
once the specifications are further refined, CMS and the CDC met with 
MAP Coordinating committee on March 15th. Additional information was 
provided to address vaccine availability, alignment of the COVID-19 
Vaccination Coverage Among HCP as closely as possible with the data 
collection for the Influenza HCP vaccination measure (NQF 0431) and 
clarification related to how HCP are defined. At this meeting, CMS and 
the CDC presented preliminary findings from the testing of the 
numerator of COVID-19 Vaccination Coverage Among HCP, which is 
currently in process. These preliminary findings show numerator data 
should be feasible and reliable. Testing of the numerator of the number 
of healthcare personnel vaccinated involves a comparison of the data 
collected through NHSN and independently reported through the Federal 
pharmacy partnership program for delivering vaccination to LTC 
facilities. These are two completely independent data collection 
systems. In initial analyses of the first month of vaccination, the 
number of healthcare workers vaccinated in approximately 1,200 
facilities, which had data from both systems the number of healthcare 
personnel vaccinated was highly correlated between these 2 systems with 
a correlation coefficient of nearly 90 percent in the second two weeks 
of reporting.\106\ The MAP further noted that the measure would add 
value to the program measure set by providing visibility into an 
important intervention to limit COVID-19 infections in healthcare 
personnel and the patients for whom they provide care.\107\
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    \101\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: https://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \102\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: https://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \103\ Measure Applications Partnership. 2020-2021 MAP Final 
Recommendations. Accessed on February 3, 2021 at: https://www.qualityforum.org/Setting_Priorities/Partnership/Measure_Applications_Partnership.aspx.
    \104\ Measure Applications Partnership. 2020-2021 MAP Final 
Recommendations. Accessed on February 23, 2021 at: https://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \105\ Ibid.
    \106\ For more information on testing results and other measure 
updates, please see the Meeting Materials (including Agenda, 
Recording, Presentation Slides, Summary, and Transcript) of the 
March 15, 2021 meeting available at https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
    \107\ Measure Applications Partnership. 2020-2021 MAP Final 
Recommendations. Accessed on February 23, 2021 at: https://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
---------------------------------------------------------------------------

    We value the recommendations of the MAP and considered these 
recommendations carefully. Section 1890A(a)(4) of the Act requires the 
Secretary to take into consideration input from multi-stakeholder 
groups in selecting certain quality and efficiency measures. While we 
value input from the MAP, we believe it is important to propose the 
measure as quickly as possible to address the urgency of the COVID-19 
PHE and its impact on vulnerable populations, including IPFs. CMS 
continues to engage with the MAP to mitigate concerns and appreciates 
the MAP's conditional support for the measure.
(3). NQF Endorsement
    Under section 1886(s)(4)(D)(i) of the Act, unless the exception of 
clause (ii) applies, measures selected for the quality reporting 
program must have been endorsed by the entity with a contract under 
section 1890(a) of the Act. The NQF currently holds this contract. 
Section 1886(s)(4)(D)(ii) of the Act provides an exception to the 
requirement for NQF endorsement of measures: In the case of a specified 
area or medical topic determined appropriate by the Secretary for which 
a feasible and practical measure has not been endorsed by the entity 
with a contract under section 1890(a) of the Act, the Secretary may 
specify a measure that is not so endorsed as long as due consideration 
is given to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary.
    This measure is not NQF endorsed and has not been submitted to NQF 
for

[[Page 19504]]

endorsement consideration. CMS will consider the potential for future 
NQF endorsement as part of its ongoing work with the MAP.
    Because this measure is not NQF-endorsed, we considered other 
available measures. We found no other feasible and practical measures 
on the topic of COVID-19 vaccination among HCP, therefore, we believe 
the exception in Section 1186(s)(4)(D)(ii) of the Act applies.
c. Data Collection, Submission and Reporting
    Given the time-sensitive nature of this measure considering the 
PHE, we are proposing that IPFs would be required to begin reporting 
data on the proposed COVID-19 Vaccination Coverage Among HCP measure 
beginning October 1, 2021 for the FY 2023 IPFQR Program year. 
Thereafter, we propose annual reporting periods.
    To report this measure facilities would report COVID-19 vaccination 
data to the NHSN for at least one week each month, beginning in October 
2021 for the October 1, 2021 through December 31, 2021 reporting period 
affecting FY 2023 payment determination and continuing for each quarter 
in subsequent years. For more details on data submission, we refer 
readers to section V.J.2.a of this proposed rule.
    If our proposal to adopt this measure is finalized, IPFs would 
report the measure through the CDC National Healthcare Safety Network 
(NHSN) web-based surveillance system.\108\ While the IPFQR Program does 
not currently require use of the NHSN web-based surveillance system, we 
have previously required use of this system. We refer readers to the FY 
2015 IPF PPS final rule in which we adopted the Influenza Vaccination 
Coverage Among Healthcare Personnel (NQF #0431) measure for additional 
information on reporting through the NHSN web-based surveillance system 
(79 FR 45968 through 45970).
---------------------------------------------------------------------------

    \108\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at: https://www.cdc.gov/nhsn/hps/weekly-covid-vac/. on February 10, 
2021.
---------------------------------------------------------------------------

    IPFs would report COVID-19 vaccination data in the NHSN Healthcare 
Personnel Safety (HPS) Component by reporting the number of HCP 
eligible to have worked at the facility that week (denominator) and the 
number of those HCP who have received a completed vaccination course of 
a COVID-19 vaccination (numerator). For additional information about 
the data reporting requirements, see V.J.4. of this proposed rule.
    We invite public comment on our proposal to add a new measure, 
COVID-19 Vaccination Coverage Among HCP, to the IPFQR Program for the 
FY 2023 payment determination and subsequent years.
3. Proposed Adoption of the Follow-Up After Psychiatric Hospitalization 
(FAPH) Measure for the FY 2024 Payment Determination and Subsequent 
Years
a. Background
    We are proposing one new measure, Follow-Up After Psychiatric 
Hospitalization (FAPH), for the FY 2024 payment determination and 
subsequent years. The FAPH measure would use Medicare fee-for-service 
(FFS) claims to determine the percentage of inpatient discharges from 
an inpatient psychiatric facility (IPF) stay with a principal diagnosis 
of select mental illness or substance use disorders (SUDs) for which 
the patient received a follow-up visit for treatment of mental illness 
or SUD. Two rates would be calculated for this measure: (1) The 
percentage of discharges for which the patient received follow-up 
within 7 days of discharge, and; (2) the percentage of discharges for 
which the patient received follow-up within 30 days of discharge.
    The proposed FAPH measure is an expanded and enhanced version of 
the Follow-Up After Hospitalization for Mental Illness (FUH, NQF #0576) 
measure currently in the IPFQR Program. We are proposing to adopt the 
FAPH measure and replace the FUH measure and refer readers to section 
IV.F.2.d of this proposed rule for our proposal to remove the FUH 
measure contingent on adoption of the FAPH measure. The FUH (NQF #0576) 
measure uses Medicare FFS claims to determine the percentage of 
inpatient discharges from an IPF stay with a principal diagnosis of 
select mental illness diagnoses for which the patient received a 
follow-up visit for treatment of mental illness, and it excludes 
patients with primary substance use diagnoses. During the 2017 
comprehensive review of NQF #0576, the NQF Behavioral Health Standing 
Committee (BHSC) recommended expanding the measure population to 
include patients hospitalized for drug and alcohol disorders, because 
these patients also require follow-up care after they are discharged. 
In 2018, CMS began development of a measure to expand the IPFQR FUH 
population to include patients with principal SUD diagnoses to address 
the NQF BHSC recommendation and the CMS Meaningful Measures priority to 
promote treatment of SUDs. The FAPH measure would expand the number of 
discharges in the denominator by about 35 percent over the current FUH 
measure by adding patients with SUD or dementia, populations that also 
benefit from timely follow-up care.
    Furthermore, compared to the criteria for provider type in the 
current FUH measure, the FAPH measure does not limit the provider type 
for the follow-up visit if it is billed with a diagnosis of mental 
illness or SUD. During the measure's testing, the most frequent 
provider types for the FAPH measure were family or general practice 
physicians, internal medicine physicians, nurse practitioners, and 
physician assistants. The technical expert panel (TEP) convened by our 
contractor agreed that these provider types should be credited by the 
measure for treating mental illness and SUD and confirmed that this is 
aligned with integrated care models that aim to treat the whole 
patient. The TEP further noted that in areas where there are shortages 
of mental health or SUD clinicians, other types of providers are often 
the only choice for follow-up treatment. Allowing visits to these types 
of providers to count towards the numerator allows the measure to 
capture the rates of appropriate follow-up care more accurately in 
areas with provider shortages.
    Performance on the FAPH measure indicates that follow-up rates for 
patients hospitalized with mental illness or SUD are less than optimal 
and that room for improvement is ample. The clinical benefits of timely 
follow-up care after hospitalization, including reduced risk of 
readmission and improved adherence to medication, are well-documented 
in the published literature.^{109 110 111 112 113 114 115}
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    \109\ Tong, L., Arnold, T., Yang, J., Tian, X., Erdmann, C., & 
Esposito, T. (2018). The association between outpatient follow-up 
visits and all-cause non-elective 30-day readmissions: A 
retrospective observational cohort study. PloS one, 13(7), e0200691. 
https://doi.org/10.1371/journal.pone.0200691.
    \110\ Terman, S.W., Reeves, M.J., Skolarus, L.E., & Burke, J.F. 
(2018). Association Between Early Outpatient Visits and Readmissions 
After Ischemic Stroke. Circulation. Cardiovascular quality and 
outcomes, 11(4), e004024. https://doi.org/10.1161/CIRCOUTCOMES.117.004024.
    \111\ First Outpatient Follow-Up After Psychiatric 
Hospitalization: Does One Size Fit All? (2014). Psychiatric 
Services, 66(6), 364-372. https://doi.org/10.1176/appi.ps.201400081.
    \112\ Terman, S.W., Reeves, M.J., Skolarus, L.E., & Burke, J.F. 
(2018). Association Between Early Outpatient Visits and Readmissions 
After Ischemic Stroke. Circulation. Cardiovascular quality and 
outcomes, 11(4), e004024. https://doi.org/10.1161/CIRCOUTCOMES.117.004024.
    \113\ Jackson, C., Shahsahebi, M., Wedlake, T., & DuBard, C.A. 
(2015). Timeliness of outpatient follow-up: An evidence-based 
approach for planning after hospital discharge. Annals of family 
medicine, 13(2), 115-122. https://doi.org/10.1370/afm.1753.
    \114\ Hernandez, A.F., Greiner, M.A., Fonarow, G.C., Hammill, 
B.G., Heidenreich, P.A., Yancy, C.W., Peterson, E.D., & Curtis, L.H. 
(2010). Relationship between early physician follow-up and 30-day 
readmission among Medicare beneficiaries hospitalized for heart 
failure. JAMA, 303(17), 1716-1722. https://doi.org/10.1001/jama.2010.533.
    \115\ Nadereh Pourat, Xiao Chen, Shang-Hua Wu and Anna C. Davis. 
Timely Outpatient Follow-up Is Associated with Fewer Hospital 
Readmissions among Patients with Behavioral Health Conditions. The 
Journal of the American Board of Family Medicine. May 2019, 32 (3) 
353-361; DOI: https://doi.org/10.3122/jabfm.2019.03.180244.

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[[Page 19505]]

    Behavioral health patients in particular have a number of risk 
factors that underscore the need for timely follow-up and continuity of 
care: Behavioral health patients have higher baseline hospitalization 
rates, higher hospital readmission rates, and higher health care costs 
as compared with the general population of patients.^{116 117} 
Among patients with serious mental illness, 90 percent have comorbid 
clinical conditions such as hypertension, cardiovascular disease, 
hyperlipidemia, or diabetes.\118\ Among patients hospitalized for 
general medical conditions, those who also have a mental illness are 28 
percent more likely to be readmitted within 30 days than their 
counterparts without a psychiatric comorbidity.\119\ The high 
prevalence of clinical comorbidities among behavioral health patients, 
combined with the compounding effect of mental illness on patients with 
general medical conditions, suggests that behavioral health patients 
are uniquely vulnerable and supports the intent of the measure to 
increase follow-up after hospitalization.
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    \116\ Germack, H.D., et al. (2019, January). Association of 
comorbid serious mental illness diagnosis with 30-day medical and 
surgical readmissions. JAMA Psychiatry.
    \117\ First Outpatient Follow-Up After Psychiatric 
Hospitalization: Does One Size Fit All? (2014). Psychiatric 
Services, 66(6), 364-372. https://doi.org/10.1176/appi.ps.201400081.
    \118\ First Outpatient Follow-Up After Psychiatric 
Hospitalization: Does One Size Fit All? (2014). Psychiatric 
Services, 66(6), 364-372. https://doi.org/10.1176/appi.ps.201400081.
    \119\ Benjenk, I., & Chen, J. (2018). Effective mental health 
interventions to reduce hospital readmission rates: A systematic 
review. Journal of hospital management and health policy, 2, 45. 
https://doi.org/10.21037/jhmhp.2018.08.05.
---------------------------------------------------------------------------

    In addition, clinical practice guidelines stress the importance of 
continuity of care between settings for patients with mental illness 
and SUD. For the treatment of SUD patients, the 2010 guidelines of the 
American Psychiatric Association (APA) state: ``It is important to 
intensify the monitoring for substance use during periods when the 
patient is at a high risk of relapsing, including during the early 
stages of treatment, times of transition to less intensive levels of 
care, and the first year after active treatment has ceased.'' \120\ 
This statement is accompanied by a grade of [I], which indicates the 
highest level of APA endorsement: ``recommended with substantial 
clinical evidence.''
---------------------------------------------------------------------------

    \120\ American Psychiatric Association. Practice guideline for 
the treatment of patients with substance use disorders. 2010. https://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/substanceuse.pdf.
---------------------------------------------------------------------------

    Evidence supports that outpatient follow-up care and interventions 
after hospital discharges are associated with a decreased risk of 
readmissions for patients with mental illness.^{121 122} IPFs 
can influence rates of follow-up care for patients hospitalized for 
mental illness or SUD. Three studies reported that with certain 
interventions--such as pre-discharge transition interviews, appointment 
reminder letters or reminder phone calls, meetings with outpatient 
clinicians before discharge, and meetings with inpatient staff familiar 
to patients at the first post-discharge appointment--facilities 
achieved 30-day follow-up rates of 88 percent or 
more.^{123 124 125} This is substantially higher than the 
national rate of about 52 percent observed in the current FUH measure 
for Medicare FFS discharges between July 1, 2016, and June 30, 
2017.\126\ Medicare FFS data from July 1, 2016, to June 30, 2017, show 
the national 7-day follow-up rate to be 35.5 percent and the 30-day 
rate to be 61.0 percent. These data reveal wide variation in follow-up 
rates across facilities, with a 16.9 percent absolute difference 
between the 25th and 75th percentiles for the 7-day rate and a 17.4 
percent absolute difference for the 30-day rate. If all facilities 
achieved the benchmark follow-up rates for their Medicare FFS patients 
(as calculated using the AHRQ Achievable Benchmarks of Care 
method),\127\ 53,841 additional discharges would have a 7-day follow-up 
visit, and 47,552 would have a 30-day follow-up visit.\128\
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    \121\ Kurdyak P, Vigod SN, Newman A, Giannakeas V, Mulsant BH, 
Stukel T. Impact of Physician Follow-Up Care on Psychiatric 
Readmission Rates in a Population-Based Sample of Patients With 
Schizophrenia. Psychiatr Serv. 2018;69(1):61-68. doi: 10.1176/
appi.ps.201600507.
    \122\ Marcus SC, Chuang CC, Ng-Mak DS, Olfson M. Outpatient 
follow-up care and risk of hospital readmission in schizophrenia and 
bipolar disorder. Psychiatr Serv. 2017;68(12):1239-1246. doi: 
10.1176/appi.ps.201600498.
    \123\ Batscha C, McDevitt J, Weiden P, Dancy B. The effect of an 
inpatient transition intervention on attendance at the first 
appointment post discharge from a psychiatric hospitalization. J Am 
Psychiatr Nurses Assoc. 2011;17(5):330-338. doi: 10.1177/
1078390311417307.
    \124\ Agarin T, Okorafor E, Kailasam V, et al. Comparing kept 
appointment rates when calls are made by physicians versus behavior 
health technicians in inner city hospital: Literature review and 
cost considerations. Community Ment Health J. 2015;51(3):300-304. 
doi: 10.1007/s10597-014-9812-x.
    \125\ Olfson M, Mechanic D, Boyer CA, Hansell S. Linking 
inpatients with schizophrenia to outpatient care. Psychiatr Serv. 
1998;49(7):911-917. doi: 10.1176/ps.49.7.911. Quality AFHRA. 2017 
National Healthcare Quality and Disparities Report. Rockville, MD: 
Services USDoHaH; 2018.
    \126\ https://data.cms.gov/provider-data/archived-data/
hospitals''.
    \127\ https://nhqrnet.ahrq.gov/inhqrdr/resources/methods#Benchmarks.
    \128\ Quality AfHRa. 2017 National Healthcare Quality and 
Disparities Report. Rockville, MD: Services USDoHaH; 2018.
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    During the development process, we used the CMS Quality Measures 
Public Comment Page to ask for public comments on the measure.\129\ We 
accepted public comments from Friday, January 25, 2019, to Wednesday, 
February 13, 2019. During this period, we received comments from 29 
organizations or individuals. Many commenters acknowledged the 
importance of developing a measure that assesses acute care providers 
for follow-up post-hospitalization. Some commenters expressed 
skepticism about the measure's appropriateness as a tool for evaluating 
the performance of discharging IPFs due to factors beyond the IPFs' 
control that can affect whether a patient receives timely post-
discharge follow-up care. Ten stakeholders expressed support for the 
measure based on the expanded list of qualifying diagnoses in the 
denominator and the inclusion of more patients who could benefit from 
post-discharge follow-up visits.\130\
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    \129\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/IPF_-Follow-Up-After-Psychiatric-Hospitalization_Public-Comment-Summary.pdf.
    \130\ Mathematica. FAPH public comment summary. April 2019.
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    We reviewed the comments we received with the TEP, whose members 
shared similar feedback regarding the importance of follow-up for 
patients with both mental health diagnoses and substance use disorders, 
as well as concerns about the ability of IPFs to influence follow-up 
care. We agree with commenters that some factors that influence follow-
up are outside of a facility's control. However, as described, in 
section IV.E.3.a, we believe that there are interventions (such as pre-
discharge transition interviews, appointment reminder letters or 
reminder phone calls, meetings with outpatient

