Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals (IPPS) and the Long-Term Care Hospital Prospective Payment System and Policy Changes and Fiscal Year (FY) 2026 Rates; Changes to the FY 2025 IPPS Rates Due to Court Decision; Requirements for Quality Programs; and Other Policy Changes; Health Data, Technology, and Interoperability: Electronic Prescribing, Real-Time Prescription Benefit and Electronic Prior Authorization rogram were to be extended by law beyond September 30, 2025, similar to how it was extended by prior legislation as described previously, we would, depending on timing of such legislation in relation to the final rule, modify our proposed conforming changes to the regulations governing the MDH program at § 412.108(a)(1) and (c)(2)(iii) and the general payment rules at § 412.90(j) to reflect any such further extension of the MDH program. We also noted that these modifications to our proposed conforming changes would only be made if the MDH program were to be extended by statute beyond September 30, 2025. Comment: Many commenters expressed support for extending the MDH program or making the MDH program permanent and noted that they would continue supporting congressional efforts to protect the MDH program. A few commenters urged CMS to advocate for action to be taken to ensure that the MDH program is extended. Several state hospital associations expressed their concern that hospitals in their states would experience significant payment decreases as a result of the expiration of the MDH program. One commenter stated that if CMS moves forward with the proposed changes, any transitional their states would experience significant payment decreases as a result of the expiration of the MDH program. One commenter stated that if CMS moves forward with the proposed changes, any transitional payments must be meaningful and implemented over a multi-year period to VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00379 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36914 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations prevent harmful disruptions in patient care. Another commenter asked that CMS consider whether any alternative regulatory flexibilities exist to assist these hospitals if the program is not renewed. Some commenters also expressed support for increasing the base rates for these hospitals. Others supported an additional base rate for calculating MDH payments. Response: While we appreciate the commenters’ concerns about the expiration of the MDH program and the financial impact to affected providers if the MDH program is not extended beyond FY 2025, CMS does not have the authority under current law to extend the MDH program beyond the September 30, 20 nd the financial impact to affected providers if the MDH program is not extended beyond FY 2025, CMS does not have the authority under current law to extend the MDH program beyond the September 30, 2025 statutory expiration date. Similarly, section 1886(b)(3)(D) of the Act specifies the applicable base years or ‘‘target amounts’’ for hospitals classified as MDHs. These comments are similar to comments we received previously, prior to the most recent statutory extension of the MDH program for FY 2025. We refer commenters to our discussion in the FY 2025 IPPS/ LTCH PPS final rule (89 FR 69353). In response to the comment requesting CMS explore other regulatory support options, should Congress not act, we may consider this for future rulemaking. Comment: Several commenters expressed support for CMS’ policy that allows MDHs to apply for SCH status in advance of the expiration of the MDH program and be paid as such under certain conditions. A commenter requested that CMS provide technical assistance to MDHs seeking to transition to SCH classification. Commenters requested that CMS explicitly clarify how it would handle the MDH program should Congress extend it and requested that CMS exp ssistance to MDHs seeking to transition to SCH classification. Commenters requested that CMS explicitly clarify how it would handle the MDH program should Congress extend it and requested that CMS expedite restoration of MDH status and expeditiously process claims in the event the program lapses. Commenters also urged CMS to ensure that affected hospitals have access to technical assistance and timely guidance to minimize confusion. Other commenters requested that CMS provide instructions to MACs during program extensions, especially in instances when extensions are made retroactively. A commenter requested that CMS publish disaggregated impact analyses to help stakeholders and legislators understand the projected consequences of expiration. Response: We appreciate the commenters’ support of our policy allowing MDHs to apply for SCH status in advance of the expiration of the MDH program and to be paid as such under certain conditions and allow for a seamless transition from MDH classification to SCH classification. MDHs looking to apply for SCH classification should contact their individual MACs for assistance on the application requirements or for any technical assistance. We appr ication to SCH classification. MDHs looking to apply for SCH classification should contact their individual MACs for assistance on the application requirements or for any technical assistance. We appreciate the commenters’ sharing their concerns relating to a retroactive restoration of the MDH program. As with past extensions, CMS will evaluate enacted legislation to determine the most appropriate approach to implement changes to the law, including issuing instructions to the MACs to reinstate MDH status to eligible hospitals and to communicate with affected hospitals. As in the past, we will make every effort to implement any extension of the MDH program as expeditiously as possible. In response to the comment requesting that CMS publish disaggregated impact analyses to help stakeholders and legislators understand the projected financial effect of expiration, we refer the commenter to the provider data used in creating Table I—Impact Analysis of Changes to the IPPS for Operating Costs for FY 2026, in Appendix A of this final rule and posted on the web which can be used to estimate individual hospital’s payments for FY 2026. The data can be found on the CMS website at https:// www. for FY 2026, in Appendix A of this final rule and posted on the web which can be used to estimate individual hospital’s payments for FY 2026. The data can be found on the CMS website at https:// www.cms.gov/medicare/payment/ prospective-payment-systems/acute- inpatient-pps. In addition, we note in Table I in Appendix A of this final rule, the lines reflecting the changes for ‘‘Bed Size (Rural)’’ with 0–49 beds and 50–99 beds generally reflect the expected impact for hospitals classified as MDH prior to the expiration on October 1, 2025 under current law. In summary, under current law, beginning October 1, 2025, all hospitals that previously qualified for MDH status will no longer have MDH status. After consideration of the public comments we received, we are adopting as final the proposed conforming changes to the regulations text at §§ 412.90 and 412.108 to reflect the extension of the MDH program through September 30, 2025 in accordance with section 2202 of the Full-Year Continuing Appropriations and Extensions Act, 2025 (Pub. L. 119–4). We are finalizing the proposed changes in paragraphs (a)(1) and (c)(2)(iii) of § 412.108 and paragraph (j) of § 412.90 without modification. F. Appropriations and Extensions Act, 2025 (Pub. L. 119–4). We are finalizing the proposed changes in paragraphs (a)(1) and (c)(2)(iii) of § 412.108 and paragraph (j) of § 412.90 without modification. F. Payment for Indirect and Direct Graduate Medical Education Costs (§§ 412.105 and 413.75 through 413.83) 1. Background Section 1886(h) of the Act, as added by section 9202 of the Consolidated Omnibus Budget Reconciliation Act (COBRA) of 1985 (Pub. L. 99–272) and as currently implemented in the regulations at 42 CFR 413.75 through 413.83, establishes a methodology for determining payments to hospitals for the direct costs of approved graduate medical education (GME) programs. Section 1886(h)(2) of the Act sets forth a methodology for the determination of a hospital-specific base-period per resident amount (PRA) that is calculated by dividing a hospital’s allowable direct costs of GME in a base period by its number of full-time equivalent (FTE) residents in the base period. The base period is, for most hospitals, the hospital’s cost reporting period beginning in FY 1984 (that is, October 1, 1983, through September 30, 1984). The base year PRA is updated annually for inflation. In general s, for most hospitals, the hospital’s cost reporting period beginning in FY 1984 (that is, October 1, 1983, through September 30, 1984). The base year PRA is updated annually for inflation. In general, Medicare direct GME payments are calculated by multiplying the hospital’s updated PRA by the weighted number of FTE residents working in all areas of the hospital complex (and at non-provider sites, when applicable), and the hospital’s Medicare share of total inpatient days. Section 1886(d)(5)(B) of the Act provides for a payment adjustment known as the indirect medical education (IME) adjustment under the IPPS for hospitals that have residents in an approved GME program, in order to account for the higher indirect patient care costs of teaching hospitals relative to nonteaching hospitals. The regulations regarding the calculation of this additional payment are located at 42 CFR 412.105. The hospital’s IME adjustment applied to the DRG payments is calculated based on the ratio of the hospital’s number of FTE residents