[[Page 19506]]

clinicians before discharge, and meetings with inpatient staff familiar 
to patients at the first post-discharge appointment) that allow 
facilities to improve their follow-up adherence. We remain committed to 
monitoring follow-up to improve health outcomes and view this measure 
as an expansion of our ability to measure appropriate follow-up care 
established by FUH.
b. Overview of Measure
(1). Measure Calculation
    The FAPH measure would be calculated by dividing the number of 
discharges that meet the numerator criteria by the number that meet the 
denominator criteria. Two rates are reported for this measure: The 7-
day rate and the 30-day rate.
(a) Numerator
    The first rate that would be reported for this measure includes 
discharges from a psychiatric facility that are followed by an 
outpatient visit for treatment of mental illness or SUD within 7 days. 
The second rate reported for this measure would include discharges from 
a psychiatric facility that are followed by an outpatient visit for 
treatment of mental illness or SUD within 30 days. Outpatient visits 
are defined as outpatient visits, intensive outpatient encounters, or 
partial hospitalization and are defined by the Current Procedural 
Terminology (CPT), Healthcare Common Procedure Coding System (HCPCS), 
and Uniform Billing (UB) Revenue codes. Claims with codes for emergency 
room visits do not count toward the numerator.
(b) Denominator
    The denominator includes discharges paid under the IPF prospective 
payment system during the performance period for Medicare FFS patients 
with a principal diagnosis of mental illness or SUD. Specifically, the 
measure includes IPF discharges for which the patient was:
     Discharged with a principal diagnosis of mental illness or 
SUD that would necessitate outpatient follow-up care,
     Alive at the time of discharge,
     Enrolled in Medicare Parts A and B during the month of the 
discharge date and at least one month after the discharge date to 
ensure that data are available to capture the index admission and 
follow-up visits, and
     Age 6 or older on the date of discharge, because follow-up 
treatment for mental illness or SUD might not always be recommended for 
younger children.
    The denominator excludes IPF discharges for patients who:
     Were admitted or transferred to acute and non-acute 
inpatient facilities within the 30-day follow-up period, because 
admission or transfer to other institutions could prevent an outpatient 
follow-up visit from taking place,
     Were discharged against medical advice, because the IPF 
could have limited opportunity to complete treatment and prepare for 
discharge,
     Died during the 30-day follow-up period, or
     Use hospice services or elect to use a hospice benefit at 
any time during the measurement year regardless of when the services 
began, because hospice patients could require different follow-up 
services.
    The FAPH measure differs from FUH mostly in the expansion of the 
measure population to include SUD and other mental health diagnoses in 
the measure's denominator, but it includes some additional differences:
     The FAPH measure simplifies the exclusion of admission or 
transfer to acute or non-acute inpatient facilities within 30 days 
after discharge by aligning with the HEDIS[supreg] Inpatient Stay Value 
Set used in both the HEDIS[supreg] FUH and the HEDIS[supreg] Follow-Up 
After Emergency Department Visit for Alcohol and Other Drug Abuse or 
Dependence (FUA) measures to identify acute and non-acute inpatient 
stays. A discharge is excluded from the FAPH measure if it is followed 
by an admission or a transfer with one of the codes in the value set.
     The FAPH measure uses Medicare UB Revenue codes (rather 
than inpatient discharge status code, which the FUH measure uses) to 
identify discharge or transfer to other health care institutions. This 
is to align better with the intent of the HEDIS[supreg] FUH and 
HEDIS[supreg] FUA measures.
     The FAPH measure allows mental illness or SUD diagnoses in 
any position on the follow-up visit claim to count toward the numerator 
and does not require that it be in the primary position as the FUH 
measure does.
(2) Measure Reliability and Validity
    In 2019, CMS used the final measure specifications to complete 
reliability and validity testing, which revealed that the FAPH measure 
provides reliable and valid facility-level rates of follow-up after 
psychiatric hospitalization. We evaluated measure reliability based on 
a signal-to-noise analysis,\131\ in which a score of 0.0 implies that 
all variation is attributed to measurement error (noise), and a score 
of 1.0 implies that all measure score variation is caused by a real 
difference in performance across IPFs. Using that approach, we 
established a minimum denominator size of 40 discharges to attain an 
overall reliability score of 0.7 for both the 7-day and the 30-day 
rate. These analyses revealed that the measure can reliably distinguish 
differences in performance between IPFs with adequate denominator size.
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    \131\ For additional information on reliability tests see https://www.qualityforum.org/Measuring_Performance/Improving_NQF_Process/Measure_Testing_Task_Force_Final_Report.aspx.
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    We evaluated the validity of the measure based on its correlation 
to two conceptually related measures in the IPFQR Program: The 30-Day 
All-Cause Unplanned Readmission After Psychiatric Discharge from an IPF 
(IPF Readmission) measure, and the Medication Continuation Following 
Inpatient Psychiatric Discharge (Medication Continuation) measure. We 
observed a weak negative correlation between FAPH and the IPF 
Readmission measure for both 7-day (-0.11) and 30-day (-0.18) measure 
rates. This negative correlation is expected because a higher score is 
indicative of better quality of care for the FAPH, while a lower score 
is indicative of better quality of care for the IPF readmission measure 
(that is, a lower rate of unplanned readmissions). High rates of 
follow-up after visits after discharge and low rates of unplanned 
readmissions both indicate good care coordination during the discharge 
process. We observed a weak positive correlation between the 7-day FAPH 
measure rate and the Medication Continuation measure (0.32), and 
between the 30-day FAPH measure rate and the Medication Continuation 
measure (0.42). This result is expected because for both the FAPH and 
the Medication Continuation measures higher scores are indicative of 
better-quality care. Follow-up visits after discharge and continuation 
of medication after discharge both indicate good care coordination 
during the discharge process. After reviewing these results and the 
proposed measure specifications, all 13 TEP members who were present 
agreed that the measure had face validity.\132\
---------------------------------------------------------------------------

    \132\ Face validity is defined as a subjective determination by 
experts that the measure appears to reflect quality of care, done 
through a systematic and transparent process, that explicitly 
addresses whether performance scores resulting from the measure as 
specified can be used to distinguish good from poor quality, with 
degree of consensus and any areas of disagreement provided/
discussed: https://www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/Docs/Evaluation_Guidance.aspx.

---------------------------------------------------------------------------

[[Page 19507]]

(3) Review by the Measure Applications Partnership and NQF
    Under section 1890A(a)(2) of the Act, this measure was included in 
a publicly available document: ``List of Measures Under Consideration 
for December 1, 2019,'' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Downloads/Measures-under-Consideration-List-for-2018.pdf.
    On January 15, 2020, the MAP Coordinating Committee rated the 
measure as ``Conditional Support for Rulemaking'' contingent upon NQF 
endorsement. We submitted the measure to the NQF for endorsement in the 
spring 2020 cycle. However, some members of the NQF Behavioral Health 
and Substance Use Standing Committee were concerned about the measure's 
exclusions for patients who died during the 30-day follow-up period or 
who were transferred. In addition, some members objected to combining 
persons with a diagnosis of SUD and those with a diagnosis for a mental 
health disorder into a single measure of follow-up care. Therefore, the 
NQF declined to endorse this measure. We noted that the exclusions for 
patients who died or who were admitted or transferred to an acute or 
non-acute inpatient facility during the 30-day follow up period align 
with the FUH measure currently in the IPFQR Program.
    Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to 
specify a measure for the IPFQR Program that is not endorsed by NQF. 
The exception to the requirement to specify an endorsed measure states 
that in the case of a specified area or medical topic determined 
appropriate by the Secretary for which a feasible and practical measure 
has not been endorsed by the entity with a contract under section 
1890(a) of the Act, the Secretary may specify a measure that is not so 
endorsed as long as due consideration is given to measures that have 
been endorsed or adopted by a consensus organization.
    The FAPH measure is not NQF endorsed. We have reviewed NQF-endorsed 
and other consensus-endorsed measures related to follow-up care and 
identified the FUH measure (NQF #0576) currently in the IPFQR Program 
and Continuity of Care after Inpatient or [bond]Residential Treatment 
for SUD (NQF #3453). We believe that the FAPH measure is an improvement 
over the current FUH measure and over the Continuity of Care after 
Inpatient or Residential Treatment of Substance Use Disorder because we 
believe that it is important to ensure appropriate access to follow-up 
treatment for the largest patient population possible and the FAPH 
measure applies to a larger patient population than either of the 
measures we considered. Therefore, we propose to adopt the FAPH measure 
described in this section for the FY 2024 payment determination and 
subsequent years.
c. Data Collection, Submission and Reporting
    FAPH uses Medicare FFS Part A and Part B claims that are received 
by Medicare for payment purposes. The measure links Medicare FFS claims 
submitted by IPFs and subsequent outpatient providers for Medicare FFS 
IPF discharges. Therefore, no additional data collection would be 
required from IPFs. For additional information on data submission for 
this measure, see section IV.J.2.b of this proposed rule. The 
performance period used to identify cases in the denominator is 12 
months. Data from this period and 30 days afterward are used to 
identify follow-up visits in the numerator. Consistent with other 
claims-based measures in the IPFQR Program, the performance period for 
this measure is July 1 through June 30. For example, for the FY 2024 
payment determination, the performance period will include discharges 
between July 1, 2021 and June 30, 2022.\133\
---------------------------------------------------------------------------

    \133\ If data availability or operational issues prevent use of 
this performance period, we would announce the updated performance 
period through subregulatory communications including announcement 
on a CMS website and/or on our applicable listservs.
---------------------------------------------------------------------------

    We invite public comment on our proposal to add a new measure, 
Follow-Up After Psychiatric Hospitalization, to the IPFQR Program, 
beginning with the FY 2024 payment determination and subsequent years.

F. Removal or Retention of IPFQR Program Measures

1. Background
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through 
38465), we adopted considerations for removing or retaining measures 
within the IPFQR Program and criteria for determining when a measure is 
``topped out.'' In the FY 2019 IPF PPS final rule (83 FR 38591 through 
38593), we adopted one additional measure removal factor. We are not 
proposing any changes to these removal factors, topped-out criteria, or 
retention factors and refer readers to the FY 2018 IPPS/LTCH PPS final 
rule (82 FR 38463 through 38465) and the FY 2019 IPF PPS final rule (83 
FR 38591 through 38593) for more information. We will continue to 
retain measures from each previous year's IPFQR Program measure set for 
subsequent years' measure sets, except when we specifically propose to 
remove or replace a measure. We will continue to use the notice-and-
comment rulemaking process to propose measures for removal or 
replacement, as we described upon adopting these factors in the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38464 through 38465).
    In our continual evaluation of the IPFQR Program measure set under 
our Meaningful Measures Framework and according to our measure removal 
and retention factors, we identified four measures that we believe are 
appropriate to propose removing from the IPFQR Program for the FY 2024 
payment determination and subsequent years. Our discussion of these 
measures follows.
2. Measures for Removal
a. Proposal To Remove Alcohol Use Brief Intervention Provided or 
Offered and Alcohol Use Brief Intervention (SUB-2/2a) Beginning With FY 
2024 Payment Determination
    We are proposing to remove the Alcohol Use Brief Intervention 
Provided or Offered and Alcohol Use Brief Intervention (SUB-2/2a) 
measure from the IPFQR Program beginning with the FY 2024 payment 
determination under our measure removal Factor 8, ``The costs 
associated with a measure outweigh the benefit of its continued use in 
the program.'' We adopted the Alcohol Use Brief Intervention Provided 
or Offered and Alcohol Use Brief Intervention (SUB-2/2a) measure in the 
FY 2016 IPF PPS final rule (80 FR 46699 through 46701) because we 
believe it is important to address the common comorbidity of alcohol 
use among IPF patients. This measure requires facilities to chart-
abstract measure data on a sample of IPF patient records, in accordance 
with established sampling policies (80 FR 46717 through 46719).
    We have previously stated our intent to move away from chart-
abstracted measures to reduce information collection burden in this and 
other CMS quality programs (78 FR 50808; 79 FR 50242; 80 FR 49693). 
When we adopted the SUB-2/2a measure to the IPFQR Program, the benefits 
of this measure were high because facility performance was not 
consistent. Therefore, the measure provided a means of distinguishing 
facility performance and incentivized facilities to improve rates of 
treatment for this common comorbidity. Between the FY 2018

[[Page 19508]]

payment determination (the first year that SUB-2/2a was included in the 
IPFQR Program measure set) and the FY 2019 payment determination, we 
saw substantial performance improvement on the SUB-2 measure (which is 
the portion of the SUB-2/2a measure that assess whether the facility 
provided or offered a brief intervention for alcohol use). However, for 
the FY 2019 and FY 2020 payment determinations, that improvement has 
leveled off to consistently high performance, as indicated in Table 2. 
These data further show that at this time there is little room for 
improvement in the SUB 2 measure, and that the quality improvement 
benefits from the measure have greatly diminished. We continue to 
believe that alcohol use is an important comorbidity to address in the 
IPF setting, and that brief interventions are a key component of 
addressing this comorbidity. However, based on these data, we believe 
that most IPFs routinely offer alcohol use brief interventions, and 
that IPFs will continue to offer these interventions to patients, 
regardless of whether the SUB-2/2a measure is in the IPFQR Program 
measure set, because it has become an embedded part of their clinical 
workflows.

          Table 2--Performance Analysis for Alcohol Use Brief Intervention Provided or Offered (SUB-2)
----------------------------------------------------------------------------------------------------------------
                                                                                                     Truncated
                                                                       75th            90th       coefficient of
              Year                     Mean           Median        percentile      percentile       variation
                                                                                                       (TCV)
----------------------------------------------------------------------------------------------------------------
2016 (2018 Payment                         66.96              77              96             100            0.49
 Determination).................
2017 (2019 Payment                         77.11              88              99             100            0.28
 Determination).................
2018 (2020 Payment                         79.49              91             100             100            0.25
 Determination).................
----------------------------------------------------------------------------------------------------------------

    While the measure does not meet our criteria for ``topped-out'' 
status because of the TCV higher than 0.1, we believe that this measure 
no longer meaningfully supports the program objectives of informing 
beneficiary choice and driving improvement in IPF interventions for 
alcohol use because it is no longer showing significant improvement in 
facility performance (that is, in providing or offering alcohol use 
brief interventions). Furthermore, as we stated in the FY 2019 IPF PPS 
final rule, costs are multi-faceted and include not only the burden 
associated with reporting, but also the costs associated with 
implementing and maintaining the program (83 FR 38592). For example, it 
may be costly for health care providers to maintain general 
administrative knowledge to report this measure. Additionally, CMS must 
expend resources in maintaining information collection systems, 
analyzing reported data, and providing public reporting of the 
collected information.
    Here, IPF information collection burden and related costs 
associated with reporting the SUB 2/2a measure to CMS are high because 
it is a chart-abstracted measure. Furthermore, CMS incurs costs 
associated with the program oversight of the measure for public 
display. As a result, we believe that the costs and burdens associated 
with this chart-abstracted measure outweigh the benefit of its 
continued use in the program.
    Therefore, we are proposing to remove the Alcohol Use Brief 
Intervention Provided or Offered and Alcohol Use Brief Intervention 
(SUB-2/2a) measure from the IPFQR Program beginning with the FY 2024 
payment determination. We welcome public comments on our proposal to 
remove the SUB-2/2a measure from the IPFQR Program.
b. Proposal To Remove Tobacco Use Brief Intervention Provided or 
Offered and Tobacco Use Brief Intervention (TOB-2/2a) Beginning With FY 
2024 Payment Determination
    We are proposing to remove the Tobacco Use Brief Intervention 
Provided or Offered and Tobacco Use Brief Intervention (TOB-2/2a) 
measure from the IPFQR Program beginning with the FY 2024 payment 
determination under our measure removal Factor 8, ``The costs 
associated with a measure outweigh the benefit of its continued use in 
the program.'' We adopted the Tobacco Use Brief Intervention Provided 
or Offered and Tobacco Use Brief Intervention (TOB-2/2a) measure in the 
FY 2015 IPF PPS final rule (79 FR 45971 through 45972) because we 
believe it is important to address the common comorbidity of tobacco 
use among IPF patients. Like SUB-2/2a described in the previous 
subsection, this measure requires facilities to chart-abstract measure 
data on a sample of IPF patient records, in accordance with established 
sampling policies (80 FR 46717 through 46719). When we introduced the 
TOB-2/2a measure to the IPFQR Program, the benefits of this measure 
were high, because facility performance was not consistent and 
therefore the measure provided a means of distinguishing facility 
performance and incentivized facilities to improve rates of treatment 
for this common comorbidity. Between the FY 2017 payment determination 
(the first year that TOB-2/2a was included in the IPFQR Program's 
measure set) and the FY 2019 payment determination we saw substantial 
performance improvement on TOB-2. However, between the FY 2019 and FY 
2020 payment determinations, that improvement has leveled off to 
consistently high performance, as indicated in Table 3. These data 
further show that currently there is little room for improvement in the 
TOB-2 measure, and that the quality improvement benefits from the 
measure have greatly diminished. We continue to believe that tobacco 
use is an important comorbidity to address in the IPF setting, and that 
brief interventions are a key component of addressing this comorbidity. 
However, based on these data, we believe that most IPFs routinely offer 
tobacco use brief interventions, and that IPFs will continue to offer 
these interventions to patients, regardless of whether the TOB-2/2a 
measure is in the IPFQR Program measure set, because it has become an 
embedded part of their clinical workflows.

[[Page 19509]]



          Table 3--Performance Analysis for Tobacco Use Brief Intervention Provided or Offered (TOB-2)
----------------------------------------------------------------------------------------------------------------
                                                                                                     Truncated
                                                                       75th            90th       coefficient of
              Year                     Mean           Median        percentile      percentile       variation
                                                                                                       (TCV)
----------------------------------------------------------------------------------------------------------------
2015 (2017 Payment                         63.83            71.5              91              99            0.49
 Determination).................
2016 (2018 Payment                         74.72              84              95             100            0.28
 Determination).................
2017 (2019 Payment                         79.04              88              97             100            0.22
 Determination).................
2018 (2020 Payment                         79.08              88              98             100            0.22
 Determination).................
----------------------------------------------------------------------------------------------------------------

    While the measure does not meet our criteria for ``topped-out'' 
status because of the TCV higher than 0.1, we believe that this measure 
no longer meaningfully supports the program objectives of informing 
beneficiary choice and driving improvement in IPF interventions for 
tobacco use because it is no longer showing significant improvement in 
facility performance (that is, in providing or offering tobacco use 
brief interventions). Furthermore, as we stated in the FY 2019 IPF PPS 
final rule, costs are multi-faceted and include not only the burden 
associated with reporting, but also the costs associated with 
implementing and maintaining the program (83 FR 38592). For example, it 
may be costly for health care providers to maintain general 
administrative knowledge to report this measure. Additionally, CMS must 
expend resources in maintaining information collection systems, 
analyzing reported data, and providing public reporting of the 
collected information. Here, IPF information collection burden and 
related costs associated with reporting this measure to CMS are high 
because the measure is a chart-abstracted measure. Furthermore, CMS 
incurs costs associated with the program oversight of the measure for 
public display. As a result, we believe that the costs and burdens 
associated with this chart-abstracted measure outweigh the benefit of 
its continued use in the program.
    Therefore, we are proposing to remove the Tobacco Use Brief 
Intervention Provided or Offered and Tobacco Use Brief Intervention 
(TOB-2/2a) measure from the IPFQR Program beginning with the FY 2024 
payment determination. We welcome public comments on our proposal to 
remove the TOB-2/2a measure from the IPFQR Program.
c. Proposal To Remove Timely Transmission of Transition Record 
(Discharges From an Inpatient Facility to Home/Self Care or Any Other 
Site of Care) Beginning With FY 2024 Payment Determination
    We are proposing to remove the Timely Transmission of Transition 
Record (Discharges from an Inpatient Facility to Home/Self Care or Any 
Other Site of Care) measure from the IPFQR Program beginning with the 
FY 2024 payment determination under our measure removal Factor 8, ``The 
costs associated with a measure outweigh the benefit of its continued 
use in the program.''
    We adopted the Timely Transmission of Transition Record (Discharges 
from an Inpatient Facility to Home/Self Care or Any Other Site of Care) 
measure in the FY 2016 IPF PPS final rule (80 FR 46706 through 46709) 
because more timely communication of vital information regarding the 
inpatient hospitalization results in better care, reduction of systemic 
medical errors, and improved patient outcomes. The Timely Transmission 
of Transition Record (Discharges from an Inpatient Facility to Home/
Self Care or Any Other Site of Care) measure builds on the Transition 
Record with Specified Elements Received by Discharged Patients 
(Discharges from an Inpatient Facility to Home/Self Care or Any Other 
Site of Care) measure, which requires facilities to provide a discharge 
record with 11 specified elements to patients at discharge.
    We continue to believe that the 11 elements required by the 
Transition Record with Specified Elements measure provide meaningful 
information about the quality of care provided by IPFs, and we are 
therefore not proposing to remove that measure from the IPFQR Program. 
However, we believe that the benefits of requiring facilities to 
transmit the discharge record with 11 specified elements to the next 
level care provided within 24 hours, as required by the Timely 
Transmission of Transition Record (Discharges from an Inpatient 
Facility to Home/Self Care or Any Other Site of Care) measure, have 
been reduced. Reporting this measure requires facilities to chart-
abstract measure data on a sample of IPF patient records, in accordance 
with established sampling policies (80 FR 46717 through 46719). On May 
1, 2020, we updated the Conditions of Participation (CoPs) for IPFs 
participating in the Medicare program in the Medicare and Medicaid 
Programs; Patient Protection and Affordable Care Act; Interoperability 
and Patient Access for Medicare Advantage Organization and Medicaid 
Managed Care Plans, State Medicaid Agencies, CHIP Agencies and CHIP 
Managed Care Entities, Issuers of Qualified Health Plans on the 
Federally Facilitated Exchanges, and Health Care Providers final rule 
(85 FR 25588).
    In the May 1, 2020 update to the CoPs, we adopted a requirement for 
psychiatric hospitals that possess EHR systems with the technical 
capacity to generate information for electronic patient event 
notifications to send electronic patient event notifications of a 
patient's admission, discharge, and/or transfer to another health care 
facility or to another community provider at the time of a patient's 
discharge or transfer. Because these updated CoP requirements overlap 
with, but are not the same as, the requirements for the Timely 
Transmission of Transition Record (Discharges from an Inpatient 
Facility to Home/Self Care or Any Other Site of Care) measure (which 
requires transmission of a discharge record with 11 specified elements 
to the next level care provider within 24 hours of the patient's 
discharge rather that requiring notification regarding the patient's 
inpatient stay to be transmitted at discharge), we believe that the 
adoption of these updated CoPs increases the costs of the Timely 
Transmission of Transition Record (Discharges from an Inpatient 
Facility to Home/Self Care or Any Other Site of Care) measure while 
decreasing its benefit. Specifically, we believe that the costs of this 
measure are increased because facilities to which the new CoPs apply 
(that is, facilities that possess EHR or other administrative systems 
with the technical capacity to generate information for electronic 
patient event notifications) could bear increased cost if they 
separately implement the patient event notifications meeting both the 
criteria for the updated CoPs and the capacity to share a transition 
record that meets the requirements of our measure. We

[[Page 19510]]

note that the updated CoPs do not include the level of detail regarding 
data to be transferred at discharge that our Timely Transmission of 
Transition Record (Discharges from an Inpatient Facility to Home/Self 
Care or Any Other Site of Care) measure requires. While the set of 
information in the CoP notification policy is a minimal set of 
information, we believe that it would continue to be appropriate for 
providers to transmit the transition record that they will continue to 
be providing to patients under our Transition Record Received by 
Discharged Patients (Discharges from an Inpatient Facility to Home/Self 
Care or Any Other Site of Care) measure.
    We believe the different requirements regarding both timeliness of 
notification and contents of notification could lead some providers to 
send two separate discharge notifications to meet the separate 
requirements. Further, we believe that the benefits of the measure are 
reduced because all facilities to which the new CoPs apply will be 
sending patient discharge information to the next level of care 
provider as required by the CoPs. Therefore, the benefits of this 
measure are reduced because it is less likely to ensure that these 
facilities provide patient discharge information to the next level care 
provider, and it is less likely to provide information to help 
consumers differentiate quality between facilities. While these updated 
CoPs do not directly address transmission of patient event 
notifications for facilities that do not possess EHR systems with 
patient event notification capabilities, such facilities should 
continue to transmit data using their existing infrastructure and 
timelines.
    Because we believe that the costs are now increased and the 
benefits are now reduced, we believe that the costs and burdens 
associated with this chart-abstracted measure outweigh the benefit of 
its continued use in the IPFQR Program.
    Therefore, we are proposing to remove the Timely Transmission of 
Transition Record (Discharges from an Inpatient Facility to Home/Self 
Care or Any Other Site of Care) measure from the IPFQR Program 
beginning with the FY 2024 payment determination. We welcome public 
comments on our proposal to remove the Timely Transmission of 
Transition Record measure from the IPFQR Program.
d. Proposal To Remove Follow-Up After Hospitalization for Mental 
Illness (FUH, NQF #0576) Beginning With FY 2024 Payment Determination
    If we finalize adoption of the Follow-Up After Psychiatric 
Hospitalization measure described in Section IV.E.3, we believe that 
our current measure removal Factor 3 would apply to the existing 
Follow-Up After Hospitalization for Mental Illness (FUH, NQF #0576) 
measure. Measure removal Factor 3 applies when a ``measure can be 
replaced by a more broadly applicable measure (across settings or 
populations) or a measure that is more proximal in time to desired 
patient outcomes for the particular topics.'' We adopted removal factor 
3 in the FY 2017 IPPS/LTCH PPS final rule (82 FR 38463 through 38465). 
The proposed FAPH measure expands the patient population from patients 
with mental illness to also include patients with primary SUD diagnoses 
while addressing the same important aspect of care transitions. Because 
this FAPH measure uses the same methodology to address the same element 
of care for a broader patient population than the FUH measure, we 
believe that it is more broadly applicable across populations.
    Therefore, we are proposing to remove the FUH measure under measure 
removal Factor 3 only if we finalize our proposal to adopt of the FAPH 
measure. We note that if we do not adopt the FAPH measure, we will 
retain the FUH measure because we believe this measure addresses an 
important clinical topic. We welcome public comments on our proposal to 
remove FUH if we adopt FAPH.

G. Summary of Previously Finalized and Newly Proposed Measures

1. Previously Finalized and Newly Proposed Measures for the FY 2023 
Payment Determination and Subsequent Years
    There are 14 previously finalized measures for the FY 2023 payment 
determination and subsequent years. In this proposed rule, we are 
proposing to adopt one measure for the FY 2023 payment determination 
and subsequent years. The 15 measures which would be in the program if 
this proposal is finalized are shown in Table 4.

Table 4--IPFQR Program Measure Set for the FY 2023 Payment Determination
    and Subsequent Years if Measure Adoption Is Finalized as Proposed
------------------------------------------------------------------------
       NQF #               Measure ID                  Measure
------------------------------------------------------------------------
0640...............  HBIPS-2...............  Hours of Physical Restraint
                                              Use.
0641...............  HBIPS-3...............  Hours of Seclusion Use.
0560...............  HBIPS-5...............  Patients Discharged on
                                              Multiple Antipsychotic
                                              Medications with
                                              Appropriate Justification.
0576...............  FUH...................  Follow-Up After
                                              Hospitalization for Mental
                                              Illness.
N/A *..............  SUB-2 and SUB-2a......  Alcohol Use Brief
                                              Intervention Provided or
                                              Offered and SUB-2a Alcohol
                                              Use Brief Intervention.
N/A *..............  SUB-3 and SUB-3a......  Alcohol and Other Drug Use
                                              Disorder Treatment
                                              Provided or Offered at
                                              Discharge and SUB-3a
                                              Alcohol and Other Drug Use
                                              Disorder Treatment at
                                              Discharge.
N/A *..............  TOB-2 and TOB-2a......  Tobacco Use Treatment
                                              Provided or Offered and
                                              TOB-2a Tobacco Use
                                              Treatment.
N/A *..............  TOB-3 and TOB-3a......  Tobacco Use Treatment
                                              Provided or Offered at
                                              Discharge and TOB-3a
                                              Tobacco Use Treatment at
                                              Discharge.
1659...............  IMM-2.................  Influenza Immunization.
N/A *..............  N/A...................  Transition Record with
                                              Specified Elements
                                              Received by Discharged
                                              Patients (Discharges from
                                              an Inpatient Facility to
                                              Home/Self Care or Any
                                              Other Site of Care).
N/A *..............  N/A...................  Timely Transmission of
                                              Transition Record
                                              (Discharges from an
                                              Inpatient Facility to Home/
                                              Self Care or any Other
                                              Site of Care).
N/A................  N/A...................  Screening for Metabolic
                                              Disorders.
2860...............  N/A...................  Thirty-Day All-Cause
                                              Unplanned Readmission
                                              Following Psychiatric
                                              Hospitalization in an
                                              Inpatient Psychiatric
                                              Facility.
3205...............  Med Cont..............  Medication Continuation
                                              Following Inpatient
                                              Psychiatric Discharge.

[[Page 19511]]

 
TBD................  COVID HCP.............  COVID-19 Healthcare
                                              Personnel (HCP)
                                              Vaccination Measure.
------------------------------------------------------------------------
* Measure is no longer endorsed by the NQF but was endorsed at time of
  adoption. Section 1886(s)(4)(D)(ii) of the Act authorizes the
  Secretary to specify a measure that is not endorsed by the NQF as long
  as due consideration is given to measures that have been endorsed or
  adopted by a consensus organization identified by the Secretary. We
  attempted to find available measures for each of these clinical topics
  that have been endorsed or adopted by a consensus organization and
  found no other feasible and practical measures on the topics for the
  IPF setting.

2. Previously Finalized and Newly Proposed Measures for the FY 2024 
Payment Determination and Subsequent Years
    There are 14 previously finalized measures for the FY 2024 payment 
determination and subsequent years. In this proposed rule, we are 
proposing to adopt one measure for the FY 2023 payment determination 
and subsequent years. Additionally, we are proposing to remove three 
measures and replace one measure for the FY 2024 payment determination 
and subsequent years. The 12 measures which would be in the program for 
FY 2024 payment determination and subsequent years if these proposals 
are finalized are shown in Table 5.

Table 5--IPFQR Program Measure Set for the FY 2024 Payment Determination
and Subsequent Years if Adoptions and Removals Are Finalized as Proposed
------------------------------------------------------------------------
       NQF #               Measure ID                  Measure
------------------------------------------------------------------------
0640...............  HBIPS-2...............  Hours of Physical Restraint
                                              Use.
0641...............  HBIPS-3...............  Hours of Seclusion Use.
0560...............  HBIPS-5...............  Patients Discharged on
                                              Multiple Antipsychotic
                                              Medications with
                                              Appropriate Justification.
N/A................  FAPH..................  Follow-Up After Psychiatric
                                              Hospitalization.
1659...............  IMM-2.................  Influenza Immunization.
N/A *..............  SUB-3 and SUB-3a......  Alcohol and Other Drug Use
                                              Disorder Treatment
                                              Provided or Offered at
                                              Discharge and SUB-3a
                                              Alcohol and Other Drug Use
                                              Disorder Treatment at
                                              Discharge.
N/A *..............  TOB-3 and TOB-3a......  Tobacco Use Treatment
                                              Provided or Offered at
                                              Discharge and TOB-3a
                                              Tobacco Use Treatment at
                                              Discharge.
N/A *..............  N/A...................  Transition Record with
                                              Specified Elements
                                              Received by Discharged
                                              Patients (Discharges from
                                              an Inpatient Facility to
                                              Home/Self Care or Any
                                              Other Site of Care).
N/A................  N/A...................  Screening for Metabolic
                                              Disorders.
2860...............  N/A...................  Thirty-Day All-Cause
                                              Unplanned Readmission
                                              Following Psychiatric
                                              Hospitalization in an
                                              Inpatient Psychiatric
                                              Facility.
3205...............  Med Cont..............  Medication Continuation
                                              Following Inpatient
                                              Psychiatric Discharge.
TBD................  COVID HCP.............  COVID-19 Healthcare
                                              Personnel (HCP)
                                              Vaccination Measure.
------------------------------------------------------------------------
* Measure is no longer endorsed by the NQF but was endorsed at time of
  adoption. Section 1886(s)(4)(D)(ii) of the Act authorizes the
  Secretary to specify a measure that is not endorsed by the NQF as long
  as due consideration is given to measures that have been endorsed or
  adopted by a consensus organization identified by the Secretary. We
  attempted to find available measures for each of these clinical topics
  that have been endorsed or adopted by a consensus organization and
  found no other feasible and practical measures on the topics for the
  IPF setting.

H. Considerations for Future Measure Topics

    As we have previously indicated, we seek to develop a comprehensive 
set of quality measures to be available for widespread use for informed 
decision-making and quality improvement in the IPF setting (79 FR 45974 
through 45975). Therefore, through future rulemaking, we intend to 
propose new measures for development or adoption that will help further 
our goals of achieving better healthcare and improved health for 
individuals who obtain inpatient psychiatric services through the 
widespread dissemination and use of quality information. In 2017, we 
introduced the Meaningful Measures Framework as a tool to foster 
operational efficiencies and reduce costs including collection and 
reporting burden while producing quality measurement that is more 
focused on meaningful outcomes (83 FR 38591). As we continue to evolve 
the Meaningful Measures Framework, we have stated that we intend to 
better address health care priorities and gaps, emphasize digital 
quality measurement, and promote patient perspectives.\134\ As we work 
to align the IPFQR Program's measure set with these priorities, we have 
identified the following areas that we believe are important to 
stakeholders, but which are not covered in the current IPFQR Program 
measure set: Patient Experience of Care, Functional Outcomes 
Measurement, and digital measures. As described in the following 
subsections, we are seeking public comment on each of these topics and 
other future measure considerations which stakeholders believe are 
important.
---------------------------------------------------------------------------

    \134\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

1. Patient Experience of Care Data Collection Instrument
    When we finalized removal of the Assessment of Patient Experience 
of Care attestation measure in the FY 2019 IPF PPS final rule (83 FR 
38596) we stated that we believed we had collected sufficient 
information to inform development of a patient experience of care 
measure that would capture data on the results of such a survey. In the 
FY 2020 IPF PPS proposed rule (84 FR 16986 through 16987), we solicited 
input on how providers had implemented the Hospital Consumer Assessment 
of Healthcare Providers and Systems (HCAHPS) survey in their

[[Page 19512]]

facilities. We also sought public comment on other potential surveys 
that commenters believed would be appropriate to adopt for the IPFQR 
Program. We received many comments on this subject, and many of these 
comments expressed that there is not one survey used predominantly 
across IPFs (84 FR 38467). Additional commenters expressed concerns 
that the HCAHPS survey may not be appropriate for the IPF setting 
because it does not include some of the unique aspects of inpatient 
psychiatric care including, group therapy, non-physician providers, and 
involuntary admissions. While we did not solicit public comment on this 
issue in the FY 2021 IPF PPS proposed rule, we received many comments 
addressing this issue (85 FR 47043). We continue to seek to identify a 
minimally burdensome patient experience of care instrument that would 
be appropriate for the IPF setting. Therefore, we are seeking public 
comment on instruments currently in use in the IPF setting, input on 
whether the HCAHPS survey may be appropriate for this setting, and 
information on how facilities that currently use the HCAHPS survey have 
addressed challenges with using this survey within this setting (that 
is, concerns regarding unique aspects of inpatient psychiatric care).
2. Functional Outcomes Instrument for Use in a Patient Reported 
Outcomes Measure
    When we introduced the Meaningful Measures Framework, we stated 
that we wanted to focus on meaningful outcomes (83 FR 38591). As we 
have assessed the IPFQR Program measure set against the Meaningful 
Measures Framework, we have identified functional outcomes as a 
potential gap area in the IPFQR Program's measure set. Therefore, we 
are evaluating whether a patient reported outcomes measure that 
assesses functional outcomes, such as global functioning, interpersonal 
problems, psychotic symptoms, alcohol or drug use, emotional lability, 
and self-harm, would be an appropriate measure to include in the IPFQR 
program measure set. If we were to develop such a measure, we would 
develop a measure that compares a patient's responses to a standardized 
functional outcomes assessment instrument at admission with the 
patient's results on the same assessment instrument at discharge. We 
are seeking public comment on the value of such a measure in the IPFQR 
program measure set, what would be an appropriate functional outcome 
assessment instrument to use in the potential development of such a 
measure, and any additional topics or concepts stakeholders believe 
would be appropriate for patient reported outcomes measures.
3. Measures for Electronic Data Reporting
    As we seek to improve digital measurement across our quality 
reporting and value-based payment programs, we are considering measures 
both within and appropriate to adopt for the IPFQR Program measure set 
that would be appropriate for digital data collection. In our 
assessment of the current measure set, we identified the Transition 
Record with Specified Elements Received by Discharged Patients 
(Discharges from an Inpatient Facility to Home/Self Care or Any Other 
Site of Care) measure as a potential option for digital data 
collection. We are seeking stakeholder input on the current data 
collection burden associated with this measure, concerns regarding 
potential electronic specification and data collection for this 
measure, and other measures that may be appropriate for electronic data 
collection, either those currently in the IPFQR Program measure set, or 
those that we could adopt in the future.