training in either the inpatient or outpatient departments of the IPPS hospital (and, for discharges occurring on or after October 1, 1997, at non- provider sites, when pital’s number of FTE residents training in either the inpatient or outpatient departments of the IPPS hospital (and, for discharges occurring on or after October 1, 1997, at non- provider sites, when applicable) to the number of inpatient hospital beds. The calculation of both direct GME payments and the IME payment adjustment is affected by the number of FTE residents that a hospital is allowed to count. Generally, the greater the number of FTE residents a hospital counts, the greater the amount of Medicare direct GME and IME payments the hospital will receive. In an attempt to end the implicit incentive for hospitals to increase the number of FTE residents, Congress established a limit on the number of allopathic and osteopathic residents that a hospital could include in its FTE resident count for direct GME and IME payment purposes in the Balanced Budget Act of 1997 (Pub. L. 105–33). Under section 1886(h)(4)(F) of the Act, for cost VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00380 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules a 00000 Frm 00380 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36915 reporting periods beginning on or after October 1, 1997, a hospital’s unweighted FTE count of residents for purposes of direct GME cannot exceed the hospital’s unweighted FTE count for direct GME in its most recent cost reporting period ending on or before December 31, 1996. Under section 1886(d)(5)(B)(v) of the Act, a similar limit based on the FTE count for IME during that cost reporting period is applied, effective for discharges occurring on or after October 1, 1997. Dental and podiatric residents are not included in this statutorily mandated cap. We received some comments related to IME and direct GME payment that were outside the scope of the proposed rule, including comments related to the eligibility of SCHs and MDHs paid under the hospital-specific rate to receive IME payments. Because we consider these public comments to be outside the scope of the proposed rule, we are not addressing these comments in this final rule. 2. Calculating Full-time Equivalent eive IME payments. Because we consider these public comments to be outside the scope of the proposed rule, we are not addressing these comments in this final rule. 2. Calculating Full-time Equivalent Counts and Caps for Cost Reporting Periods Other Than Twelve Months CMS’s full-time equivalent (FTE) counting regulations, as established in the September 29, 1989, Federal Register (54 FR 40291), specify that no individual should be counted as more than one FTE, and that FTE status is based on the total time necessary to fill a residency slot and the share of total time spent training at each training site (see 42 CFR 412.105(f)(1)(iii)(A) for IME and 42 CFR 413.78(b)(1) for DGME). The requirements for what constitutes full- time participation may vary from specialty to specialty, or among different programs in the same specialty. Additionally, full-time equivalency may be computed based on various increments, such as hours, days, weeks, or months, in order for a hospital to obtain the full-time equivalent which it is allowed to count. Full-time equivalency for each resident is computed by determining the portion of total allowable training time that may be claimed by each hospital. I ll-time equivalent which it is allowed to count. Full-time equivalency for each resident is computed by determining the portion of total allowable training time that may be claimed by each hospital. In general, these data are sourced from a ‘‘master’’ rotation schedule for each approved residency program. Each rotation may consist of both allowable and non-allowable training time. For example, the time that a resident spends in a hospital’s distinct-part unit is allowable to the hospital for purposes of DGME, but not for purposes of IME, while time spent in research activities at an offsite nonpatient care facility is not allowable for either DGME or IME. Additionally, a hospital cannot claim the time spent by residents training at another hospital. Consistent with the regulations at 42 CFR 413.75(d), hospitals that cross-train residents in the same program need to agree on the method of computing FTEs to ensure that no resident is counted as more than one FTE. For purposes of completing the Medicare cost report (Worksheet E, Part A, for IME and Worksheet E–4 for DGME of Form CMS–2552–10), full- time equivalency is typically calculated on the basis of 365 days (or 366 days, in the ng the Medicare cost report (Worksheet E, Part A, for IME and Worksheet E–4 for DGME of Form CMS–2552–10), full- time equivalency is typically calculated on the basis of 365 days (or 366 days, in the case of a leap year) for DGME versus the actual number of days in the cost reporting period for IME. Thus, for a standard 12-month cost reporting period, there is no difference in the calculation of the DGME and IME FTE counts. In the case of a cost reporting period other than 12 months in length, the statute for both DGME and IME instructs the Secretary to make ‘‘appropriate modifications’’ to ensure that the FTE counts are based on the equivalent of 12 months. Specifically, for DGME, section 1886(h)(4)(G)(ii) states that if any cost reporting period beginning on or after October 1, 1997, is not equal to 12 months, the Secretary shall make appropriate modifications to ensure that the average full-time equivalent resident counts pursuant to section 1886(h)(4)(G)(i) are based on the equivalent of full 12-month cost reporting periods. Similarly, for IME, section 1886(d)(5)(B)(vii) states that if any cost reporting period beginning on or after October 1, 1997, is not equal to 12 months, t ent of full 12-month cost reporting periods. Similarly, for IME, section 1886(d)(5)(B)(vii) states that if any cost reporting period beginning on or after October 1, 1997, is not equal to 12 months, the Secretary shall make appropriate modifications to ensure that the average full-time equivalent residency count pursuant to section 1886(d)(5)(B)(vi)(II) is based on the equivalent of full 12-month cost reporting periods. The procedures for determining the total DGME and IME FTE counts for a non-12-month cost reporting period reflect the underlying differences in the two payment methodologies. A hospital’s DGME count represents the number of FTE residents working in the healthcare complex over the course of an entire cost reporting period, and the total DGME payment is based on the hospital’s PRA, which reflects the average costs incurred per resident during a 12-month base period or equivalent (see discussion at 54 FR 40290). Accordingly, the DGME FTE count must be prorated to reflect the length of a short or long cost reporting period, as illustrated in the following section of this preamble. By contrast, the IME adjustment reflects the average intensity of teaching activity in a h he length of a short or long cost reporting period, as illustrated in the following section of this preamble. By contrast, the IME adjustment reflects the average intensity of teaching activity in a hospital at any given time, and the total IME payment is based on the hospital’s DRG payments during a cost reporting period. Because the size of a hospital’s DRG payments already reflects the amount of patient care furnished during a short or long cost reporting period, it is not necessary to prorate the IME FTE count in the same manner as the DGME FTE count. Similarly, as explained later in this section, proration must be applied to a hospital’s DGME FTE cap (but not the IME FTE cap) to account for a non-12- month cost reporting period, as well as to the prior- and penultimate-year DGME FTE counts (but not the IME FTE counts) for the purpose of calculating the three-year rolling average FTE count. We also note that, while these methodological distinctions become apparent in the context of calculating the counts and caps for a non-12-month cost reporting period, they are equally applicable in the case of a standard 12- month cost reporting period. In the FY 2026 IPPS/LTCH PPS Proposed calculating the counts and caps for a non-12-month cost reporting period, they are equally applicable in the case of a standard 12- month cost reporting period. In the FY 2026 IPPS/LTCH PPS Proposed Rule (90 FR 18274 through 18277), we stated that while CMS’s FTE counting policy is long-established and widely used in existing cost reporting software and the Intern and Resident Information System (IRIS) software, we were taking the opportunity to restate and clarify our FTE counting policy in rulemaking. We did not propose any changes to the FTE counting policy in the proposed rule. a. Calculating FTE Counts To determine the unweighted FTE count for DGME, whether or not the cost reporting period is 12 months, or more or less, the following steps should be used: • For each resident and each of that resident’s individual rotations, determine the ratio of total days allowable to the hospital in that rotation, to total days in that entire rotation, consistent with the regulations at 42 CFR 413.78. • Multiply the ratio from Step 1 by the ratio of (total days in the entire rotation divided by 365) (or 366, in the case of a leap year).162 This represents the portion of total FTE time for 413.78. • Multiply the ratio from Step 1 by the ratio of (total days in the entire rotation divided by 365) (or 366, in the case of a leap year).162 This represents the portion of total FTE time for this rotation that may be claimed by the hospital for purposes of DGME payment, prorated for the length of the cost reporting period. • Calculate the sum of the products from Step 2 for all residents and rotations in the hospital’s programs to arrive at the hospital’s total unweighted 162 366 days should be used when the cost reporting period includes February 29. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00381 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36916 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations DGME FTE count for the cost reporting period. Stated formulaically: Unweighted DGME FTE count = Sum of [(Allowable days in a rotation/Total days in the rotation) × (Total days in the rotation/365)] Note: This portion of the FTE calculation is not weighted for years outside of the Initial Residency Period, as the application of weighting factors is a separate s × (Total days in the rotation/365)] Note: This portion of the FTE calculation is not weighted for years outside of the Initial Residency Period, as the application of weighting factors is a separate step in the calculation of DGME payment on the cost report. See 42 CFR 413.79(a) for more information about the Initial Residency Period. Example: A resident worked in a rotation at Hospital A for 4 weeks (28 days) but spent 1 week (7 days) offsite engaged in non-patient care research. • Step 1: Consistent with the DGME regulations, the total time allowable to Hospital A for this rotation is 21 days. The ratio is (21 days/28 days) = 0.75. • Step 2: The portion of total FTE time for this rotation that Hospital A may claim for purposes of DGME payment is 0.75 × (28/365) = 0.06 FTE. (Note: In the case of a leap year, divide by 366 days.) • Step 3: Repeat Steps 1 and 2 for all residents and rotations in the hospital’s programs and sum the results from Step 2 to arrive at Hospital A’s total unweighted DGME FTE count for the cost reporting period. As stated previously, 365 or 366 days is used as the denominator in Step 2 of the calculation regardless of the actual number of days in the cost r ighted DGME FTE count for the cost reporting period. As stated previously, 365 or 366 days is used as the denominator in Step 2 of the calculation regardless of the actual number of days in the cost reporting period. Thus, in computing the DGME FTE count, the length of the cost reporting period can affect the full-time equivalency determined for a given number of residents training at the hospital. For example, there would be fewer total rotations in a 3-month cost reporting period than in a 12-month period, and thus a commensurately smaller DGME count calculated in accordance with the procedure outlined previously. Note that the hospital’s updated PRA is always used and is not prorated, as it represents that hospital’s average cost to train an FTE resident determined in a base period and is not dependent upon the length of cost reporting periods subsequent to the PRA base period. In this manner, the DGME FTE count continues to be based on the ‘‘equivalent of 12 months,’’ as required by section 1886(h)(4)(G)(ii) of the Act. This procedure is performed to determine the total unweighted DGME FTE count on Form CMS–2552–10, Worksheet E–4, line 6 and line 7, as well as for the weighted y section 1886(h)(4)(G)(ii) of the Act. This procedure is performed to determine the total unweighted DGME FTE count on Form CMS–2552–10, Worksheet E–4, line 6 and line 7, as well as for the weighted FTE counts on lines 8 through 11, lines 15 and 16, and lines 21 and 22. For lines that record weighted FTE counts, the appropriate weighting factors are applied consistent with the regulations at 42 CFR 413.79(a). As mentioned previously, the procedure for determining the 12-month equivalent IME FTE count, in accordance with section 1886(d)(5)(B)(vii) of the Act, is different in that the number of days used in the denominator of the calculation in Step 2 depends on the length of the cost reporting period. For 12-month cost reporting periods, a denominator of 365 days is used (or 366 days in the case of a leap year), while for cost reporting periods of different lengths, the denominator is equal to the actual number of days in the cost reporting period. The resulting FTE count represents the average number of residents in the hospital at any given time, and in turn is multiplied by the DRG payments in that same cost reporting period to obtain the hospital’s total IME payment. Accordingl e average number of residents in the hospital at any given time, and in turn is multiplied by the DRG payments in that same cost reporting period to obtain the hospital’s total IME payment. Accordingly, to determine the FTE count for IME, whether or not the cost reporting period is 12 months, or more or less, the following steps should be used: • For each resident and each of that resident’s individual rotations, determine the ratio of total days allowable to the hospital in that rotation, to total days in that entire rotation, consistent with the regulations at 42 CFR 412.105(f). • Multiply the ratio from Step 1 by the ratio of (total days in the entire rotation divided by the actual number of days in the cost reporting period). This represents the portion of total FTE time for this rotation that may be claimed by the hospital for purposes of IME payment. • Calculate the sum of the products from Step 2 for all residents and rotations in the hospital’s programs to arrive at the hospital’s total IME FTE count for the cost reporting period. Stated formulaically: IME FTE count = Sum of [(Allowable days in a rotation/Total days in the rotation) × (Total days in the rotation/Days in cos l’s total IME FTE count for the cost reporting period. Stated formulaically: IME FTE count = Sum of [(Allowable days in a rotation/Total days in the rotation) × (Total days in the rotation/Days in cost reporting period)] Example 1: 12-Month Cost Reporting Period (365 Days): A resident worked in a rotation at Hospital A for 4 weeks (28 days) but spent 1 week (7 days) offsite engaged in non-patient care research. Step 1: Consistent with the IME regulations, the total time allowable to Hospital A for this rotation is 21 days. The ratio is (21 days/28 days) = 0.75. Step 2: The portion of total FTE time for this rotation that Hospital A may claim for purposes of IME payment is 0.75 × (28/365) = 0.06 FTE. (Note: In the case of a leap year, divide by 366 days.) Step 3: Repeat Steps 1 and 2 for all residents and rotations in the hospital’s programs and sum the results from Step 2 to arrive at Hospital A’s total IME FTE count for the cost reporting period. Example 2: 3-Month Cost Reporting Period (92 Days): During a 92-day cost reporting period, a resident worked in a rotation at Hospital A for 4 weeks (28 days) but spent 1 week (7 days) offsite engaged in non-patient care research. Step 1: od (92 Days): During a 92-day cost reporting period, a resident worked in a rotation at Hospital A for 4 weeks (28 days) but spent 1 week (7 days) offsite engaged in non-patient care research. Step 1: Consistent with the IME regulations, the total time allowable to Hospital A for this rotation is 21 days. The ratio is (21 days/28 days) = 0.75. Step 2: The portion of total FTE time for this rotation that Hospital A may claim for purposes of IME payment is 0.75 × (28/92) = 0.23 FTE. Step 3: Repeat Steps 1 and 2 for all residents and rotations in the hospital’s programs and sum the results from Step 2 to arrive at Hospital A’s total IME FTE count for the 3-month cost reporting period. Consistent with the regulations at 42 CFR 412.105(b), the bed count used in the denominator of the intern and resident to bed (IRB) ratio is determined by counting the number of available bed days during the cost reporting period and dividing that number by the number of days in the cost reporting period. While the IME FTE count itself is not prorated, the final amount of a hospital’s IME payment nonetheless will be commensurate with the cost reporting period by virtue of the total amount of its DRG paym ile the IME FTE count itself is not prorated, the final amount of a hospital’s IME payment nonetheless will be commensurate with the cost reporting period by virtue of the total amount of its DRG payments, which will generally increase or decrease as a result of the length of the period. For example, if a cost reporting period is 12 months long, the DRG payments by which the IME adjustment factor is multiplied to derive the total IME payment will also reflect 12 months of patient care. By contrast, the DRG payments for the 3-month (or 92-day) cost reporting period in Example 2 would reflect just 3 months of patient care. This procedure is performed to determine the total IME FTE count on Form CMS–2552–10, Worksheet E, Part A, lines 10 through 12, as well as the FTE counts on lines 16 and 17 and lines 24 and 25. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00382 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36917 b. Calculating FTE Caps for Cost Reporting Periods Other Than Twelve Months Just as the DGME FTE counts ar k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36917 b. Calculating FTE Caps for Cost Reporting Periods Other Than Twelve Months Just as the DGME FTE counts are prorated on the basis of a standard 365- or 366-day cost reporting period, a hospital’s DGME FTE cap must similarly be prorated for cost reporting periods other than 12 months in length. To calculate the prorated cap, the hospital’s regular 12-month DGME FTE cap is divided by 365 days (or 366 days, in the case of a leap year) and then multiplied by the actual number of days in the cost reporting period. For example, if a hospital has a regular DGME FTE cap of 270 FTEs, then the prorated DGME cap for a 3-month cost reporting period with 92 days would be: (270/365) × (92) = 68.05 FTEs. (If the hospital subsequently had a 9-month cost report with 273 days, the DGME FTE cap for the 9-month cost report would be calculated as follows: (270/ 365) × (273) = 201.95 FTEs. Note that 68.05 + 201.95 = 270, equivalent to the total DGME cap for 12 months (totals may be slightly off due to rounding)). Proration applies similarly to all lines on Worksheet E–4 that are associated with the FTE cap, inc = 270, equivalent to the total DGME cap for 12 months (totals may be slightly off due to rounding)). Proration applies similarly to all lines on Worksheet E–4 that are associated with the FTE cap, including lines 1 through 5 and line 20. For reasons similar to those explained previously in the discussion of the FTE counts, it is not necessary to prorate the IME FTE caps for a non-12-month cost reporting period; the same IME FTE cap and any associated cap adjustments apply to a cost reporting period that is less than or more than 12 months. c. Calculating the Three-Year Rolling Average for Cost Reporting Periods of Unequal Lengths Sections 1886(d)(5)(B)(vi)(II) and 1886(h)(4)(G)(i) of the Act require that a hospital’s FTE counts for IME and DGME payment, respectively, in the current cost reporting period be based on a three-year rolling average. That is, the FTE counts in the current cost reporting period, prior cost reporting period, and penultimate cost reporting period are summed, then divided by 3. These provisions phase in any reductions or increases in payment over a three-year period for hospitals that experience a change in the number of residents they train. The regulations en divided by 3. These provisions phase in any reductions or increases in payment over a three-year period for hospitals that experience a change in the number of residents they train. The regulations are at 42 CFR 412.105(f)(1)(v) for IME and 42 CFR 413.79(d)(3) for DGME. lengths, adjustments must be made to the respective DGME FTE counts so that the rolling average is based on quantities that are comparable with one another. Accordingly, if the current cost reporting period is other than 12 months in length, the prior- and penultimate- year DGME FTE counts must be prorated, yielding 3 years of comparable FTE counts from which to calculate the rolling average: For the prior year, take the FTE count that would be reported on Worksheet E– 4, line 12, and divide by 365 (or 366, if the prior year cost reporting period includes February 29), and then multiply that quotient by the number of days in the current non-12-month cost reporting period. Report this prorated FTE count on Worksheet E–4, line 12, of the current year cost report. For the penultimate year, take the FTE count that would be reported on Worksheet E–4, line 13, and divide by 365 (or 366, if the penultimate year cost rep –4, line 12, of the current year cost report. For the penultimate year, take the FTE count that would be reported on Worksheet E–4, line 13, and divide by 365 (or 366, if the penultimate year cost reporting period includes February 29), and then multiply that quotient by the number of days in the current non-12- month cost reporting period. Report this prorated FTE count on Worksheet E–4, line 13, of the current year cost report. Stated formulaically: Prorated DGME FTE count = [(Total annual DGME FTE count/365 or 366) × (Number of days in current cost reporting period)] For example, if the current year cost reporting period is 3 months (92 days), while the prior year cost reporting period was 12 months, and the hospital’s total capped DGME FTE count in the prior year was 300, then the prorated FTE count for the prior year would be: [(300/365) × (92)] = 75.62. That is, a DGME FTE count of 300 in a 12-month cost reporting period would be the equivalent of 75.62 FTEs in the current year 3-month cost reporting period. On the current year cost report, the hospital would enter 75.62 on line 12 of Worksheet E–4 (prior year FTE count). If the total capped DGME FTE count in the penultimate -month cost reporting period. On the current year cost report, the hospital would enter 75.62 on line 12 of Worksheet E–4 (prior year FTE count). If the total capped DGME FTE count in the penultimate cost reporting period was 302, and the penultimate year was also 12 months, then the prorated FTE count for the penultimate year would be: [(302/365) × (92)] = 76.12. On the current year cost report, the hospital would enter 76.12 on line 13 of Worksheet E–4 (penultimate year FTE count). For reasons similar to those discussed We note that in this scenario, if either previously, no adjustments need to be made to the prior and penultimate years when calculating the rolling average IME count. However, if the current, prior and/or penultimate year cost reporting periods are of different the prior or penultimate year cost reporting period was also other than 12 months in length, then it would be necessary to adjust the calculation to account for that difference. For instance, suppose that the hospital’s penultimate year cost reporting period was 9 months or 273 days long, and its capped DGME FTE count during that period (prorated on a 12-month basis as described earlier in this preamble) wa ospital’s penultimate year cost reporting period was 9 months or 273 days long, and its capped DGME FTE count during that period (prorated on a 12-month basis as described earlier in this preamble) was 225. In this case, rather than dividing by 365 days, the hospital would divide the penultimate- year DGME FTE count by 273 days, as follows: [(225/273) × (92)] = 75.82 FTEs. Thus, the hospital would enter 75.82 on line 13 of Worksheet E–4 of the current year cost report. Conversely, if the current year is a full cost reporting period, but the prior and/ or penultimate cost reporting period was other than 12 months, then the prior and/or penultimate year DGME FTE counts (which have been prorated on a 12-month basis as described earlier in this preamble) must be annualized to yield 12-month equivalents. This procedure avoids understatement (or overstatement) of the DGME FTE count in the current year and, similar to the proration of DGME counts in the preceding scenario, results in 3 years of comparable FTE counts from which to calculate the DGME rolling average: For the prior year, take the FTE count that would be reported on Worksheet E– 4, line 12, and divide by the number of days in of comparable FTE counts from which to calculate the DGME rolling average: For the prior year, take the FTE count that would be reported on Worksheet E– 4, line 12, and divide by the number of days in the non-12-month cost reporting period, and then multiply that quotient by 365 (or 366, if the current cost reporting period includes February 29). Report this annualized FTE count on Worksheet E–4, line 12 of, the current year cost report. For the penultimate year, take the FTE count that would be reported on Worksheet E–4, line 13, and divide by the number of days in the non-12-month cost reporting period, and then multiply that quotient by 365 (or 366, if the current cost reporting period includes February 29). Report this annualized FTE count on Worksheet E–4, line 13 of the current year cost report. Stated formulaically: Annualized DGME FTE count = [(Prorated DGME FTE count/ Number of days in the non-12- month cost reporting period) × (365 or 366)] For example, if the current year cost reporting period is 12 months (365 days), while the prior year cost reporting period was 3 months (92 days), and the prior-year capped DGME FTE count (prorated on a 12-month basis) was 75, then the st reporting period is 12 months (365 days), while the prior year cost reporting period was 3 months (92 days), and the prior-year capped DGME FTE count (prorated on a 12-month basis) was 75, then the annualized FTE count for the prior year would be: [(75/ 92) × (365)] = 297.55. On the current year cost report, the hospital would enter 297.55 on line 12 of Worksheet E– 4 (prior year FTE count). Comment: Commenters expressed support for our proposed clarification of VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00383 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36918 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations the policy for determining the DGME and IME FTE resident counts for 12- month and non-12-month cost reporting periods. Response: We thank the commenters for their support. As noted previously, we did not propose any changes to our existing FTE counting policies. Accordingly, we are finalizing our proposed clarification with no change to the regulations at 42 CFR 412.105 or §§ 413.75 through 81. G. Reasonable Cost Payment for Nursing and Allied Health Educ es. Accordingly, we are finalizing our proposed clarification with no change to the regulations at 42 CFR 412.105 or §§ 413.75 through 81. G. Reasonable Cost Payment for Nursing and Allied Health Education Programs (§ 413.85 and § 413.87) 1. General Under section 1861(v) of the Act, Medicare has historically paid providers for Medicare’s share of the costs that providers incur in connection with approved educational activities. The costs of these activities are excluded from the definition of ‘‘inpatient hospital operating costs’’ and are not included in the calculation of payment rates for hospitals or hospital units paid under the IPPS, IRF PPS, or IPF PPS, and are excluded from the rate-of- increase ceiling for certain facilities not paid on a PPS. These costs are separately identified and ‘‘passed through’’ (that is, paid separately on a reasonable cost basis). Under the existing regulations at 42 CFR 413.85, approved nursing and allied health (NAH) education programs must meet State licensure requirements or be accredited by a recognized national professional organization. Additionally, an approved NAH education program must be operated by a provider. The most recent substanti te licensure requirements or be accredited by a recognized national professional organization. Additionally, an approved NAH education program must be operated by a provider. The most recent substantive rulemakings on these regulations were in the January 12, 2001, final rule (66 FR 3358 through 3374), and in the August 1, 2003, final rule (68 FR 45423 and 45434). The regulations regarding Medicare Advantage (MA) add-on payments for NAH education programs are at 42 CFR 413.87. 