I. Public Display and Review Requirements

    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53653 through 53654), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 
through 50898), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 
through 57249) for discussion of our previously finalized public 
display and review requirements. In this proposed rule, we are not 
proposing any changes to these requirements.

J. Form, Manner, and Timing of Quality Data Submission for the FY 2022 
Payment Determination and Subsequent Years

1. Procedural Requirements for the FY 2023 Payment Determination and 
Subsequent Years
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53654 through 53655), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50898 
through 50899), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 
through 38472) for our previously finalized procedural requirements. In 
this proposed rule, we are proposing to use the term ``QualityNet 
security official'' instead of ``QualityNet system administrator,'' 
proposing to revise Sec.  412.434(b)(3) by replacing the term 
``QualityNet system administrator'' with the term ``QualityNet security 
official,'' and clarifying our policy under the previously finalized 
requirement that hospitals ``[i]dentify a QualityNet Administrator who 
follows the registration process located on the QualityNet website'' 
(77 FR 53654).
a. Proposal To Update Reference to QualityNet System Administrator and 
to No Longer Require Active Account To Qualify for Payment
    The previously finalized QualityNet security administrator 
requirements, including those for setting up a QualityNet account and 
the associated timelines, are described in the FY 2013 IPPS/LTCH final 
rule (77 FR 53654).
    In this proposed rule, we propose to use the term ``QualityNet 
security official'' instead of ``QualityNet system administrator'' to 
denote the exercise of authority invested in the role and align with 
the Hospital Outpatient Quality Reporting Program and other programs. 
The term ``security official'' would refer to ``the individual(s)'' who 
have responsibilities for security and account management requirements 
for a facility's QualityNet account. To clarify, this proposed update 
in terminology would not change the individual's responsibilities or 
add burden.
    We invite public comment on our proposal to replace the term 
``QualityNet system administrator'' with ``QualityNet security 
official.''
    Additionally, we are proposing to no longer require IPFs to 
maintain an active QualityNet security official account to qualify for 
payment. As we reviewed the requirements for the security official role 
and the basic user \135\ role to identify the most appropriate language 
to describe the distinguishing authority invested in the security 
official role, we recognized that the QualityNet security official is 
not required for submitting data--a basic user can serve in this role--
but remains necessary to set up QualityNet basic user accounts and for 
security purposes. Therefore, consistent with our proposal to adopt the 
security official term to differentiate the unique security authority 
and responsibilities of the role from the data submission 
responsibilities of the basic user role, we would continue to require a 
QualityNet basic user account to meet

[[Page 19513]]

IPFQR Program requirements, including data submission and 
administrative requirements, while recommending, but not requiring, 
that hospitals maintain an active QualityNet security official account.
---------------------------------------------------------------------------

    \135\ We also noted that a basic user is a QualityNet user who 
(1) does not have the registration access described for security 
officials, (2) has the appropriate data entry roles and permissions 
for program participation, (3) can submit and review measures and 
non-measure data, (4) signs and submits the Data Accuracy 
Completeness Acknowledgement (DACA) form, and (5) refreshes their 
QualityNet account password every 180 days to ensure that the 
facility's IPFQR Program Notice of Participation status is 
``Participating.''
---------------------------------------------------------------------------

    We welcome public comments on our proposal to no longer require 
facilities to maintain an active QualityNet security official account 
to qualify for payment.
b. Proposal To Update Reference to QualityNet Administrator in Code of 
Federal Regulations
    In this proposed rule, we propose to revise our regulation at Sec.  
412.434(b)(3) by replacing ``QualityNet system administrator'' with 
``QualityNet security official.'' The term ``QualityNet security 
official'' refers to the individual(s) who have responsibilities for 
security and account management requirements for a hospital's 
QualityNet account. To clarify, this proposed update in terminology 
would not change the individual's responsibilities or add burden. If 
finalized, the revised paragraph (b)(3) would read: ``Contact 
information for the inpatient psychiatric facility's chief executive 
officer and QualityNet security official, including each individual's 
name, email address, telephone number, and physical mailing address.''
    We invite public comment on our proposal to replace the term 
``QualityNet system administrator'' with ``QualityNet security 
official'' at Sec.  412.434(b)(3).
2. Data Submission Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53655 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50899 
through 50900), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472 
through 38473) for our previously finalized data submission 
requirements. In this proposed rule, we are proposing to adopt one 
measure for the FY 2023 payment determination and subsequent years and 
one measure for the FY 2024 payment determination and subsequent years. 
Data submission requirements for each of these measures are described 
in the following subsections. Additionally, we are proposing to adopt 
patient level data submission for certain chart abstracted measures 
beginning with data submitted for the FY 2023 payment determination and 
subsequent years; details of this proposal are in subsection c. of this 
section.
a. Data Submission Requirements for FY 2023 Payment Determination and 
Subsequent Years
    The measure we are proposing for FY 2023 payment determination and 
subsequent years (the COVID-19 HCP--Vaccination measure) requires 
facilities to report data on the number of HCP who have received 
completed vaccination course of a COVID-19 vaccine through the CDC's 
National Healthcare Safety Network (NHSN). Specific details on data 
submission for this measure can be found in the CDC's Overview of the 
Healthcare Safety Component, available at https://www.cdc.gov/nhsn/PDFs/slides/NHSN-Overview-HPS_Aug2012.pdf. For each CMS Certification 
Number (CCN), a percentage of the HCP who received a completed vaccine 
course of the COVID-19 vaccination will be calculated and publicly 
reported, so that the public will know what percentage of the HCP have 
been vaccinated in each IPF.
    For the COVID-19 HCP Vaccination measure, we are proposing that 
facilities would report the numerator and denominator for the COVID-19 
HCP vaccination measure to the NHSN for at least one week each month, 
beginning in October 2021 for the October 1, 2021 through December 31, 
2021 reporting period affecting the FY 2023 payment determination. If 
facilities report more than one week of data in a month, the most 
recent week's data would be used to calculate the measure. Each 
quarter, the CDC would calculate a single quarterly result of COVID-19 
vaccination coverage which would summarize the data submitted by IPFs 
for each of the three weeks of data submitted over the three month 
period. If finalized, CMS would publicly report the CDC's quarterly 
summary of COVID-19 vaccination coverage for IPFs.
    We invite public comment on our proposal to require facilities to 
report the COVID-19 HCP vaccination measure.
b. Data Submission Requirements for FY 2024 Payment Determination and 
Subsequent Years
    Because the Follow-Up After Psychiatric Hospitalization (FAPH) 
measure would be calculated by CMS using Medicare Fee-for-Service 
claims, there will be no additional data submission requirements for 
the FY 2024 payment determination and subsequent years. Therefore, we 
are not proposing any changes to our data submission policies 
associated with the proposal to adopt this measure.
c. Proposal To Adopt Patient-Level Reporting for Certain Chart-
Abstracted Measures Beginning With FY 2024 Payment Determination and 
Subsequent Years
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 
53657), we finalized that IPFs participating in the IPFQR Program must 
submit data to the Web-Based Measures Tool found in the Inpatient 
Psychiatric Facility section of the QualityNet website's secure portal 
between July 1 and August 15 of each year. We noted that the data input 
forms within the Quality Net secure portal require submission of 
aggregate data for each separate quarter. In the FY 2014 IPPS/LTCH PPS 
final rule, we clarified our intent to require that IPFs submit 
aggregate data on measures on an annual basis via the Web-Based 
Measures Tool found in the IPF section of the Quality Net website's 
secure portal and that the forms available require aggregate data for 
each separate quarter (78 FR 50899 through 50900). In the FY 2016 IPF 
PPS final rule (80 FR 46716), we updated our data submission 
requirements to require facilities to report data for chart-abstracted 
measures to the Web-Based Measures Tool on an aggregate basis by year, 
rather than by quarter. Additionally, we discontinued the requirement 
for reporting by age group. We updated these policies in the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38472 through 38473) to change the 
specification of the submission deadline from exact dates to a 45-day 
submission period beginning at least 30 days following the end of the 
data collection period.
    In the FY 2019 IPF PPS final rule (83 FR 38607), we observed that 
reporting aggregate measure data increases the possibility of human 
error, such as making typographical errors while entering data, which 
cannot be detected by CMS or by data submission systems. We noted that 
unlike patient-level data reporting, aggregate measure data reporting 
does not allow for data accuracy validation, thereby lowering the 
ability to detect error. We stated that we were considering requiring 
patient-level data reporting (data regarding each patient included in a 
measure and whether the patient was included in each numerator and 
denominator of the measure) of IPFQR measure data in the future. We 
sought public comment on including patient-level data collection in the 
IPFQR program. Several commenters expressed support for patient-level 
data collection, observing that it provides greater confidence in the 
data's validity and reliability. Other

[[Page 19514]]

commenters recommended that CMS use a system that has already been 
tested and used for IPF data reporting or work with IPFs in selecting a 
system so that any selected system would avoid additional burden.
    We believe that patient-level data reporting would improve the 
accuracy of the submitted and publicly reported data without increasing 
burden. As we considered the current IPFQR measure set, we determined 
that patient-level reporting of the Hours of Physical Restraint Use 
(HBIPS-2, NQF #0640) measure and Hours of Seclusion Use (HBIPS-2, NQF 
#0641) measure would be appropriate for the numerators of these 
measures only, because these measures are calculated with a denominator 
of 1,000 hours rather than a denominator of patients who meet specific 
criteria for inclusion in the measure. Therefore, we are proposing to 
require reporting patient-level information for the numerators of these 
measures only. For the remainder of the chart-abstracted measures in 
the IPFQR Program we are proposing to require patient-level reporting 
of the both the numerator and the denominator. Table 6 lists the 
proposed FY 2023 IPFQR measure set categorized by whether we would 
require patient-level data submission through the QualityNet secure 
portal.

  Table 6--Patient-Level Data Submission Requirements for FY 2024 IPFQR
                           Program Measure Set
------------------------------------------------------------------------
                                                          Patient-level
    NQF #         Measure ID            Measure          data submission
------------------------------------------------------------------------
0640.........  HBIPS-2.........  Hours of Physical      Yes, numerator
                                  Restraint Use.         only.
0641.........  HBIPS-3.........  Hours of Seclusion     Yes, numerator
                                  Use.                   only.
0560.........  HBIPS-5.........  Patients Discharged    Yes.
                                  on Multiple
                                  Antipsychotic
                                  Medications with
                                  Appropriate
                                  Justification.
0576.........  FUH.............  Follow-Up After        No (claims-
                                  Hospitalization for    based).
                                  Mental Illness.
N/A *........  SUB-2 and SUB-2a  Alcohol Use Brief      Yes.
                                  Intervention
                                  Provided or Offered
                                  and SUB-2a Alcohol
                                  Use Brief
                                  Intervention.
N/A *........  SUB-3 and SUB-3a  Alcohol and Other      Yes.
                                  Drug Use Disorder
                                  Treatment Provided
                                  or Offered at
                                  Discharge and SUB-3a
                                  Alcohol and Other
                                  Drug Use Disorder
                                  Treatment at
                                  Discharge.
N/A *........  TOB-2 and TOB-2a  Tobacco Use Treatment  Yes.
                                  Provided or Offered
                                  and TOB-2a Tobacco
                                  Use Treatment.
N/A *........  TOB-3 and TOB-3a  Tobacco Use Treatment  Yes.
                                  Provided or Offered
                                  at Discharge and TOB-
                                  3a Tobacco Use
                                  Treatment at
                                  Discharge.
1659.........  IMM-2...........  Influenza              Yes.
                                  Immunization.
N/A *........  N/A.............  Transition Record      Yes.
                                  with Specified
                                  Elements Received by
                                  Discharged Patients
                                  (Discharges from an
                                  Inpatient Facility
                                  to Home/Self Care or
                                  Any Other Site of
                                  Care).
N/A *........  N/A.............  Timely Transmission    Yes.
                                  of Transition Record
                                  (Discharges from an
                                  Inpatient Facility
                                  to Home/Self Care or
                                  any Other Site of
                                  Care).
N/A..........  N/A.............  Screening for          Yes.
                                  Metabolic Disorders.
2860.........  N/A.............  Thirty-Day All-Cause   No (claims-
                                  Unplanned              based).
                                  Readmission
                                  Following
                                  Psychiatric
                                  Hospitalization in
                                  an Inpatient
                                  Psychiatric Facility.
3205.........  Med Cont........  Medication             No (claims-
                                  Continuation           based).
                                  Following Inpatient
                                  Psychiatric
                                  Discharge.
TBD..........  COVID HCP.......  COVID-19 Healthcare    No (calculated
                                  Personnel (HCP)        for HCP).
                                  Vaccination Measure.
------------------------------------------------------------------------
* Measure is no longer endorsed by the NQF but was endorsed at time of
  adoption. Section 1886(s)(4)(D)(ii) of the Act authorizes the
  Secretary to specify a measure that is not endorsed by the NQF as long
  as due consideration is given to measures that have been endorsed or
  adopted by a consensus organization identified by the Secretary. We
  attempted to find available measures for each of these clinical topics
  that have been endorsed or adopted by a consensus organization and
  found no other feasible and practical measures on the topics for the
  IPF setting.

    Submission of aggregate data requires facilities to abstract 
patient-level data, then calculate measure performance prior to 
submitting data through the QualityNet website's secure portal. For 
measures for which we would require patient-level data submission, we 
would allow facilities to submit data using a tool such as the CMS 
Abstraction & Reporting Tool (CART). This is the tool we use in our 
other quality reporting and value-based purchasing programs, and 
therefore, we believe that many facilities may already have familiarity 
with using this tool to abstract and report data. Additionally, the 
tool has been specifically designed to facilitate data reporting and 
minimize provider burden.
    We note that under aggregate data reporting, facilities submit 
aggregate numerators and aggregate denominators for all measures to CMS 
in the Hospital Quality Reporting (HQR) system. These aggregate 
numerators and denominators are generally calculated by manually 
abstracting the medical record of each included patient using the 
algorithm, a paper tool, or a vendor abstraction tool. After each 
required medical record has been abstracted, the numerator and 
denominator results are added up and submitted as aggregate values in 
the HQR system. Under our patient level data reporting proposal, 
facilities would still manually abstract the medical record using 
either a vendor abstraction tool or an abstraction tool provided by 
CMS. The vendor abstraction tool or the CMS tool would then produce an 
individual XML file for each of the cases abstracted. Instead of 
submitting the aggregate data, the facility will log into HQR and 
upload batches of XML files that contain patient level data for each 
measure with data from all patients whose records were abstracted, and 
CMS would calculate the aggregate numerators, aggregate denominators, 
and measure rates from those XML file submissions. Because facilities 
must abstract patient-level data as one step in calculating measure 
results, we do not believe that requiring patient-level data submission 
will increase provider costs or burden associated with measure 
submission.
    Because we believe that patient-level data will improve the data 
accuracy without increasing provider burden, we are now proposing to 
adopt patient-level data reporting for numerators only for the Hours of 
Physical Restraint Use

[[Page 19515]]