2. Medicare Advantage Nursing and Allied Health Education Payments Section 541 of the Balanced Budget Refinement Act (BBRA) of 1999 provides for additional payments to hospitals for costs of nursing and allied health education associated with services to Medicare+Choice (now called Medicare Advantage (MA)) 163 enrollees. Hospitals that operate approved nursing or allied health 163 The M+C program in Part C of Medicare was renamed the Medicare Advantage (MA) Program under the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA), which was enacted in December 2003. education programs and receive Medicare reasonable cost reimbursement for these programs may receive additional payments to t, and Modernization Act of 2003 (MMA), which was enacted in December 2003. education programs and receive Medicare reasonable cost reimbursement for these programs may receive additional payments to account for MA enrollees. Section 541 of the BBRA limits total spending under the provision for MA enrollees to no more than $60 million in any calendar year (CY). (In this document, we refer to the total amount of $60 million or less as the payment ‘‘pool’’.) Section 541 of the BBRA also provides that direct graduate medical education (GME) payments for Medicare+Choice (now MA) utilization be reduced to the extent that these additional payments are made for nursing and allied health education programs. This provision was effective for portions of cost reporting periods occurring in a calendar year, on or after January 1, 2000. Section 512 of the Benefits Improvement and Protection Act (BIPA) of 2000 changed the formula for determining the additional amounts to be paid to hospitals for Medicare+Choice (now MA) nursing and allied health costs. Under section 541 of the BBRA, the additional payment amount was determined based on the proportion of each individual hospital’s nursing and all icare+Choice (now MA) nursing and allied health costs. Under section 541 of the BBRA, the additional payment amount was determined based on the proportion of each individual hospital’s nursing and allied health education payment to total nursing and allied health education payments made to all hospitals. However, this formula did not account for a hospital’s specific Medicare+Choice (now MA) utilization. Section 512 of the BIPA revised this payment formula to specifically account for each hospital’s Medicare+Choice (now MA) utilization. This provision was effective for portions of cost reporting periods occurring in a calendar year, beginning with CY 2001. The regulations at 42 CFR 413.87 implement both statutory provisions. We first implemented the BBRA NAH Medicare+Choice (now MA) provision in the August 1, 2000, IPPS interim final rule with comment period (IFC) (65 FR 47036 through 47039), and subsequently implemented the BIPA provision in the August 1, 2001 IPPS final rule (66 FR 39909 and 39910). In those rules, we outlined the qualifying conditions for a hospital to receive the NAH Medicare+Choice (now MA) payment, how we would calculate the NAH Medicare+Choice (now MA) payme 9909 and 39910). In those rules, we outlined the qualifying conditions for a hospital to receive the NAH Medicare+Choice (now MA) payment, how we would calculate the NAH Medicare+Choice (now MA) payment pool, and how a qualifying hospital would calculate its ‘‘share’’ of payment from that pool. Determining a hospital’s NAH MA payment essentially involves applying a ratio of the hospital-specific NAH Part A payments, total inpatient days, and MA inpatient days, to national totals of those same variables, from cost reporting periods ending in the fiscal year that is 2 years prior to the current calendar year. The formula is as follows: (((Hospital NAH pass-through payment/ Hospital Part A Inpatient Days) *(Hospital MA Inpatient Days)) divided by ((National NAH pass-through payment/ National Part A Inpatient Days) * (National MA Inpatient Days))) * Current Year Payment Pool. With regard to determining the total national amounts for NAH pass-through payment, Part A inpatient days, and MA inpatient days, we note that section 1886(l) of the Act, as added by section 541 of the BBRA, gives the Secretary the discretion to ‘‘estimate’’ the national components of the formula noted previously. npatient days, we note that section 1886(l) of the Act, as added by section 541 of the BBRA, gives the Secretary the discretion to ‘‘estimate’’ the national components of the formula noted previously. For example, section 1886(l)(2)(A) of the Act states that the Secretary shall estimate the ratio of payments for all hospitals for portions of cost reporting periods occurring in the year under section 1886(h)(3)(D) of the Act to total direct GME payments estimated for the same portions of periods under section 1886(h)(3) of the Act. Accordingly, we stated in the August 1, 2000, IFC (65 FR 47038) that each year, we would determine and publish in a final rule the total amount of nursing and allied health education payments made across all hospitals during the fiscal year 2 years prior to the current calendar year. We would use the best available cost reporting data for the applicable hospitals from the Hospital Cost Report Information System (HCRIS) for cost reporting periods in the fiscal year that is 2 years prior to the current calendar year. To calculate the pool, in accordance with section 1886(l) of the Act, we stated that we would ‘‘estimate’’ a total amount for each calendar ye year that is 2 years prior to the current calendar year. To calculate the pool, in accordance with section 1886(l) of the Act, we stated that we would ‘‘estimate’’ a total amount for each calendar year, not to exceed $60 million (65 FR 47038). To calculate the proportional reduction to Medicare+Choice (now MA) direct GME payments, we stated that the percentage is estimated by calculating the ratio of the Medicare+Choice nursing and allied health payment ‘‘pool’’ for the current calendar year to the projected total Medicare+Choice direct GME payments made across all hospitals for the current calendar year. We stated that the projections of Medicare+Choice direct GME and Part A direct GME payments are based on the best available cost report data from the HCRIS (for example, for CY 2000, the projections are based on the best available cost report data from FY 1998 HCRIS), and these payment amounts are increased using the increases allowed by section 1886(h) of the Act for these services (using the percentage applicable for the VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00384 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D (using the percentage applicable for the VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00384 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36919 current calendar year for Medicare+Choice direct GME and the Consumer Price Index (CPI–U) increases for Part A direct GME). We also stated that we would publish the applicable percentage reduction each year in the IPPS proposed and final rules (65 FR 47038). Thus, in the August 1, 2000, IFC, we described our policy regarding the timing and source of the national data components for the NAH Medicare+Choice (now MA) add-on payment and the percent reduction to the direct GME Medicare+Choice payments, and we stated that we would publish the rates for each calendar year in the IPPS proposed and final rules. While the rates for CY 2000 were published in the August 1, 2000, IFC (see 65 FR 47038 and 47039), the rates for subsequent CYs were only issued through Change Requests (CRs) (CR 2692, CR 11642, CR 12407). After recent issuance of the CY 2019 rates in CR 12407 on August 19, 202 FR 47038 and 47039), the rates for subsequent CYs were only issued through Change Requests (CRs) (CR 2692, CR 11642, CR 12407). After recent issuance of the CY 2019 rates in CR 12407 on August 19, 2021, we reviewed our update procedures, and were reminded that the August 1, 2000, IFC states that we would publish the NAH Medicare+Choice (now MA) rates and direct GME percent reduction every year in the IPPS rules. Accordingly, for CY 2020 and CY 2021, we proposed and finalized the NAH MA add-on rates in the FY 2023 IPPS/LTCH PPS proposed and final rules. We stated that for CYs 2022 and after, we would similarly propose and finalize the respective NAH MA rates and direct GME percent reductions in subsequent IPPS/LTCH PPS rulemakings (see 87 FR 49073, August 10, 2022). In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18278 through 18280), we proposed the rates for CY 2024. Consistent with the use of HCRIS data for past calendar years, we proposed to use data from cost reports ending in FY 2022 HCRIS (the fiscal year that is 2 years prior to CY 2024) to compile these national amounts: NAH pass-through payment, Part A Inpatient Days, MA Inpatient Days. For the proposed rule, we accessed 2022 HCRIS (the fiscal year that is 2 years prior to CY 2024) to compile these national amounts: NAH pass-through payment, Part A Inpatient Days, MA Inpatient Days. For the proposed rule, we