(HBIPS-2, NQF #0640) and the Hours of Seclusion Use (HBIPS-3, NQF 
#0631) for numerators and denominators for the following 9 chart-
abstracted IPFQR Program measures as detailed in Table 6: Patients 
Discharged on Multiple Antipsychotic Medications with Appropriate 
Justification (NQF #0560); Alcohol Use Brief Intervention Provided or 
Offered and SUB-2a Alcohol Use Brief Intervention; Alcohol and Other 
Drug Use Disorder Treatment Provided or Offered at Discharge and SUB-3a 
Alcohol and Other Drug Use Disorder Treatment at Discharge, Tobacco Use 
Treatment Provided or Offered and TOB-2a Tobacco Use Treatment, Tobacco 
Use Treatment Provided or Offered at Discharge and TOB-3a Tobacco Use 
Treatment at Discharge, Influenza Immunization (NQF #1659), Transition 
Record with Specified Elements Received by Discharged Patients 
(discharges from an Inpatient Facility to Home/Self Care or Any Other 
Site of Care), Timely Transmission of Transition Record (Discharges 
from an Inpatient Facility to Home/Self Care or any Other Site of 
Care), and Screening for Metabolic Disorders.
    We believe that it is appropriate to transition to patient-level 
reporting incrementally. This would allow facilities to become familiar 
with the data submission systems and to provide feedback on any 
challenges they face in reporting data to us. Therefore, we are 
proposing to allow voluntary patient-level data submission for the FY 
2023 payment determination (that is, data submitted during CY 2022). We 
note that because participation in patient-level reporting for these 
chart-abstracted measures would be voluntary for this one-year period, 
facilities would be able to choose whether to submit measure data in 
aggregate or at the patient level, and would not face a payment 
reduction as long as they submit all measure data either at the patient 
level or in aggregate for each measure for which reporting is required, 
and as long as they met all other IPFQR Program requirements. 
Therefore, we are proposing to allow voluntary patient-level reporting 
prior to requiring such data submission for one year prior to the FY 
2024 payment determination. If we transition to patient-level 
reporting, we will ensure that facilities have guidance available 
through our standard communications channels (that is, listserv 
announcements, educational webinars, and training material on the 
QualityNet website).
    We are also proposing to require patient-level data submission for 
these chart-abstracted measures for the FY 2024 payment determination 
(that is, data submitted during CY 2023) and subsequent years.
    We welcome comment on our proposals to allow voluntary patient-
level data reporting for these chart-abstracted measures for the FY 
2023 payment determination and then to require patient-level data 
reporting for the FY 2024 payment determination and subsequent years.
3. Considerations for Data Validation Pilot
    As discussed in section IV.J.4 and in the FY 2019 IPF PPS final 
rule, we are concerned about the limitations of aggregate data 
submission (83 FR 28607). One such concern was that the ability to 
detect error is lower for aggregate measure data reporting than for 
patient-level data reporting (that is, data regarding each patient 
included in a measure and whether the patient was included in the 
numerator and denominator of the measure). We note that if we finalize 
our proposal to adopt patient-level data requirements, we would be able 
to adopt a data validation policy for the IPFQR Program in the future. 
We believe that it would be appropriate to develop such a policy 
incrementally through adoption of a data validation pilot prior to 
national implementation of data validation within the IPFQR Program. We 
seek public input on elements of a potential data validation pilot, for 
example, the number of measures to validate, number of participating 
facilities, whether the pilot should be mandatory or voluntary, 
potential thresholds for determining measure accuracy, or any other 
policies that commenters believe would be appropriate to include in a 
data validation pilot or eventual data validation policy.
4. Reporting Requirements for the FY 2022 Payment Determination and 
Subsequent Years
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53656 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50900 
through 50901), and the FY 2015 IPF PPS final rule (79 FR 45976 through 
45977) for our previously finalized reporting requirements. In this 
proposed rule, we are not proposing any changes to these policies.
5. Quality Measure Sampling Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53657 through 53658), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901 
through 50902), the FY 2016 IPF PPS final rule (80 FR 46717 through 
46719), and the FY 2019 IPF PPS final rule (83 FR 38607 through 38608) 
for discussions of our previously finalized sampling policies. We note 
that neither the measure we are proposing to remove (FUH-NQF #0576) nor 
the measure we are proposing to adopt (FAPH) if we remove the FUH-NQF 
#0576 are affected by our sampling policies because these are both 
calculated by CMS using Medicare Fee-for-Service claims and, therefore, 
apply to all Medicare patients in the denominator. Furthermore, the 
denominator of the COVID-19 Healthcare Personnel Vaccination measure we 
are proposing to adopt in this proposed rule is all healthcare 
personnel, and therefore, this measure is not eligible for sampling. In 
this proposed rule, we are not proposing any changes to our previously 
finalized sampling policies.
6. Non-Measure Data Collection
    We refer readers to the FY 2015 IPF PPS final rule (79 FR 45973), 
the FY 2016 IPF PPS final rule (80 FR 46717), and the FY 2019 IPF PPS 
final rule (83 FR 38608) for our previously finalized non-measure data 
collection policies. In this proposed rule, we are not proposing any 
changes to these policies.
7. Data Accuracy and Completeness Acknowledgement (DACA) Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53658) for our previously finalized DACA requirements. In this proposed 
rule, we are not proposing any changes to these policies.

K. Reconsideration and Appeals Procedures

    We refer readers to 42 CFR 412.434 for the IPFQR Program's 
reconsideration and appeals procedures. In this proposed rule, we are 
not proposing any changes to these policies.

L. Extraordinary Circumstances Exceptions (ECE) Policy

    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53659 through 53660), the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50903), the FY 2015 IPF PPS final rule (79 FR 45978), and the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38473 through 38474) for our previously 
finalized ECE policies. In this proposed rule, we are not proposing any 
changes to these policies.

V. Collection of Information Requirements

    Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et 
seq.), we are required to provide 60-day notice

[[Page 19516]]

in the Federal Register and solicit public comment before a 
``collection of information'' (as defined under 5 CFR 1320.3(c) of the 
PRA's implementing regulations) requirement is submitted to the Office 
of Management and Budget (OMB) for review and approval. In order to 
fairly evaluate whether an information collection should be approved by 
OMB, section 3506(c)(2)(A) of the PRA requires that we solicit comment 
on the following issues:
     The need for the information collection and its usefulness 
in carrying out the proper functions of our agency.
     The accuracy of our estimate of the information collection 
burden.
     The quality, utility, and clarity of the information to be 
collected.
     Recommendations to minimize the information collection 
burden on the affected public, including automated collection 
techniques.
    We are soliciting public comment on each of the section 
3506(c)(2)(A)--required issues for the following information collection 
requirements (ICRs).

A. Proposed ICRs for the (IPFQR) Program

    The following proposed requirement and burden changes will be 
submitted to OMB for approval under control number 0938-1171 (CMS-
10432).
1. Wage Estimates
    In the FY 2020 IPF PPS final rule (84 FR 38468), which was the most 
recent rule in which we adopted updates to the IPFQR Program, we 
estimated that reporting measures for the IPFQR Program could be 
accomplished by a Medical Records and Health Information Technician 
(BLS Occupation Code: 29-2071) with a median hourly wage of $18.83/hr. 
(May 2017). Since then, BLS (the Bureau of Labor Statistics) has 
revised their wage data (May 2019) to $20.50/hr.\136\ In response, we 
are proposing to adjust our cost estimates using the updated median 
wage rate figure of $20.50/hr., an increase of $1.67/hr.
---------------------------------------------------------------------------

    \136\ https://www.bls.gov/oes/current/oes292098.htm (Accessed on 
March 30, 2021).
---------------------------------------------------------------------------

    Under OMB Circular A-76, in calculating direct labor, agencies 
should not only include salaries and wages, but also ``other 
entitlements'' such as fringe benefits and overhead.\137\ Consistent 
with our past approach, we continue to calculate the cost of fringe 
benefits and overhead at 100 percent of the median hourly wage (81 FR 
57266). This is necessarily a rough adjustment, both because fringe 
benefits and overhead costs vary significantly from employer to 
employer, and methods of estimating these costs vary widely from study 
to study. Therefore, using these assumptions, we estimate an hourly 
labor cost increase from $37.66/hr ($18.83/hr base salary + $18.83/hr 
fringe benefits and overhead) to $41.00/hr ($20.50/hr base salary + 
$20.50/hr fringe benefits and overhead). Table 7 presents these 
assumptions.
---------------------------------------------------------------------------

    \137\ https://www.whitehouse.gov/omb/circulars_a076_a76_incl_tech_correction.

                                 Table 7--Wage Assumptions for the IPFQR Program
----------------------------------------------------------------------------------------------------------------
                                                                                Fringe benefits
              Occupation title                Occupation code   Median hourly   and overhead ($/  Adjustedhourly
                                                                 wage ($/hr)          hr)          wage ($/hr)
----------------------------------------------------------------------------------------------------------------
Medical Records and Health Information               29-2071            20.50            20.50            41.00
 Technician.................................
----------------------------------------------------------------------------------------------------------------

2. ICRs Regarding the Inpatient Psychiatric Facility Quality Reporting 
(IPFQR) Program
    In subsection 2.a., we restate our currently approved burden 
estimates. In subsection 2.b., we estimate the proposed adjustments in 
burden associated with the updated BLS wage rate, our facility 
estimates, and our case estimates. In subsection 2.c., we estimate the 
changes in burden associated with the proposals in this rule. Finally, 
in subsection 2.d., we provide an overview of the total estimated 
burden.
a. Currently Approved Burden
    For a detailed discussion of the burden for the IPFQR Program 
requirements that we have previously adopted, we refer readers to the 
following rules:
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53673);
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50964);
     The FY 2015 IPF PPS final rule (79 FR 45978 through 
45980);
     The FY 2016 IPF PPS final rule (80 FR 46720 through 
46721);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57265 through 
57266);
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38507 through 
38508);
     The FY 2019 IPF PPS final rule (83 FR 38609 through 
38612); and
     The FY 2020 IPF PPS final rule (84 FR 38468 through 
38476).
    Tables 8, 9, and 10 provide an overview of our currently approved 
burden. These tables use our previous estimate of $37.66 ($18.83 base 
salary plus $18.83 fringe benefits and overhead) hourly labor cost. For 
more information on our currently approved burden estimates, please see 
PRA Supporting Statement A on the Office of Information and Regulatory 
Affairs website.\138\
---------------------------------------------------------------------------

    \138\ https://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=201908-0938-011.

                                           Table 8--Currently Approved Measure Collection and Reporting Burden
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                Annual time
                                                                       Estimated     Time per       per                    Total annual    Total annual
        NQF #               Measure ID          Measure description    cases (per      case       facility   Number IPFs   time (hours)      cost ($)
                                                                       facility)     (hours)      (hours)
--------------------------------------------------------------------------------------------------------------------------------------------------------
0640................  HBIPS-2...............  Hours of Physical             1,283         0.25       320.75        1,679      538,539.25      20,281,388
                                               Restraint Use.
0641................  HBIPS-3...............  Hours of Seclusion Use        1,283         0.25       320.75        1,679      538,539.25      20,281,388
0560................  HBIPS-5...............  Patients Discharged on          609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Multiple
                                               Antipsychotic
                                               Medications with
                                               Appropriate
                                               Justification.
N/A.................  SUB-2 and SUB-2a......  Alcohol Use Brief               609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Intervention Provided
                                               or Offered.

[[Page 19517]]

 
N/A.................  SUB-3 and SUB-3a......  Alcohol and Other Drug          609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Use Disorder
                                               Treatment Provided or
                                               Offered at Discharge
                                               and Alcohol and Other
                                               Drug Use Disorder
                                               Treatment at
                                               Discharge.
0576................  FUH...................  Follow-Up After                   0            0            0            0               0               0
                                               Hospitalization for
                                               Mental Illness *.
N/A.................  TOB-2 and TOB-2a......  Tobacco Use Treatment           609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Provided or Offered
                                               and Tobacco Use
                                               Treatment.
N/A.................  TOB-3 and TOB-3a......  Tobacco Use Treatment           609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Provided or Offered
                                               at Discharge and
                                               Tobacco Use Treatment
                                               at Discharge.
1659................  IMM-2.................  Influenza Immunization          609         0.25       152.25        1,679      255,627.75       9,626,941
0647................  N/A...................  Transition Record with          609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Specified Elements
                                               Received by
                                               Discharged Patients
                                               (Discharges from an
                                               Inpatient Facility to
                                               Home/Self Care or Any
                                               Other Site of Care).
0648................  N/A...................  Timely Transmission of          609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Transition Record
                                               (Discharges from an
                                               Inpatient Facility to
                                               Home/Self Care or Any
                                               Other Site of Care).
N/A.................  N/A...................  Screening for                   609         0.25       152.25        1,679      255,627.75       9,626,941
                                               Metabolic Disorders.
2860................  N/A...................  Thirty-day all-cause              0            0            0            0               0               0
                                               unplanned readmission
                                               following psychiatric
                                               hospitalization in an
                                               IPF *.
3205................  Med Cont..............  Medication                        0            0            0            0               0               0
                                               Continuation
                                               Following Inpatient
                                               Psychiatric Discharge
                                               *.
                                                                     -----------------------------------------------------------------------------------
    Total...........  ......................  ......................        8,047       Varies     2,011.75        1,679       3,377,728     127,205,245
--------------------------------------------------------------------------------------------------------------------------------------------------------
* CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any
  cases.


                                      Table 9--Currently Approved Non-Measure Data Collection and Reporting Burden
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     Annual time per                                                       Total annual
                       Tasks                          Number IPFs        facility       Total annual    Wage rate ($/     Cost per IPF     cost for all
                                                                         (hours)        time (hours)         hr)              ($)            IPFs ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-measure Data Collection and Submission........           1,679              2.0            3,358            37.66            75.32          126,462
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                    Table 10--Currently Approved Total Burden
----------------------------------------------------------------------------------------------------------------
              Requirement                 Respondents           Responses          Time (hours)      Cost ($)
----------------------------------------------------------------------------------------------------------------
Measure Data Collection and Reporting.           1,679  13,510,913 (8,047              3,377,728     127,205,245
                                                         responses or cases per
                                                         facility * 1,679
                                                         facilities).
Non-Measure Data Collection and                  1,679  6,716 (4 * responses per           3,358         126,462
 Reporting.                                              facility * 1,679
                                                         facilities) 4.
Notice of Participation, Data Accuracy             N/A  N/A.....................             N/A             N/A
 Acknowledgment, and Vendor
 Authorization Form *.
                                       -------------------------------------------------------------------------
    Total.............................           1,679  13,517,629..............       3,381,086     127,331,707
----------------------------------------------------------------------------------------------------------------
* The 15 minutes per measure for chart abstraction under Measure Data Collection and Reporting also includes the
  time for completing and submitting any forms.

b. Proposed Adjustments in Burden Due to Updated Wage, Facility Count, 
and Case Count Estimates
    In the FY 2020 IPF PPS final rule (84 FR 38468), which is the most 
recent rule, that updated the IPFQR Program policies, we estimated that 
there were 1,679 participating IPFs and that (for measures that require 
reporting on the entire patient population) these facilities will 
report on an average of 1,283 cases per facility. In this FY 2022 rule, 
we are proposing to update our facility count and case estimates by 
using the most recent data available. Specifically, we estimate that 
there are now approximately 1,634 facilities (a decrease of 45 
facilities) and an average of 1,346 cases per facility (an increase of 
63 cases per facility). Tables 11, 12,

[[Page 19518]]

and 13, depict the effects of these updates, as well as the wage rate 
update to $41.00/hr described in section V.A.1 of the preamble of this 
proposed rule, on our previously estimated burden.

                  Table 11--Measure Collection and Reporting Burden Based on Updated Cases per Facility, Facility Counts, and Wage Rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                              Annual time
                                                                     Estimated     Time per       per                    Total annual     Total annual
        NQF #               Measure ID        Measure description    cases (per      case       facility   Number IPFs   time (hours)       cost ($)
                                                                     facility)     (hours)      (hours)
--------------------------------------------------------------------------------------------------------------------------------------------------------
0640................  HBIPS-2..............  Hours of Physical            1,346         0.25       336.50        1,634         549,841        22,543,481
                                              Restraint Use.
0641................  HBIPS-3..............  Hours of Seclusion           1,346         0.25       336.50        1,634         549,841        22,543,481
                                              Use.
0560................  HBIPS-5..............  Patients Discharged          * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              on Multiple
                                              Antipsychotic
                                              Medications with
                                              Appropriate
                                              Justification.
N/A.................  SUB-2 and SUB-2a.....  Alcohol Use Brief            * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              Intervention
                                              Provided or Offered
                                              and Alcohol Use
                                              Brief Intervention
                                              Provided.
N/A.................  SUB-3 and SUB-3a.....  Alcohol and Other            * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              Drug Use Disorder
                                              Treatment Provided
                                              or Offered at
                                              Discharge and
                                              Alcohol and Other
                                              Drug Use Disorder
                                              Treatment at
                                              Discharge.
0576................  FUH..................  Follow-Up After                  0            0            0            0               0                 0
                                              Hospitalization for
                                              Mental Illness *.
N/A.................  TOB-2 and TOB-2a.....  Tobacco Use Treatment        * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              Provided or Offered
                                              and Tobacco Use
                                              Treatment.
N/A.................  TOB-3 and TOB-3a.....  Tobacco Use Treatment        * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              Provided or Offered
                                              at Discharge and
                                              Tobacco Use
                                              Treatment at
                                              Discharge.
1659................  IMM-2................  Influenza                    * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              Immunization.
0647................  N/A..................  Transition Record            * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              with Specified
                                              Elements Received by
                                              Discharged Patients
                                              (Discharges from an
                                              Inpatient Facility
                                              to Home/Self Care or
                                              Any Other Site of
                                              Care).
0648................  N/A..................  Timely Transmission          * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              of Transition Record
                                              (Discharges from an
                                              Inpatient Facility
                                              to Home/Self Care or
                                              Any Other Site of
                                              Care).
N/A.................  N/A..................  Screening for                * 609         0.25       152.25        1,634       248,776.5     10,199,836.50
                                              Metabolic Disorders.
2860................  N/A..................  Thirty-day all-cause             0            0            0            0               0                 0
                                              unplanned
                                              readmission
                                              following
                                              psychiatric
                                              hospitalization in
                                              an IPF*.
3205................  Med Cont.............  Medication                       0            0            0            0               0                 0
                                              Continuation
                                              Following Inpatient
                                              Psychiatric
                                              Discharge*.
N/A.................  COVID-19 HCP.........  COVID-19 Vaccination          ** 0            0            0            0               0                 0
                                              Rate Among
                                              Healthcare Personnel.
N/A.................  FAPH.................  Follow-Up After                  0            0            0            0               0                 0
                                              Psychiatric
                                              Hospitalization.
                                                                   -------------------------------------------------------------------------------------
    Total...........  .....................  .....................        8,173       Varies     2,043.25        1,634       3,338,671       136,885,491
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Under our previously finalized ``global sample'' (80 FR 46717 through 46718) we allow facilities to apply the same sampling methodology to all
  measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR 46718), we finalized that facilities with between 609 and 3,056 cases that
  choose to participate in the global sample would be required to report data for 609 cases. Because facilities are only required to submit data on a
  number specified by the global sampling methodology, rather than abstracting data for all patients or applying measure specific sampling
  methodologies, we believe that the number of cases under the global sample is a good approximation of facility burden associated with these measures.
  Therefore, for the average IPF discharge rate of 1,346 discharges versus the previously estimated 1,283, the global sample continues to require
  abstraction of 609 records.
** The COVID-19 HCP measure will be calculated using data submitted to the CDC under a separate OMB Control Number (0920-1317).