accessed the FY 2022 HCRIS data from the fourth quarterly HCRIS update of 2024. However, to calculate the ‘‘pool’’ and the direct GME MA percent reduction, we ‘‘projected’’ Part A direct GME payments and MA direct GME payments for the current calendar year, which in the proposed rule and in this final rule is CY 2024, based on the ‘‘best available cost report data from the HCRIS’’ (65 FR 47038). Next, consistent with the method we described previously in the August 1, 2000, IFC, we increased these payment amounts from midpoint to midpoint of the appropriate calendar year using the increases allowed by section 1886(h) of the Act for these services (using the percentage applicable for the current calendar year for MA direct GME, and the Consumer Price Index-Urban (CPI–U) increases for Part A direct GME). For CY 2024, the direct GME projections are based on the fourth quarterly update of CY 2022 HCRIS, adjusted for the CPI–U and for increasing MA enrollment. For CY 2024, the proposed national rat GME). For CY 2024, the direct GME projections are based on the fourth quarterly update of CY 2022 HCRIS, adjusted for the CPI–U and for increasing MA enrollment. For CY 2024, the proposed national rates and percentages, and their data sources, are set forth in this table. We stated in the proposed rule that we intended to update these numbers in the FY 2026 final rule based on the latest available cost report data. Comment: We received a few comments in support of our proposed calculation of the NAH MA payment rates for CY 2024. Response: We thank the commenters for their support. For this final rule, consistent with the use of HCRIS data for past calendar years, for CY 2024, we use data from cost reports ending in FY 2022 HCRIS (the fiscal year that is 2 years prior to CY 2024) to compile these national amounts: NAH pass-through payment, Part A Inpatient Days, and MA Inpatient Days. For this final rule, we accessed the HCRIS data from the first quarterly update of 2025. However, to calculate the ‘‘pool’’ and the direct GME MA percent reduction, we ‘‘project’’ Part A direct GME payments and MA direct GME payments for the current calendar year, which in this final rule in CY 2024, b lculate the ‘‘pool’’ and the direct GME MA percent reduction, we ‘‘project’’ Part A direct GME payments and MA direct GME payments for the current calendar year, which in this final rule in CY 2024, based on the best available cost report data. Next, consistent with the method we described previously from the August 1, 2000 IFC, we increase these payment amounts from midpoint to midpoint of the appropriate calendar year using the increases allowed by section 1886(h) of the Act for these services (using the percentage applicable for the current calendar year for MA direct GME, and the Consumer Price Index-Urban (CPI–U) increases for Part A direct GME). For CY 2024, the direct GME projections are based on the first quarterly update of CY 2022 HCRIS, adjusted for the CPI–U and for increasing MA enrollment. For CY 2024, the final national rates and percentages, and their data sources, are set forth in this table. 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00385 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00386 Fmt 4701 Sfmt 4700 E:\FR\FM ep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00385 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00386 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36921 Worksheet B, Part I. According to the providers, the regulations require that indirect costs be included as part of a provider’s total allowable educational costs before tuition and student fees are offset, and the change to the cost reporting instructions in 2017 was a change in policy that conflicts with the regulations. The U.S. District Court for D.C. sided with the providers, arguing that the plain reading of the regulations text at 42 CFR 413.85(d)(2)(i) is consistent with the providers’ interpretation of the order of operations, which is to allow direct and indirect costs to be summed, and tuition and fees to be subtracted from that sum. In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18280 through 18282), we stated that we disagree with the Court’s ruling and asserted that the cost report instructions o be subtracted from that sum. In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18280 through 18282), we stated that we disagree with the Court’s ruling and asserted that the cost report instructions at PRM 15–2 sec. 4016 are clear that revenue that is a recovery of expenses should be offset via Worksheet A–8, prior to the allocation of indirect costs, and that these instructions are consistent with the regulations and Medicare cost reporting policy broadly. Nevertheless, to further clarify the regulations, we proposed to change the regulations text at 42 CFR 413.85(d)(2)(i) to state that the net cost of approved educational activities is determined as follows: • Determine allowable direct costs incurred by the provider for trainee stipends and compensation of teachers employed by the provider. • Subtract from allowable direct costs the revenues the provider receives from students or on behalf of students enrolled in the program, such as, but not limited to, tuition, student fees, or textbooks purchased for resale. • Add indirect costs of the activities as determined under the Medicare cost- finding principles in 42 CFR 413.24, but limited to indirect costs that the provider itsel textbooks purchased for resale. • Add indirect costs of the activities as determined under the Medicare cost- finding principles in 42 CFR 413.24, but limited to indirect costs that the provider itself incurs as a consequence of operating the approved educational activities. We noted that as a result of this proposal, we would be modifying and moving the first sentence of existing 42 CFR 413.85(d)(2)(ii), which defines a provider’s total allowable educational costs as those costs incurred by the provider for trainee stipends, compensation of teachers, and other costs of the activities as determined under the Medicare cost-finding principles in § 413.24, up to proposed 42 CFR 413.85(d)(2)(i). However, we did not propose to revise the portion of existing regulations text at 42 CFR 413.85(d)(2)(ii) which states that the direct and indirect allowable costs of educational activities do not include patient care costs, costs incurred by a related organization, or costs that constitute a redistribution of costs from an educational institution to a provider or costs that have been or are currently being provided through community support. The effective date of this proposed regulatory chang tribution of costs from an educational institution to a provider or costs that have been or are currently being provided through community support. The effective date of this proposed regulatory change would have been cost reporting periods beginning on or after October 1, 2025. We received many comments in opposition to our proposal to determine the net cost of approved nursing and allied health education programs by deducting tuition and other revenue from direct costs prior to the allocation of indirect costs. Commenters objected that the proposed policy is inconsistent with general cost-finding principles and would result in the NAH cost centers receiving less than their share of institutional overhead. We thank the commenters for their feedback. Due to the number and nature of the comments that we received, and after further consideration of this issue, we have decided not to finalize changes to our existing policy in this final rule. We expect to revisit the treatment of NAH education costs in future rulemaking and we encourage interested parties to submit comments on any proposed policy changes at that time. H. Payment Adjustment for Certain Immunotherapy Cases (§§ 412.85 an ation costs in future rulemaking and we encourage interested parties to submit comments on any proposed policy changes at that time. H. Payment Adjustment for Certain Immunotherapy Cases (§§ 412.85 and 412.312) Effective for FY 2021, we created MS– DRG 018 for cases that include procedures describing CAR T-cell therapies, which were reported using ICD–10–PCS procedure codes XW033C3 or XW043C3 (85 FR 58599 through 58600). Effective for FY 2022, we revised MS–DRG 018 to include cases that report the procedure codes for CAR T-cell and non-CAR T-cell therapies and other immunotherapies (86 FR 44798 through 448106). Effective for FY 2021, we modified our relative weight methodology for MS–DRG 018 to develop a relative weight that is reflective of the typical costs of providing CAR T-cell therapies relative to other IPPS services. Specifically, under our finalized policy we do not include claims determined to be clinical trial claims that group to MS–DRG 018 when calculating the average cost for MS–DRG 018 that is used to calculate the relative weight for this MS–DRG, with the additional refinements that: (a) when the CAR T- cell therapy product is purchased in the usual manner, but the for MS–DRG 018 that is used to calculate the relative weight for this MS–DRG, with the additional refinements that: (a) when the CAR T- cell therapy product is purchased in the usual manner, but the case involves a clinical trial of a different product, the claim will be included when calculating the average cost for MS DRG 018 to the extent such claims can be identified in the historical data; and (b) when there is expanded access use of immunotherapy, these cases will not be included when calculating the average cost for MS–DRG 018 to the extent such claims can be identified in the historical data (85 FR 58600). The term ‘‘expanded access’’ (sometimes called ‘‘compassionate