             Table 12--Non-Measure Data Collection and Reporting Burden Based on Updated Cases per Facility, Facility Counts, and Wage Rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     Annual time per                                                       Total annual
                       Tasks                          Number IPFs        facility       Total annual    Wage rate ($/     Cost per IPF     cost for all
                                                                         (hours)        time (hours)         hr)              ($)            IPFs ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-measure Data Collection and Submission........           1,634              2.0            3,268            41.00            82.00          133,988
--------------------------------------------------------------------------------------------------------------------------------------------------------


[[Page 19519]]


           Table 13--Total Burden Based on Updated Cases per Facility, Facility Counts, and Wage Rate
----------------------------------------------------------------------------------------------------------------
              Requirement                 Respondents           Responses          Time (hours)      Cost ($)
----------------------------------------------------------------------------------------------------------------
Measure Data Collection and Reporting.           1,634  13,354,682 (8,173              3,338,671     136,885,491
                                                         responses per facility
                                                         * 1,634 facilities).
Non-Measure Data Collection and                  1,634  6,536 (4 responses per             3,268         133,988
 Reporting.                                              facility * 1,634
                                                         facilities).
                                       -------------------------------------------------------------------------
    Total.............................           1,634  13,361,218..............       3,341,939     137,019,479
----------------------------------------------------------------------------------------------------------------

c. Changes in Burden Due to This Proposed Rule
(1). Updates Due to Proposed Measure Adoptions
    In section IV.E of this preamble, we are proposing to adopt the 
following two measures:
     COVID-19 HCP Vaccination for FY 2023 Payment Determination 
and Subsequent Years; and
     Follow-Up After Psychiatric Hospitalization (FAPH) for FY 
2024 Payment Determination and Subsequent Years.
    We are proposing to adopt the COVID-19 HCP Vaccination measure 
beginning with an initial reporting period from October 1 to December 
31, 2021 affecting the FY 2023 payment determination followed by annual 
reporting beginning with the FY 2024 payment determination and 
subsequent years. IPFs would submit data through the CDC NHSN. The NHSN 
is a secure, internet-based system maintained by the CDC and provided 
free. Currently the CDC does not estimate burden for COVID-19 
vaccination reporting under the CDC PRA package currently approved 
under OMB control number 0920-1317 because the agency has been granted 
a waiver under Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA).\139\
---------------------------------------------------------------------------

    \139\ Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA) provides the PRA waiver for activities that come under the 
NCVIA, including those in the NCVIA at section 2102 of the Public 
Health Service Act (42 U.S.C. 300aa-2). Section 321 is not codified 
in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    Although the burden as associated with the COVID-19 HCP Vaccination 
measure is not accounted for under the CDC PRA package currently 
approved under OMB control number 0920-1317 due to the NCVIA waiver, 
the cost and burden information is discussed here and will be included 
in a revised information collection request for 0920-1317. Consistent 
with the CDC's experience of collecting data using the NHSN, we 
estimate that it would take each IPF on average approximately 1 hour 
per month to collect data for the COVID-19 Vaccination Coverage among 
HCP measure and enter it into NHSN. We have estimated the time to 
complete this entire activity, since it could vary based on provider 
systems and staff availability. This burden is comprised of 
administrative hours and wages. We believe it would take an 
Administrative Assistant \140\ between 45 minutes and 1 hour and 15 
minutes to enter this data into NHSN. For the CY 2021 reporting period 
(consisting of October 1, 2021 through December 31, 2021) 3 months are 
required. For the CY 2021 reporting period/FY 2023 payment 
determination, IPFs would incur an additional burden between 2.25 hours 
(0.75 hours * 3 months) and 3.75 hours (1.25 hours * 3 months) per IPF. 
For all 1,634 IPFs, the total burden would range from 3,676.5 (2.25 
hours * 1,634 IPFs) and 6,127.5 hours (3.75 hours * 1,634 IPFs). Each 
IPF would incur an estimated cost of between $27.47 (0.75 hour * 
$36.62/hr) and $45.78 (1.25 hours * 36.63/hr) monthly and between 
$82.40 (2.25 hours * $36.62/hr) and $137.33 (3.75 hours * $36.62/hr) in 
total over the CY 2021 reporting period to complete this task. 
Thereafter, 12 months of data are required annually. Therefore, IPFs 
would incur an additional annual burden between 9 hours (0.75 hours/
month * 12 months) and 15 hours (1.25 hours/month * 12 months) per IPF 
and between 14,706 hours (9 hours/IPF * 1,634 IPFs) and 24,510 hours 
(15 hours/IPF * 1,634 IPFs) for all IPFs. Each IPF would incur an 
estimated cost of between $329.58 (9 hours x $36.62/hr) and $549.30 
annually (15 hours x $36.62/hr). The estimated cost across all 1,634 
IPFs would be between $134,641.6 ($82.40/IPF * 1,634 IPFs) and 
$224,397.22 ($137.33/IPF * 1,634 IPFs) for the CY 2021 reporting 
period. The estimated cost across all 1,634 IPFs would be between 
$538,533.72 ($329.58/IPF * 1,634 IPFs) and $897,556.2 ($549.30/IPF * 
1,634 IPFs) annually thereafter.
---------------------------------------------------------------------------

    \140\ https://www.bls.gov/oes/current/oes436013.htm (accessed on 
March 30, 2021). The hourly rate of $36.62 includes an adjustment of 
100 percent of the median hourly wage to account for the cost of 
overhead, including fringe benefits.
---------------------------------------------------------------------------

    We recognize that many healthcare facilities are also reporting 
other COVID-19 data to HHS. We believe the benefits of requiring IPFs 
to report data on the COVID-19 HCP Vaccination measure to assess 
whether they are taking steps to limit the spread of COVID-19 among 
their healthcare workers and to help sustain the ability of IPFs to 
continue serving their communities throughout the PHE and beyond 
outweigh the costs of reporting. We welcome comments on the estimated 
time to collect data and enter it into the NHSN.
    We further note that as described in section IV.E.C of this 
preamble, we will calculate performance on the FAPH measure using 
Medicare Part A and Part B claims that facilities and other providers 
submit for payment. Since this is a claims-based measure, there is no 
additional burden outside of submitting the claim. The claim submission 
is approved by OMB under control number 0938-0050 (CMS-2552-10). This 
rule does not propose any changes under that control number.
(2). Updates Due to Proposed Measure Removals
    In section IV.F. of this preamble, we are proposing to remove the 
following four measures for the FY 2024 payment determination and 
subsequent years:
     SUB-2--Alcohol Use Brief Intervention Provided or Offered 
and the subset measure SUB-2a Alcohol Use Brief Intervention Provided;
     TOB-2--Tobacco Use Brief Intervention Provided or Offered 
and the subset measure TOB-2a Tobacco Use Brief Intervention;
     Timely Transmission of Transition Record (Discharges from 
an Inpatient Facility to Home/Self Care or Any Other Site of Care); and
     FUH--Follow-Up After Hospitalization for Mental Illness 
(NQF #0576).
    For the FY 2024 payment determination, data on CY 2022 performance 
would be reported during the summer of 2023. Therefore, we are applying 
the burden reduction that would occur to the FY 2023 burden 
calculation. Three of these measures

[[Page 19520]]

(SUB-2/2a, TOB-2/2a, and the Timely Transmission measure) fall under 
our previously finalized ``global sample'' (80 FR 46717 through 46718) 
and, therefore, would require abstraction of 609 records. We estimate 
that removing each of these three measures would result in a decrease 
in burden of 152.25 hours per facility, or 248,776.5 hours (152.25 
hours x 1,634 facilities) across all IPFs. Therefore, the decrease in 
costs for each measure is approximately $6,242.25 per IPF ($41.00hr * 
152.25 hours), or $10,199,836.50 across all IPFs ($6,242.25/facility * 
1,634 facilities). For all three of these chart-abstracted measures the 
total decrease in burden is approximately 456.75 hours per IPF (3 
measures * 152.25 hours per measure) or 746,329.5 hours across all IPFs 
(3 measures * 248,776.5 hours per measure). This equates to $18,726.75 
per IPF (3 measures * $6,242.25 per measure), or $30,599,509.50 across 
all IPFs (3 measures * $10,199,836.50 per measure).
    We have previously estimated that the FUH (NQF #0576) measure does 
not have any reporting burden because it is calculated from Medicare 
FFS claims. Therefore, we do not anticipate a reduction in facility 
burden associated with the removal of this measure. Table 14 describes 
our estimated reduction in burden associated with removing these four 
measures.

                                                Table 14--Burden Updates Due to Proposed Measure Removals
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                              Annual time
                                                                     Estimated     Time per       per                    Total annual     Total annual
        NQF #               Measure ID        Measure description    cases (per      case       facility   Number IPFs   time (hours)       cost ($)
                                                                     facility)     (hours)      (hours)
--------------------------------------------------------------------------------------------------------------------------------------------------------
N/A.................  SUB-2 and SUB-2a.....  Alcohol Use Brief            (609)         0.25       152.25        1,634     (248,776.5)    (10,199,836.5)
                                              Intervention
                                              Provided or Offered.
0576................  FUH..................  Follow-Up After                  0            0            0        1,634               0                 0
                                              Hospitalization for
                                              Mental Illness *.
N/A.................  TOB-2 and TOB-2a.....  Tobacco Use Treatment        (609)         0.25       152.25        1,634     (248,776.5)    (10,199,836.5)
                                              Provided or Offered
                                              and Tobacco Use
                                              Treatment.
0648................  N/A..................  Timely Transmission          (609)         0.25       152.25        1,634     (248,776.5)    (10,199,836.5)
                                              of Transition Record
                                              (Discharges from an
                                              Inpatient Facility
                                              to Home/Self Care or
                                              Any Other Site of
                                              Care).
                                                                   -------------------------------------------------------------------------------------
    Total...........  .....................  .....................      (1,827)       Varies     (456.75)        1,634     (746,329.5)   (30,599,509.50)
--------------------------------------------------------------------------------------------------------------------------------------------------------
* CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require facilities to submit data on any
  cases.

(3). Updates Due to Proposed Administrative Policies
(a). Updates Associated With Proposed Updated Reference to QualityNet 
System Administrator
    In section IV.J.1.a of this preamble, we proposed to use the term 
``QualityNet security official'' instead of ``QualityNet system 
administrator.'' Because this proposed update would not change the 
individual's responsibilities, we do not believe there would be any 
changes to the information collection burden as a result of this 
update. We also do not believe that removing the requirement for 
facilities to have an active QualityNet security official account to 
qualify for payment updates will affect burden because we continue to 
recommend that facilities maintain an active QualityNet security 
official account.
(b). Updates Associated With Proposed Adoption of Patient-Level 
Reporting for Certain Chart Abstracted Measures
    In section IV.J.2.c of this preamble, we propose to adopt patient-
level data submission for the eleven chart-abstracted measures 
currently in the IPFQR Program measure set (for more details on these 
measures we refer readers to Table 6). Because submission of aggregate 
data requires facilities to abstract patient-level data, then calculate 
measure performance prior to submitting data through the QualityNet 
website's secure portal, facilities must already abstract patient-level 
data. Therefore, we do not believe that submitting data that facilities 
must already calculate through a tool that facilities already have 
experience using will change provider burden.
d. Overall Burden Summary
    Table 15 summarizes the estimated burden associated with the IPFQR 
Program if the proposals in this rule are finalized.

                                 Table 15--Total Estimated IPFQR Program Burden
----------------------------------------------------------------------------------------------------------------
                                          Estimated                Annual time
                                          responses     Time per       per       Total annual     Total annual
      Measure/response description           per        response     facility    time (hours)       cost ($)
                                           facility     (hours)      (hours)
----------------------------------------------------------------------------------------------------------------
Hours of Physical Restraint Use........        1,346         0.25       336.50         549,841       $22,543,481
Hours of Seclusion Use.................        1,346         0.25       336.50         549,841        22,543,481
Patients Discharged on Multiple                * 609         0.25       152.25       248,776.5     10,199,836.50
 Antipsychotic Medications with
 Appropriate Justification.............
Alcohol and Other Drug Use Disorder            * 609         0.25       152.25       248,776.5     10,199,836.50
 Treatment Provided or Offered at
 Discharge and Alcohol and Other Drug
 Use Disorder Treatment at Discharge...
Tobacco Use Treatment Provided or              * 609         0.25       152.25       248,776.5     10,199,836.50
 Offered at Discharge and Tobacco Use
 Treatment at Discharge................
Influenza Immunization.................        * 609         0.25       152.25       248,776.5     10,199,836.50
Transition Record with Specified               * 609         0.25       152.25       248,776.5     10,199,836.50
 Elements Received by Discharged
 Patients (Discharges from an Inpatient
 Facility to Home/Self Care or Any
 Other Site of Care)...................
Screening for Metabolic Disorders......        * 609         0.25       152.25       248,776.5     10,199,836.50
Thirty-day all-cause unplanned                  ** 0            0            0               0                 0
 readmission following psychiatric
 hospitalization in an IPF.............
Medication Continuation Following               ** 0            0            0               0                 0
 Inpatient Psychiatric Discharge.......
COVID-19 Vaccination Rate Among                *** 0            0            0               0                 0
 Healthcare Personnel..................
Follow-Up After Psychiatric                     ** 0            0            0               0                 0
 Hospitalization.......................

[[Page 19521]]

 
Non-Measure Data Collection and                    4          0.5          2.0           3,268           133,988
 Reporting.............................
                                        ------------------------------------------------------------------------
    Total..............................        6,346          N/A      1,588.5       2,595,609       106,419,969
----------------------------------------------------------------------------------------------------------------
* Under our previously finalized ``global sample'' (80 FR 46717 through 46718) we allow facilities to apply the
  same sampling methodology to all measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR
  46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global
  sample would be required to report data for 609 cases. Because facilities are only required to submit data on
  a number specified by the global sampling methodology, rather than abstracting data for all patients or
  applying measure specific sampling methodologies, we believe that the number of cases under the global sample
  is a good approximation of facility burden associated with these measures. Therefore, for the average IPF
  discharge rate of 1,346 discharges versus the previously estimated 1,283, the global sample continues to
  require abstraction of 609 records.
** CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not
  require facilities to submit data on any cases.
*** The COVID-19 HCP measure will be calculated using data submitted to the CDC under a separate OMB Control
  Number (0920-1317).

    The total change in burden associated with this proposed rule 
(including all updates to wage rate, case counts, facility numbers, and 
the measures and administrative policies) is a reduction of 785,477 
hours and $20,911,738 from our currently approved burden of 3,381,086 
hours and $127,331,707. We refer readers to Table 16 for details.

                  Table 16--Summary of Proposed Requirements and Annual Burden Estimates Under OMB Control Number 0938-1171 (CMS-10432)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                               Time per
                      Program changes                            Number           Total        response     Total time    Labor cost per  Total cost ($)
                                                               respondents      responses        (hr)          (hr)         hour ($/hr)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Active Burden..............................................           1,679      13,517,629       Varies       3,381,086           37.66     127,331,707
Total Burden Under CMS-1750-P..............................           1,634      10,375,900       Varies       2,595,609           41.00     106,419,969
PROPOSED CHANGES...........................................            (45)     (3,141,729)       Varies       (785,477)           +3.34    (20,911,738)
--------------------------------------------------------------------------------------------------------------------------------------------------------

B. Submission of PRA-Related Comments

    We have submitted a copy of this proposed rule to OMB for its 
review of the rule's information collection and recordkeeping 
requirements. The requirements are not effective until they have been 
approved by OMB.
    To obtain copies of the supporting statement and any related forms 
for the proposed collections previously discussed, visit CMS's website 
at: https://www.cms.gov/Regulations-and-Guidance/Legislation/PaperworkReductionActof1995/PRA-Listing.html or call the Reports 
Clearance Office at (410) 786-1326.
    We invite public comments on these information collection 
requirements. If you wish to comment, identify the rule (CMS-1750-P) 
and, where applicable, the preamble section, and the ICR section. See 
this rule's DATES and ADDRESSES sections for the comment due date and 
for additional instructions.

VI. 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 2022 (October 1, 2021 through September 30, 2022). 
We are proposing to apply the 2016-based IPF market basket increase of 
2.3 percent, less the productivity adjustment of 0.2 percentage point 
as required by 1886(s)(2)(A)(i) of the Act for a proposed total FY 2022 
payment rate update of 2.1 percent. In this proposed rule, we are 
proposing to update the IPF labor-related share and update the IPF wage 
index to reflect the FY 2022 hospital inpatient wage index.

B. Overall Impact

    We have examined the impacts of this proposed 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 (the Act), section 202 of the Unfunded Mandates Reform Act 
of 1995 (March 22, 1995; Pub. L. 104-4), and Executive Order 13132 on 
Federalism (August 4, 1999).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that maximize 
net benefits (including potential economic, environmental, public 
health and safety effects, distributive impacts, and equity). Section 
3(f) of Executive Order 12866 defines a ``significant regulatory 
action'' as an action that is likely to result in a rule: (1) Having an 
annual effect on the economy of $100 million or more in any 1 year, or 
adversely and materially affecting a sector of the economy, 
productivity, competition, jobs, the environment, public health or 
safety, or state, local or tribal governments or communities (also 
referred to as ``economically significant''); (2) creating a serious 
inconsistency or otherwise interfering with an action taken or planned 
by another agency; (3) materially altering the budgetary impacts of 
entitlement grants, user fees, or loan programs or the rights and 
obligations of recipients thereof; or (4) raising novel legal or policy 
issues arising out of legal mandates, the President's priorities, or 
the principles set forth in the Executive Order. In accordance with the 
provisions of Executive Order 12866, this regulation was reviewed by 
the Office of Management and Budget.
    We estimate that this rulemaking is likely to be economically 
significant as measured by the $100 million threshold, and hence, if 
finalized as proposed, a major rule under the Congressional Review Act. 
Accordingly, we have prepared a Regulatory Impact Analysis that to the 
best of our ability presents the costs and benefits of the rulemaking.
    We estimate that the total impact of these changes for FY 2022 
payments compared to FY 2021 payments will be a net increase of 
approximately $90 million. This reflects an $80 million increase from 
the update to the payment rates (+$90 million from the 4th quarter 2020 
IGI forecast of the 2016-based IPF market basket of 2.3 percent, and -
$10 million for the productivity adjustment

[[Page 19522]]

of 0.2 percentage point), as well as a $10 million increase as a result 
of the update to the outlier threshold amount. Outlier payments are 
estimated to change from 1.8 percent in FY 2021 to 2.0 percent of total 
estimated IPF payments in FY 2022.

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. The 
budget neutrality factor includes 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 
updating the wage index and labor-related share 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 2022 of 2.3 percent (see section 
III.A.4 of this proposed rule) less the productivity adjustment of 0.2 
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 2022 impact will be a net increase of $90 
million in payments to IPF providers. This reflects an estimated $80 
million increase from the update to the payment rates and a $10 million 
increase 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 2022. This estimate does not include the implementation of the 
required 2.0 percentage point reduction of the market basket update 
factor for any IPF that fails to meet the IPF quality reporting 
requirements (as discussed in section V.A. 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 IPF PPS rates and factors for FY 2022 versus those under FY 2021. 
We determined the percent change in the estimated FY 2022 IPF PPS 
payments compared to the estimated FY 2021 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 
update to the outlier fixed dollar loss threshold amount; the updated 
wage index data including the updated labor-related share; and the 
market basket update for FY 2022, as adjusted by the productivity 
adjustment according to section 1886(s)(2)(A)(i) of the Act.
    Our longstanding methodology uses the best available data as the 
basis for our estimates of payments. Typically, this is the most recent 
update of the latest available fiscal year of IPF PPS claims, and for 
this proposed rulemaking, that would be the FY 2020 claims. However, as 
discussed in section III.F.2 of this proposed rule, the U.S. healthcare 
system undertook an unprecedented response to the COVID-19 PHE during 
FY 2020. Therefore, we considered whether the most recent available 
year of claims, FY 2020, or the prior year, FY 2019, would be the best 
for estimating IPF PPS payments in FY 2021 and FY 2022.
    To illustrate the impacts of the FY 2022 changes in this proposed 
rule, our analysis presents a side-by-side comparison of payments 
estimated using FY 2019 claims versus payments estimated using FY 2020 
claims. We begin with FY 2019 IPF PPS claims (based on the 2019 MedPAR 
claims, June 2020 update) and FY 2020 IPF PPS claims (based on the 2020 
MedPAR claims, December 2020 update). We estimate FY 2021 IPF PPS 
payments using these 2019 and 2020 claims, the finalized FY 2021 IPF 
PPS Federal per diem base rates, and the finalized FY 2021 IPF PPS 
patient and facility level adjustment factors (as published in the FY 
2021 IPF PPS final rule (85 FR 47042 through 47070)). We then estimate 
the FY 2021 outlier payments based on these simulated FY 2021 IPF PPS 
payments using the same methodology as finalized in the FY 2021 IPF PPS 
final rule (85 FR 47061 through 47062) where total outlier payments are 
maintained at 2 percent of total estimated FY 2021 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 2022 IPF wage index, the proposed FY 2022 
labor-related share, and the proposed updated COLA factors.
     The proposed market basket update for FY 2022 of 2.3 
percent less the productivity adjustment of 0.2 percentage point in 
accordance with section 1886(s)(2)(A)(i) of the Act for a payment rate 
update of 2.1 percent.
    Our proposed column comparison in Table 17 illustrates the percent 
change in payments from FY 2021 (that is, October 1, 2020, to September 
30, 2021) to FY 2022 (that is, October 1, 2021, to September 30, 2022) 
including all the payment policy changes in this proposed rule. For 
each column, Table 17 presents a side-by-side comparison of the results 
using FY 2019 and FY 2020 IPF PPS claims.

                                                   Table 17--FY 2022 IPF PPS Proposed Payment Impacts
                                                         [Percent change in columns 3 through 5]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                    Number of facilities             Outlier            Wage index FY22, LRS,   Total percent change \1\
                                                 ----------------------------------------------------         and COLA         -------------------------
                Facility by type                                                                     --------------------------
                                                    FY 2019      FY 2020      FY 2019      FY 2020      FY 2019      FY 2020      FY 2019      FY 2020
                                                     Claims       Claims       Claims       Claims       Claims       Claims       Claims       Claims
--------------------------------------------------------------------------------------------------------------------------------------------------------
(1)                                                          (2)
                                                             (3)
                                                             (4)
                                                             (5)
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Facilities..................................        1,526        1,536          0.2         -0.7          0.0          0.0          2.3          1.4
    Total Urban.................................        1,226        1,238          0.2         -0.7          0.0          0.0          2.3          1.3
        Urban unit..............................          742          738          0.3         -1.1         -0.1         -0.1          2.3          0.9
        Urban hospital..........................          484          500          0.1         -0.2          0.0          0.0          2.2          1.9
    Total Rural.................................          300          298          0.1         -0.5          0.1          0.1          2.4          1.8
        Rural unit..............................          240          237          0.1         -0.6          0.0          0.0          2.2          1.5
        Rural hospital..........................           60           61          0.1         -0.2          0.5          0.5          2.7          2.4

[[Page 19523]]

 
By Type of Ownership:
Freestanding IPFs:
    Urban Psychiatric Hospitals:
        Government..............................          117          123          0.3         -1.1         -0.2         -0.2          2.2          0.7
        Non-Profit..............................           93           95          0.1         -0.3         -0.3         -0.2          1.9          1.6
        For-Profit..............................          274          282          0.0         -0.1          0.1          0.2          2.3          2.2
    Rural Psychiatric Hospitals:
        Government..............................           31           32          0.1         -0.4          0.5          0.6          2.8          2.2
        Non-Profit..............................           12           12          0.2         -0.7          0.0          0.1          2.3          1.5
        For-Profit..............................           17           17          0.0          0.0          0.6          0.6          2.7          2.7
IPF Units:
    Urban:
        Government..............................          109          108          0.4         -2.1          0.1          0.1          2.7          0.0
        Non-Profit..............................          482          480          0.3         -1.1         -0.1         -0.1          2.3          0.9
        For-Profit..............................          151          150          0.1         -0.5         -0.1         -0.1          2.2          1.5
    Rural:
        Government..............................           58           57          0.1         -0.2          0.3          0.2          2.5          2.1
        Non-Profit..............................          133          130          0.2         -0.8          0.0          0.0          2.2          1.2
        For-Profit..............................           49           50          0.1         -0.4         -0.2         -0.2          2.0          1.4
By Teaching Status:
    Non-teaching................................        1,329        1,339          0.1         -0.6          0.0          0.0          2.2          1.5
    Less than 10% interns and residents to beds.          106          106          0.3         -1.2          0.0          0.0          2.4          0.9
    10% to 30% interns and residents to beds....           70           70          0.4         -1.6          0.0          0.0          2.4          0.5
More than 30% interns and residents to beds.....           21           21          0.4         -1.9         -0.1         -0.1          2.4          0.1
By Region:
    New England.................................          106          106          0.2         -0.8         -0.3         -0.4          2.0          1.0
    Mid-Atlantic................................          215          217          0.3         -1.3         -0.2         -0.2          2.1          0.5
    South Atlantic..............................          241          243          0.1         -0.5          0.7          0.7          2.9          2.3
    East North Central..........................          245          245          0.1         -0.4         -0.1         -0.1          2.2          1.5
    East South Central..........................          152          155          0.1         -0.5         -0.7         -0.7          1.5          0.8
    West North Central..........................          110          110          0.2         -0.9          0.2          0.2          2.6          1.4
    West South Central..........................          225          227          0.1         -0.4         -0.3         -0.3          1.9          1.4
    Mountain....................................          103          102          0.1         -0.4          0.1          0.1          2.3          1.8
    Pacific.....................................          129          131          0.2         -0.9          0.4          0.5          2.8          1.6
By Bed Size:
    Psychiatric Hospitals:
        Beds: 0-24..............................           85           90          0.1         -0.3          0.1          0.1          2.3          1.9
        Beds: 25-49.............................           79           83          0.1         -0.2         -0.5         -0.4          1.7          1.4
        Beds: 50-75.............................           84           87          0.0         -0.1          0.1          0.3          2.3          2.3
        Beds: 76 +..............................          296          301          0.1         -0.3          0.1          0.1          2.3          2.0
    Psychiatric Units:
        Beds: 0-24..............................          540          531          0.2         -0.8          0.0         -0.1          2.3          1.2
        Beds: 25-49.............................          258          259          0.2         -0.9          0.0          0.0          2.4          1.2
        Beds: 50-75.............................          115          115          0.3         -1.1         -0.2         -0.3          2.2          0.7
        Beds: 76 +..............................           69           70          0.3         -1.6          0.0          0.0          2.4          0.4
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ This column includes the impact of the updates in column (3) and (4) above, and of the proposed IPF market basket increase factor for FY 2022 (2.3
  percent), reduced by 0.2 percentage point for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act. Note, the products of
  these impacts may be different from the percentage changes shown here due to rounding effects.

3. Impact Results
    Table 17 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 1,526 IPFs 
included in the analysis for FY 2019 claims or the 1,536 IPFs included 
in the analysis for FY 2020 claims. In column 2, we present the number 
of facilities of each type that had information available in the PSF 
and also had claims in the MedPAR dataset for FY 2019 or FY 2020. The 
number of providers in each category therefore differs slightly between 
the two years.
    In column 3, we present the effects of the update to the outlier 
fixed dollar loss threshold amount. Based on the FY 2019 claims, we 
would estimate that IPF outlier payments as a percentage of total IPF 
payments are 1.8 percent in FY 2021. Alternatively, based on the FY 
2020 claims, we would estimate that IPF outlier payments as a 
percentage of total IPF payments are 2.7 percent in FY 2021.
    Thus, we are proposing to adjust the outlier threshold amount in 
this proposed rule to set total estimated outlier payments equal to 2.0 
percent of total payments in FY 2022. Based on the FY 2019 claims, the 
estimated change in total IPF payments for FY 2022 would include an 
approximate 0.2 percent increase in payments because we would expect 
the outlier portion of total payments to increase from approximately 
1.8 percent to 2.0 percent. Alternatively, based on the FY 2020 claims, 
the estimated change in total IPF payments for FY 2022 would include an 
approximate 0.7 percent decrease in payments because we would expect 
the outlier portion of total

[[Page 19524]]

payments to decrease from approximately 2.7 percent to 2.0 percent.
    The overall impact of the estimated increase or decrease to 
payments due to updating the outlier fixed dollar loss threshold (as 
shown in column 3 of Table 17), across all hospital groups, is 0.2 
percent based on the FY 2019 claims, or -0.7 percent based on the FY 
2020 claims. If we decrease the outlier fixed dollar loss threshold 
based on the FY 2019 claims, the largest increase in payments due to 
this change is estimated to be 0.4 percent for urban, government-owned 
IPF units and also 0.4 percent for teaching IPFs with 10 percent or 
more interns and residents to beds. These same provider types, along 
with IPF units having more than 75 beds, would experience the largest 
estimated decrease in payments if we instead increase the outlier fixed 
dollar loss threshold based on the FY 2020 claims distribution.
    In column 4, we present the effects of the budget-neutral update to 
the IPF wage index, the Labor-Related Share (LRS), and the proposed 
updated COLA factors discussed in section III.D.3. 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 updated COLA factors 
and the update from the FY 2021 IPF wage index to the proposed FY 2022 
IPF wage index, which includes basing the FY 2022 IPF wage index on the 
FY 2022 pre-floor, pre-reclassified IPPS hospital wage index data and 
updating the LRS from 77.3 percent in FY 2021 to 77.1 percent in FY 
2022. We note that there is no projected change in aggregate payments 
to IPFs, as indicated in the first row of column 4; however, there will 
be distributional effects among different categories of IPFs. We also 
note that when comparing the results using FY 2019 and FY 2020 claims, 
the distributional effects are very similar. For example, we estimate 
the largest increase in payments to be 0.7 percent for IPFs in the 
South Atlantic region, and the largest decrease in payments to be -0.7 
percent for IPFs in the East South Central region, based on either the 
FY 2019 or FY 2020 claims.
    Finally, column 5 compares the total proposed changes reflected in 
this proposed rule for FY 2022 to the estimates for FY 2021 (without 
these changes). The average estimated increase for all IPFs is 
approximately 2.3 percent based on the FY 2019 claims, or 1.4 percent 
based on the FY 2020 claims. These estimated net increases include the 
effects of the 2016-based market basket update of 2.3 percent reduced 
by the productivity adjustment of 0.2 percentage point, as required by 
section 1886(s)(2)(A)(i) of the Act. They also include the overall 
estimated 0.2 percent increase or 0.7 percent decrease in estimated IPF 
outlier payments as a percent of total payments from updating the 
outlier fixed dollar loss threshold amount. In addition, column 5 
includes the distributional effects of the proposed updates to the IPF 
wage index, the labor-related share, and the proposed updated COLA 
factors, whose impacts are displayed in column 4. Based on the FY 2020 
claims distribution, the increase to estimated payments due to the 
market basket update factor are offset in large part for some provider 
types by the increase to the outlier fixed dollar loss threshold.
    In summary, comparing the impact results for the FY 2019 and FY 
2020 claims, the largest difference in the results is due to the update 
to the outlier fixed dollar loss threshold. Therefore, we examined the 
differences between the FY 2019 and FY 2020 claims distributions to 
better understand the disparity in the estimate of outlier payments as 
a percentage of total PPS payments between the two years, which is 
driving the divergent results in column 3 of Table 17.
    The calculation of the estimated outlier percentage has two 
components: Estimated outlier payments and estimated total PPS 
payments. As discussed in section III.F.1 of this proposed rule, 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. Therefore, estimated outlier 
payments are a function of both estimated IPF costs and estimated IPF 
Federal per diem payment amounts per case. As such, we looked at 
changes in estimated costs, estimated Federal per diem payment amounts, 
estimated outlier payments, and estimated total PPS payments in order 
to understand the differences in the estimated outlier percentage when 
using the FY 2019 and FY 2020 claims data. To facilitate the comparison 
between our FY 2019 and FY 2020 datasets, we inflated all estimated 
costs to the midpoint of FY 2021 and estimated all payments based on 
the finalized FY 2021 IPF PPS patient and facility level adjustment 
factors (as published in the FY 2021 IPF PPS final rule (85 FR 47042 
through 47070)). In summary, we found that estimated outlier payments 
using the FY 2020 claims dataset are 26 percent higher than the 
estimated outlier payments using the FY 2019 claims dataset, due to 
estimated costs per stay that were relatively higher than estimated 
Federal per diem payment amounts per stay. Estimated total payments 
using the FY 2020 claims dataset are 14 percent lower than the 
estimated total payments using the FY 2019 claims dataset. Therefore, 
both the estimated outlier payments and estimated total payments are 
contributing to the differences in the estimated outlier payment 
percentage of 2.7 percent using the FY 2020 claims dataset and 1.8 
percent using the FY 2019 claims dataset. We discuss estimated total 
payments and estimated outlier payments in more detail below.
    As stated above, we observed a reduction of estimated total PPS 
payments of approximately 14 percent using the FY 2020 claims dataset 
relative to estimated total PPS payments in our FY 2019 claims dataset. 
The reduction in estimated total PPS payments corresponds with a 
roughly 15 percent decline in covered IPF days and a roughly 17 percent 
decline in covered IPF stays. The consistency between the decline in 
IPF stays and IPF days indicates the overall length of stay is fairly 
consistent in the FY 2019 claims dataset and FY 2020 claims dataset.
    An important consideration for how we estimate the percentage of 
estimated outlier payments in FY 2022 is whether we expect this lower 
level of total payments to persist in future years. We note that 
although there has been a downward trend in IPF stays and total 
payments in recent years, the decrease from FY 2019 to FY 2020 is 2 to 
3 times greater than the decreases in recent prior years. Looking on a 
monthly basis at the claims in our FY 2020 claims dataset, we observed 
that estimated total PPS payments per month declined sharply, nearly 28 
percent, from January 2020 to April 2020. Estimated total PPS payments 
per month decreased overall by approximately 21 percent from January 
2020 to September 2020. The lower estimated total PPS payments per 
month were a result of both lower covered IPF days and covered IPF 
stays. The COVID-19 PHE was declared on January 31, 2020, and continued 
through the end of FY 2020, with an initial surge in cases occurring in 
many places in the early months of the PHE. Based on the timing of the 
declines in covered IPF stays and covered IPF days, we believe they are 
related to the response to the COVID-19 PHE. Therefore, we do not 
anticipate that decreases in total PPS payments,