use’’) is a potential pathway for a patient with a serious or immediately life-threatening disease or condition to gain access to an investigational medical product (drug, biologic, or medical device) for treatment outside of clinical trials when, among other criteria, there is no comparable or satisfactory alternative therapy to diagnose, monitor, or treat the disease or condition (21 CFR 312.305).164 Effective FY 2021, we also finalized an adjustment to the payment amount for applicable clinical trial and e native therapy to diagnose, monitor, or treat the disease or condition (21 CFR 312.305).164 Effective FY 2021, we also finalized an adjustment to the payment amount for applicable clinical trial and expanded access immunotherapy cases that group to MS–DRG 018 using the same methodology that we used to adjust the case count for purposes of the relative weight calculations (85 FR 58842 through 58844). (As previously noted, effective beginning FY 2022, we revised MS–DRG 018 to include cases that report the procedure codes for CAR T-cell and non-CAR T-cell therapies and other immunotherapies (86 FR 44798 through 448106).) Specifically, under our finalized policy we apply a payment adjustment to claims that group to MS– DRG 018 and include ICD–10–CM diagnosis code Z00.6, with the modification that when the CAR T-cell, non-CAR T-cell, or other immunotherapy product is purchased in the usual manner, but the case involves a clinical trial of a different product, the payment adjustment will not be applied in calculating the payment for the case. We also finalized that when there is expanded access use of immunotherapy, the payment adjustment will be applied in calculating the payment for th be applied in calculating the payment for the case. We also finalized that when there is expanded access use of immunotherapy, the payment adjustment will be applied in calculating the payment for the case. This payment adjustment is codified at 42 CFR 412.85 (for operating IPPS payments) and 412.312 (for capital IPPS payments), for claims appropriately containing Z00.6, as described previously, and reflects that the adjustment is also applied for cases involving expanded access use immunotherapy, and that the payment adjustment only applies to applicable clinical trial cases; that is, the adjustment is not applicable to cases where the CAR T-cell, non-CAR T-cell, or other immunotherapy product is 164 https://www.fda.gov/news-events/expanded- access/expanded-access-keywords-definitions-and- resources. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00387 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36922 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations purchased in the usual manner, but the case involves a clinical trial of a different product. The regulations at 42 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations purchased in the usual manner, but the case involves a clinical trial of a different product. The regulations at 42 CFR 412.85(c) also specify that the adjustment factor will reflect the average cost for cases to be assigned to MS–DRG 018 that involve expanded access use of immunotherapy or are part of an applicable clinical trial to the average cost for cases to be assigned to MS–DRG 018 that do not involve expanded access use of immunotherapy and are not part of a clinical trial (85 FR 58844). For FY 2026, we proposed to continue to apply an adjustment to the payment amount for expanded access use of immunotherapy and applicable clinical trial cases that group to MS–DRG 018, calculated using the same methodology, as modified in the FY 2024 IPPS/LTCH PPS final rule (88 FR 59062), that we proposed to use to adjust the case count for purposes of the relative weight calculations, including our proposed modifications to that methodology for FY 2026, as described in section II.D. of the preamble of this final rule. As discussed in the FY 2024 IPPS/ LTCH PPS final rule, the MedPAR claims data now includ odifications to that methodology for FY 2026, as described in section II.D. of the preamble of this final rule. As discussed in the FY 2024 IPPS/ LTCH PPS final rule, the MedPAR claims data now includes a field that identifies whether or not the claim includes expanded access use of immunotherapy. For the FY 2023 MedPAR data and for subsequent years, this field identifies whether or not the claim includes condition code 90. The MedPAR files now also include information for claims with the payer- only condition code ‘‘ZC’’, which is used by the IPPS Pricer to identify a case where the CAR T-cell, non-CAR T- cell, or other immunotherapy product is purchased in the usual manner, but the case involves a clinical trial of a different product so that the payment adjustment is not applied in calculating the payment for the case (for example, see Change Request 11879, available at https://www.cms.gov/files/document/ r10571cp.pdf). We refer the readers to section II.D. of this final rule for further discussion of our methodology for identifying clinical trial claims and expanded access use claims in MS–DRG 018 and our methodology used to adjust the case count for purposes of the relative we rther discussion of our methodology for identifying clinical trial claims and expanded access use claims in MS–DRG 018 and our methodology used to adjust the case count for purposes of the relative weight calculations, as modified in the FY 2024 IPPS/LTCH PPS final rule, and as further proposed to be modified for FY 2026 to identify other claims for which the immunotherapy product was not purchased in the usual manner, such as obtained at no cost. In the FY 2025 IPPS/LTCH PPS final rule, we summarized a comment requesting that CMS establish a mechanism for hospitals to report when a product is not purchased in the usual manner, such as obtained at no cost, for reasons other than participation in a clinical trial or expanded access use (89 FR 69112). We indicated we may consider this request in future rulemaking. We agree that the same adjustment that applies to expanded access use of immunotherapy and applicable clinical trial cases should apply to other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, and therefore proposed that, beginning in FY 2026, the payment adjustment would also be applied in calculating the payment for roduct is not purchased in the usual manner, such as obtained at no cost, and therefore proposed that, beginning in FY 2026, the payment adjustment would also be applied in calculating the payment for such cases. We intend to issue billing instructions in separate guidance that would allow a provider to indicate, for that case, that the immunotherapy product was not purchased in the usual manner so that MACs would apply the same adjustment to the payment amount that is applied for expanded access use of immunotherapy and applicable clinical trial cases that group to MS– DRG 018. We also proposed to modify our regulations at 42 CFR 412.85 (for operating IPPS payments) and 412.312 (for capital IPPS payments) to codify this proposed payment adjustment for other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost. Specifically, we proposed to modify the section heading and paragraphs (b) and (c) at 42 CFR 412.85 to include other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, and to make additional technical revisions to paragraph (c). We also proposed to modify paragraph (f) at re the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, and to make additional technical revisions to paragraph (c). We also proposed to modify paragraph (f) at 42 CFR 412.312 to include cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost. We also refer readers to section II.D. of the preamble of this final rule for further discussion of our proposed and finalized changes to our methodology for calculating the relative weight for MS–DRG 018 to identify other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost and to adjust the case count for purposes of the relative weight calculations. Using the same methodology that we proposed to use to adjust the case count for purposes of the relative weight calculations, including our proposed modifications as discussed in section II.D. of the preamble of this final rule, we proposed to calculate the adjustment to the payment amount for expanded access use of immunotherapy, applicable clinical trial cases, and other cases where the immunotherapy product is not purchased in the usual manner, such as ob stment to the payment amount for expanded access use of immunotherapy, applicable clinical trial cases, and other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost as follows: • Calculate the average cost for cases assigned to MS–DRG 018 that (a) contain ICD–10–CM diagnosis code Z00.6 and do not contain condition code ‘‘ZC’’, (b) contain condition code ‘‘90’’, or (c) contain standardized drug charges below the median standardized drug charge of clinical trial cases in MS–DRG 018. • Calculate the average cost for all other cases assigned to MS–DRG 018. • Calculate an adjustor by dividing the average cost calculated in step 1 by the average cost calculated in step 2. • Apply this adjustor when calculating payments for expanded access use of immunotherapy, applicable clinical trial cases, and other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, that group to MS–DRG 018 by multiplying the relative weight for MS– DRG 018 by the adjustor. We refer the readers to section II.D. of the preamble of this final rule for further discussion of our methodology. Consistent with our calcu lying the relative weight for MS– DRG 018 by the adjustor. We refer the readers to section II.D. of the preamble of this final rule for further discussion