[[Page 19525]]

covered IPF days, and covered IPF stays of the same magnitude as 
observed in FY 2020 are likely to occur in FY 2022. We are seeking 
comments on this analysis. Specifically, we are requesting comments 
from stakeholders about likely explanations for the declines in total 
PPS payments, covered IPF days, and covered IPF stays in FY 2020.
    Next, we looked at estimated outlier payments. Estimated outlier 
payments were approximately 26 percent higher using the FY 2020 claims 
data compared to estimated outlier payments using the FY 2019 claims 
data despite overall covered IPF stays being approximately 17 percent 
lower using the FY 2020 claims data. As stated above, 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. We examined estimated IPF costs and estimated IPF 
Federal per diem payment amounts in order to understand the increase in 
estimated outlier payments. Overall, estimated costs were approximately 
12 percent lower when using the FY 2020 claims dataset. However, 
estimated Federal per diem payment amounts were approximately 15 
percent lower. In other words, both estimated costs and estimated 
Federal per diem payments declined along with the number of stays, but, 
importantly, estimated Federal per diem payment amounts decreased by a 
greater amount. When we account for the number of stays, we can see 
that estimated costs and Federal per diem payment amounts per stay were 
greater in FY 2020 than in FY 2019, but the increase in estimated cost 
per stay was greater. Estimated Federal per diem payment amounts per 
stay were approximately 2.5 percent higher using the FY 2020 claims 
dataset than estimated Federal per diem payment amounts per stay using 
the FY 2019 claims dataset. However, estimated costs per stay were 
about 6.0 percent higher than estimated Federal per diem payments per 
stay using the FY 2019 claims dataset. In other words, we observed that 
estimated costs per stay increased by more than estimated IPF Federal 
per diem payment amounts per stay when the FY 2020 claims dataset was 
used. As a result, total estimated costs were approximately 12 percent 
lower but total estimated Federal per diem payments were approximately 
15 percent lower. This difference between estimated costs and estimated 
Federal per diem payments contributed to the 26 percent greater 
estimated outlier payments using the FY 2020 claims dataset.
    We wanted to understand whether there were monthly trends in 
estimated costs and estimated Federal per diem payment amounts that 
would explain why estimated costs increased more than estimated Federal 
per diem payment amounts from FY 2019 to FY 2020, and if any of these 
monthly trends might be related to the COVID-19 PHE. Looking on a 
monthly basis, we observed that estimated cost per stay and estimated 
IPF Federal per diem payment per stay generally moved in line with 
average length of stay until July 2020, however estimated costs 
remained relatively higher than estimated payments from July 2020 until 
September 2020. Discharges in our dataset occurring in February and 
March 2020 had an average length of stay that was roughly 6 percent 
shorter than for discharges occurring in April 2020, and for May 2020, 
average length of stay was approximately 4 percent shorter than in the 
preceding month. We observed comparable peaks and valleys in average 
cost per stay and average estimated IPF Federal per diem payment per 
stay. However, the changes in average cost per stay were smaller, 
around a 3 percent increase from March 2020 to April 2020 and a 3.4 
decrease percent from April 2020 to May 2020. Additionally, we observed 
that estimated cost per stay declined less than average length of stay 
and estimated IPF Federal per diem payment per stay from July 2020 to 
September 2020, declining approximately 0.6 percent compared to 1.4 
percent for length of stay and 1.5 percent for estimated IPF Federal 
per diem payment per stay. In other words, we observed that from July 
2020 to September 2020, the declines in estimated payments were greater 
than the declines in estimated costs, and therefore the gap between 
costs and payments increased during this period.
    Looking specifically at estimated outlier cases on a monthly basis, 
we observed a similar trend from March 2020 to May 2020 in average 
length of stay, estimated IPF Federal per diem payment per stay, and 
estimated cost per stay to those we observed in all FY 2020 claims in 
our dataset. However, from July 2020 to September 2020, estimated cost 
per stay, estimated IPF Federal per diem payment per stay, and average 
length of stay all increased. Estimated cost per stay and estimated 
length of stay increased approximately 3.9 percent and 2.0 percent, 
whereas estimated IPF Federal per diem payment per stay increased by a 
lower amount, approximately 2.4 percent. Additionally, we observed that 
estimated outlier payment per outlier stay was approximately 50 percent 
higher in July 2020 than it was in May 2020. In September 2020 
estimated outlier payment per outlier stay was approximately 62 percent 
higher than May 2020. In other words, we observed that the divergence 
in estimated costs and estimated payments in our FY 2020 dataset 
corresponded with the increase in estimated outlier payment per stay.
    Because the IPF PPS is a per diem payment system, we also looked at 
whether increased length of stay was contributing to the increased 
estimated outlier payment per case. Among estimated outlier cases, we 
calculated the estimated outlier payment per covered IPF day. We 
observed that estimated outlier payment per covered day was nearly 69 
percent greater in July 2020 than it was in May 2020, and remained at a 
higher level through the end of the year than at the start of the year. 
Compared to January 2020, average length of stay for estimated outlier 
cases in September 2020 was approximately 10 percent lower, whereas 
estimated outlier payment per outlier stay was approximately 52 percent 
higher. Therefore, we concluded that increased length of stay among 
estimated outlier cases does not appear to be driving the increase in 
estimated outlier payments.
    We examined the distribution of DRGs throughout the FY 2020 claims 
in our dataset but did not observe variation that would explain the 
substantial increases in estimated outlier payments. In general, the 
majority of IPF cases have a DRG of 885 (Psychoses). The percentage of 
claims with this DRG remained very similar from FY 2019 (74.5 percent) 
to FY 2020 (75.2 percent), and this percentage did not appear to 
diverge or fluctuate meaningfully during FY 2020. We also looked at 
comorbidities and observed that the percentage of cases with a 
comorbidity increased slightly, from approximately 3.6 percent in our 
FY 2019 dataset to 3.8 percent in our FY 2020 dataset. In general, most 
IPF cases in both FY 2019 and FY 2020 did not have any IPF 
comorbidities. Among cases with at least one comorbidity, the number of 
cases for each comorbidity category declined in FY 2020, with the 
exception of Chronic Obstructive Pulmonary Disorder. We note that this 
is the IPF comorbidity category in which the COVID-19 diagnosis code, 
U07.1, falls. However, cases with this comorbidity category remained a 
relatively small percentage of all IPF cases, approximately 0.8 percent 
in FY 2019 and approximately 1.3 percent in FY 2020. Additionally, 
among estimated

[[Page 19526]]

outlier cases, those with at least one comorbidity received 
approximately 58 percent less estimated outlier pay per covered day 
than those without any comorbidities. This makes intuitive sense, 
because cases with an IPF comorbidity would receive a payment 
adjustment corresponding to the appropriate IPF comorbidity category, 
therefore reducing the difference between estimated IPF Federal per 
diem payments and costs for those cases. Therefore, it does not seem 
likely that cases with IPF comorbidities were the main driver of the 
increases in estimated outlier payments.
    Observing that changes in DRGs and comorbidities did not appear to 
be driving the increased estimated outlier payments in FY 2020, we 
wanted to understand what was causing the higher estimated costs 
relative to estimated IPF Federal per diem payments that we observed in 
FY 2020. Following our longstanding methodology, we estimate the costs 
per case based on the covered charges on each IPF claim and the IPF's 
most recent CCR. Therefore, in order to better understand estimated 
costs, we looked at covered charges in FY 2019 and FY 2020. For this 
analysis, we used a different source for claims which enabled us to 
calculate covered charge by categories corresponding to the MedPAR 
ancillary departments. We analyzed FY 2019 and FY 2020 IPF claims data 
from the Common Working File (CWF).
    In general, laboratory charges make up roughly one third of the 
covered charges per IPF claim. Comparing FY 2019 to FY 2020, we 
observed that covered lab charges per claim in our CWF dataset 
increased approximately 6.8 percent. Looking on a monthly basis, we 
observed fluctuation in covered lab charges per claim and per day 
during the COVID-19 PHE. We looked specifically at the period January 
2020 (the month in which the COVID-19 PHE was declared) to September 
2020 (the end of FY 2020), and observed peaks and valleys in covered 
lab charges that we believe may be related to the response to the 
COVID-19 PHE. Covered lab charges per day increased approximately 6.3 
percent (2.4 percent per claim) from January 2020 to March 2020, 
decreased approximately 7.1 percent (1.1 percent per claim) from March 
2020 to April 2020, and then increased approximately 6.2 percent (0.9 
percent per claim) from April 2020 to September 2020. Overall, covered 
lab charges per day increased approximately 4.9 percent (2.2 percent 
per claim) from January 2020 to September 2020. In other words, most of 
the 6.8 percent increase in covered lab charges from FY 2019 to FY 2020 
occurred during the period January 2020 to September 2020, with the 
highest levels of lab charges occurring during February/March and June 
through September. Based on the data available, we are not able to 
determine the root cause of these increases in covered lab charges 
during the COVID-19 PHE, however we acknowledge that these increased 
charges may be related to services in response to the COVID-19 PHE, 
such as COVID-19 testing. We are requesting comments on this analysis. 
Specifically, we are requesting comments from stakeholders about likely 
explanations for the observed fluctuations and overall increases in 
covered lab charges per claim and per day. We are also requesting 
comments regarding likely explanations for the increases in estimated 
cost per stay relative to estimated IPF Federal per diem payment 
amounts per stay.
    As discussed in this section, estimated outlier payments increased 
and estimated total PPS payments decreased, when comparing FY 2020 to 
FY 2019. Based on our analysis, we believe it is likely that the 
response to the COVID-19 PHE in FY 2020 has contributed to both of 
these trends. As a result, in contrast to our usual methodology, we are 
not confident that FY 2020 claims are the best available data for 
setting the FY 2022 proposed outlier fixed dollar loss threshold. 
Furthermore, the distributional effects of the updates presented in 
column 4 of Table 17 (the budget-neutral update to the IPF wage index, 
the LRS, and the proposed updated COLA factors) are very similar when 
using the FY 2019 or FY 2020 claims data. Therefore, we believe the FY 
2019 claims would be the best available data for estimating payments in 
this FY 2022 proposed rulemaking, and we are proposing to use the FY 
2019 claims to calculate the outlier fixed dollar loss threshold and 
wage index budget neutrality factor.
    IPF payments are therefore estimated to increase by 2.3 percent in 
urban areas and 2.4 percent in rural areas based on this proposal. 
Overall, IPFs are estimated to experience a net increase in payments as 
a result of the updates in this proposed rule. The largest payment 
increase is estimated at 2.9 percent for IPFs in the South Atlantic 
region.
4. Effect on Beneficiaries
    Under the FY 2022 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 as proposed in this rule 
will improve or maintain beneficiary access to high quality care by 
ensuring that payment rates reflect the best available data on the 
resources involved in inpatient psychiatric care and the costs of these 
resources. We continue to expect that paying prospectively for IPF 
services under the FY 2022 IPF PPS will enhance the efficiency of the 
Medicare program.
    As discussed in sections IV.E.2, IV.E.3, and V.A.2.d of this 
proposed rule, we expect that additional program measures will improve 
follow-up for patients with both mental health and substance use 
disorders and ensure health-care personnel COVID-19 vaccinations. We 
also estimate a $20,911,738 reduction in information collection burden 
as a result of our measure removal proposals. Therefore, we expect that 
the proposed updates to the IPFQR program will improve quality for 
beneficiaries.
5. Effects of Updates to the IPFQR Program
    As discussed in section V. of this proposed rule and in accordance 
with section 1886(s)(4)(A)(i) of the Act, we will apply a 2 percentage 
point reduction in the FY 2022 market basket update for IPFs that have 
failed to comply with the IPFQR Program requirements for FY 2022, 
including reporting on the required measures. In section V. of this 
proposed rule, we discuss how the 2 percentage point reduction will be 
applied. For FY 2021, of the 1,634 IPFs eligible for the IPFQR Program, 
43 IPFs (2.6 percent) did not receive the full market basket update 
because of the IPFQR Program; 31 of these IPFs chose not to participate 
and 12 did not meet the requirements of the program. We anticipate that 
even fewer IPFs would receive the reduction for FY 2022 as IPFs become 
more familiar with the requirements. Thus, we estimate that the IPFQR 
Program will have a negligible impact on overall IPF payments for FY 
2022.
    Based on the IPFQR Program proposals made in this proposed rule, we 
estimate a total decrease in burden of 785,477 hours across all IPFs, 
resulting in a total decrease in information collection burden of 
$20,911,738 across all IPFs. As discussed in section VI. of this 
proposed rule, we will attribute the cost savings associated with the 
proposals to the year in which these savings begin; for the purposes of 
all the proposals in this proposed rule, that year is FY 2023. Further 
information on these estimates

[[Page 19527]]

can be found in section VI. of this proposed rule.
    We intend to closely monitor the effects of the IPFQR Program on 
IPFs and help facilitate successful reporting outcomes through ongoing 
stakeholder education, national trainings, and a technical help desk.
6. Regulatory Review Costs
    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret this proposed rule, we 
should estimate the cost associated with regulatory review. Due to the 
uncertainty involved with accurately quantifying the number of entities 
that will be directly impacted and will review this proposed rule, we 
assume that the total number of unique commenters on the most recent 
IPF proposed rule from FY 2021 (85 FR 20625) will be the number of 
reviewers of 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 2021 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 
solicited 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, 2019 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 $110.74 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 93.5 minutes 
(1.56 hours) for the staff to review half of this proposed rule, which 
is approximately 23,365 words. For each IPF that reviews the proposed 
rule, the estimated cost is (1.56 x $110.74) or $172.75. Therefore, we 
estimate that the total cost of reviewing this proposed rule is 
$79,810.50 ($172.75 x 462 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; applying the 2016-based IPF PPS market basket update for FY 2022 
of 2.3 percent, reduced by the statutorily required multifactor 
productivity adjustment of 0.2 percentage point along with the wage 
index budget neutrality adjustment to update the payment rates; and 
proposing a FY 2022 IPF wage index which uses the FY 2022 pre-floor, 
pre-reclassified IPPS hospital wage index as its basis.
    As discussed in section VI.C.3 of this proposed rule, we also 
considered using FY 2020 claims data to determine the proposed FY 2022 
outlier fixed dollar loss threshold, wage index budget neutrality 
factor, per diem base rate, and ECT rate. For the reasons discussed in 
that section, we are proposing to use FY 2019 claims data.

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 18, 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 18 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 1,526 IPFs with data available in the PSF and with claims in 
our FY 2019 MedPAR claims dataset. Table 18 also includes our best 
estimate of the cost savings for the 1,634 IPFs eligible for the IPFQR 
Program. Lastly, Table 18 also includes our best estimate of the costs 
of reviewing and understanding this proposed rule.

            Table 18--Accounting Statement: Classification of Estimated Costs, Savings, and Transfers
----------------------------------------------------------------------------------------------------------------
                                      Primary                                              Units
                                      estimate       Low          High    --------------------------------------
             Category                ($million/    estimate     estimate       Year       Discount      Period
                                       year)                                 dollars      rate (%)     covered
----------------------------------------------------------------------------------------------------------------
Regulatory Review Costs...........         0.08  ...........  ...........         2020  ...........  * 2021-2022
Annualized Monetized Costs Savings       -20.91       -15.68       -26.14         2020            7  * 2023-2031
                                         -17.79       -13.34       -22.24         2020            3    2023-2031
Annualized Monetized Transfers               90  ...........  ...........         2020  ...........    2021-2022
 from Federal Government to IPF
 Medicare Providers...............
----------------------------------------------------------------------------------------------------------------

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 17, we estimate that the overall revenue impact 
of this proposed rule on all IPFs is to increase estimated Medicare 
payments by approximately 2.3 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

[[Page 19528]]

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 V.C.1 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 240 rural 
excluded psychiatric units and 60 rural psychiatric hospitals in our 
database of 1,526 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 2021, that 
threshold is approximately $158 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 
$158 million in any one 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.

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 chapter IV as set forth 
below:

PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL 
SERVICES

0
1. The authority citation for part 412 continues to read as follows:

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

0
2. Section 412.402 is amended by adding definitions for ``Closure of an 
IPF'', ``Closure of an IPF's residency training program'', and 
``Displaced resident'' in alphabetical order to read as follows:


Sec.  412.402   Definitions.

* * * * *
    Closure of an IPF means closure of a hospital as defined in Sec.  
413.79(h)(1)(i) by an IPF meeting the requirements of Sec.  412.404(b) 
for the purposes of accounting for indirect teaching costs.
    Closure of an IPF's residency training program means closure of a 
hospital residency training program as defined in Sec.  
413.79(h)(1)(ii) by an IPF meeting the requirements of Sec.  412.404(b) 
for the purposes of accounting for indirect teaching costs.
* * * * *
    Displaced resident means a displaced resident as defined in Sec.  
413.79(h)(1)(iii) for the purposes of accounting for indirect teaching 
costs.
* * * * *
0
3. Section 412.424 is amended by revising paragraph (d)(1)(iii)(F) to 
read as follows:


Sec.  412.424   Methodology for calculating the Federal per diem 
payment amount.

* * * * *
    (d) * * *
    (1) * * *
    (iii) * * *
    (F) Closure of an IPF. (1) For cost reporting periods beginning on 
or after July 1, 2011, an IPF may receive a temporary adjustment to its 
FTE cap to reflect displaced residents added because of another IPF's 
closure if the IPF meets the following criteria:
    (i) The IPF is training additional displaced residents from an IPF 
that closed on or after July 1, 2011.
    (ii) No later than 60 days after the IPF begins to train the 
displaced residents, the IPF submits a request to its Medicare 
contractor for a temporary adjustment to its cap, documents that the 
IPF is eligible for this temporary adjustment by identifying the 
displaced residents who have come from the closed IPF and have caused 
the IPF to exceed its cap, and specifies the length of time the 
adjustment is needed.
    (2) Closure of an IPF's residency training program. If an IPF that 
closes its residency training program on or after July 1, 2011, agrees 
to temporarily reduce its FTE cap according to the criteria specified 
in paragraph (d)(1)(iii)(F)(2)(ii) of this section, another IPF(s) may 
receive a temporary adjustment to its FTE cap to reflect displaced 
residents added because of the closure of the residency training 
program if the criteria specified in paragraph (d)(1)(iii)(F)(2)(i) of 
this section are met.
    (i) Receiving IPF(s). For cost reporting periods beginning on or 
after July 1, 2011, an IPF may receive a temporary adjustment to its 
FTE cap to reflect displaced residents added because of the closure of 
another IPF's residency training program if the IPF is training 
additional displaced residents from the residency training program of 
an IPF that closed a program; and if no later than 60 days after the 
IPF begins to train the displaced residents, the IPF submits to its 
Medicare Contractor a request for a temporary adjustment to its FTE 
cap, documents that it is eligible for this temporary adjustment by 
identifying the displaced residents who have come from another IPF's 
closed program and have caused the IPF to exceed its cap, specifies the 
length of time the adjustment is needed, and submits to its Medicare 
contractor a copy of the FTE reduction statement by the hospital that 
closed its program, as specified in paragraph (d)(1)(iii)(F)(2)(ii) of 
this section.
    (ii) IPF that closed its program. An IPF that agrees to train 
displaced residents who have been displaced by the closure of another 
IPF's program may receive a temporary FTE cap adjustment only if the 
hospital with the closed program temporarily reduces its FTE cap based 
on the FTE of displaced residents in each program year training in the 
program at the time of the program's closure. This yearly reduction in 
the FTE cap will be determined based on the number of those displaced 
residents who would have been training in the program during that year 
had the program not closed. No later than 60 days after the displaced 
residents who were in the closed program begin training at another 
hospital, the hospital with the closed program must submit to its 
Medicare contractor a statement signed and dated by its representative 
that specifies that it agrees to the temporary reduction in its FTE cap 
to allow the IPF training the displaced residents to obtain a temporary 
adjustment to its cap; identifies the displaced residents who were in 
training at the time of the program's closure; identifies the IPFs to 
which the displaced residents are transferring once the program closes; 
and specifies the

[[Page 19529]]

reduction for the applicable program years.
* * * * *
0
4. Section 412.434 is amended by revising paragraph (b)(3) to read as 
follows:


Sec.  412.434   Reconsideration and appeals procedures of Inpatient 
Psychiatric Facilities Quality Reporting (IPFQR) Program decisions.

* * * * *
    (b) * * *
    (3) Contact information for the inpatient psychiatric facility's 
chief executive officer and QualityNet security official, including 
each individual's name, email address, telephone number, and physical 
mailing address;
* * * * *

    Dated: March 29, 2021.
Elizabeth Richter,
Acting Administrator, Centers for Medicare & Medicaid Services.
    Dated: April 6, 2021.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2021-07433 Filed 4-7-21; 4:15 pm]
BILLING CODE 4120-01-P

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