of our methodology. Consistent with our calculation of the proposed adjustor for the relative weight calculations, for the proposed rule we proposed to calculate this adjustor based on the December 2024 update of the FY 2024 MedPAR file for purposes of establishing the FY 2026 payment amount. Specifically, in accordance with proposed revised 42 CFR 412.85 (for operating IPPS payments) and 412.312 (for capital IPPS payments), we proposed to multiply the FY 2026 relative weight for MS–DRG 018 by a proposed adjustor of 0.23 as part of the calculation of the payment for claims determined to be applicable clinical trial claims, expanded access use immunotherapy claims, or other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, that group to MS–DRG 018, which includes CAR T- cell and non-CAR T-cell therapies and other immunotherapies. We also proposed to update the value of the adjustor based on more recent data for the final rule. We did not receive any comments specifically relat on-CAR T-cell therapies and other immunotherapies. We also proposed to update the value of the adjustor based on more recent data for the final rule. We did not receive any comments specifically relating to the proposed payment adjustment for applicable clinical trial cases, expanded access use immunotherapy cases, and other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, and are therefore finalizing our proposal without modification. We are also finalizing our proposed modifications to our regulations at 42 CFR 412.85 and VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00388 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36923 412.312 to codify this payment adjustment for other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, without modification. We are also finalizing our proposal to update the value of this adjustor based on more recent data for this final rule. Therefore, using the March 2025 update of th d at no cost, without modification. We are also finalizing our proposal to update the value of this adjustor based on more recent data for this final rule. Therefore, using the March 2025 update of the FY 2024 MedPAR data, we are finalizing an adjustor of 0.16 for FY 2026, which will be multiplied by the final FY 2026 relative weight for MS–DRG 018 as part of the calculation of the payment for claims determined to be applicable clinical trial cases, expanded use access immunotherapy claims, and other cases where the immunotherapy product is not purchased in the usual manner, such as obtained at no cost, that group to MS–DRG 018. K. Hospital Readmissions Reduction Program Updates and Changes 1. Regulatory Background Section 1886(q) of the Act sets forth the requirements of the Hospital Readmissions Reduction Program effective for discharges from applicable hospitals beginning on or after October 1, 2012. Under the Hospital Readmissions Reduction Program, payments to applicable hospitals must be reduced to account for certain excess readmissions. We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through 49543) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38221 must be reduced to account for certain excess readmissions. We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through 49543) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38221 through 38240) for a general overview of the Hospital Readmissions Reduction Program. We also refer readers to 42 CFR 412.152 through 412.154 for codified Hospital Readmissions Reduction Program requirements. 2. Hospital Readmissions Reduction Program Measures a. Integration of Medicare Advantage (MA) Beneficiaries Into the Cohorts of the Hospital Readmissions Reduction Program Measure Set Beginning With the FY 2027 Program Year (1) Background In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18283 through 18286), we proposed to adopt substantive updates to the Hospital 30- Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Acute Myocardial Infarction (AMI) Hospitalization; Hospital 30-Day, All- Cause, RSRR Following Heart Failure (HF) Hospitalization; Hospital 30-Day, All-Cause, RSRR Following Pneumonia (PN) Hospitalization; Hospital-Level, 30- Day, All-Cause, RSRR Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization; Hospital 30- Day, All-Cause, RSR -Cause, RSRR Following Pneumonia (PN) Hospitalization; Hospital-Level, 30- Day, All-Cause, RSRR Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization; Hospital 30- Day, All-Cause, RSRR Following Total Hip Arthroplasty (THA) and Total Knee Arthroplasty (TKA) Hospitalization; and Hospital 30-Day, All-Cause, RSRR Following Coronary Artery Bypass Graft (CABG) Surgery measures, hereinafter referred to as the Hospital Readmissions Reduction Program measure set, beginning with the FY 2027 Program Year. The proposed updates to the Hospital Readmissions Reduction Program measure set would include integrating MA beneficiaries into each measure’s cohorts and reducing the applicable period from a three-year period to a two-year period. In addition, we proposed to make a non-substantive modification; we would update the risk adjustment model to use individual International Classification of Diseases (ICD)–10 codes instead of Hierarchical Condition Categories (HCCs). For the purposes of describing the substantive change of the Hospital Readmissions Reduction Program measure set, we note that ‘‘cohort’’ is defined as the hospitalizations, or ‘‘index admissions,’’ that are include s of describing the substantive change of the Hospital Readmissions Reduction Program measure set, we note that ‘‘cohort’’ is defined as the hospitalizations, or ‘‘index admissions,’’ that are included when calculating each measure. This cohort is the set of hospitalizations that meet all the inclusion and exclusion criteria. For measure cohort details of the most recent versions of the Hospital Readmissions Reduction Program measure set, we refer readers to the measure methodology report and measure risk adjustment statistical model on our website at: https:// qualitynet.cms.gov/inpatient/measures/ readmission/methodology. Including MA beneficiaries in hospital outcome measures would help ensure that hospital quality would be measured across all Medicare beneficiaries and not just the Fee-For- Service (FFS) population. In 2024, 50 percent of eligible Medicare beneficiaries—or 34.3 million people— were covered by MA plans.165 It is projected that nearly two-thirds of all Medicare enrollees will be enrolled in MA plans by 2030.166 Consequently, using FFS-only beneficiaries may exclude a large segment of the focus population for quality measurement. Additionally, studies comparing re lees will be enrolled in MA plans by 2030.166 Consequently, using FFS-only beneficiaries may exclude a large segment of the focus population for quality measurement. Additionally, studies comparing readmission rates between MA and FFS- 165 Centers for Medicaid & Medicare Services. Medicare Enrollment for September 2024 (Accessed on February 5, 2025). Available at: https:// data.cms.gov/tools/medicare-enrollment- dashboard. 166 Hale J, Hong N, Hopkins B, et al. (2024) Health Insurance Coverage Projections for the US Population and Sources of Coverage, by Age, 2024– 34. Health Affairs. 43(7); 922–932. https://doi.org/ 10.1377/hlthaff.2024.00460. only have shown mixed results. While several studies report lower readmissions for MA enrollees,167 168 others have found no difference or even higher risk-adjusted readmission rates for certain conditions.169 170 Due to these differing research study conclusions, adding the MA cohort to the Hospital Readmissions Reduction Program measures would allow for a more robust and holistic view of quality of care provided to all Medicare beneficiaries.171 Most importantly, the FFS and MA data in our hospital outcome measures would empower patients an allow for a more robust and holistic view of quality of care provided to all Medicare beneficiaries.171 Most importantly, the FFS and MA data in our hospital outcome measures would empower patients and caregivers to make informed decisions about their healthcare by giving them additional comparative data on hospitals. (2) Overview of Measure Updates We refer readers to the CMS Measures Inventory Tool and Hospital Readmissions Reduction Program readmission measures specification manuals for more information on the Hospital Readmissions Reduction Program measure set, including background on each measure and a complete summary of measure specifications.172 173 We proposed to adopt updates to the Hospital Readmissions Reduction Program measure set in the Hospital Readmissions Reduction Program beginning with the FY 2027 program year. The newly refined versions of the Hospital Readmissions Reduction 167 Jacobs PD, Basu J. Medicare Advantage and Post discharge Quality: Evidence From Hospital Readmissions. American Journal of Managed Care, 2020;26(12):524–529. Available at: https:// www.ajmc.com/view/medicare-advantage-and- postdischarge-quality-evidence-from-hospital- readmissions. 168 H Readmissions. American Journal of Managed Care, 2020;26(12):524–529. Available at: https:// www.ajmc.com/view/medicare-advantage-and- postdischarge-quality-evidence-from-hospital- readmissions. 168 Huckfeldt PJ, Escarce JJ, Rabideau B, et al. Less Intense Postacute Care, Better Outcomes for Enrollees in Medicare Advantage Than Those in Fee-For-Service. Health Affairs. 2017;26(1):91–100. https://doi.org/10.1377/hlthaff.2016.1027. 169 Yayac MF, Harrer SL, Janiec DA, et al. Costs and Outcomes of Medicare Advantage and Traditional Medicare Beneficiaries After Total Hip and Knee Arthroplasty. Journal of American Academy of Orthopedic Surgeons. 2020;28(20):e910-e916. https://doi.org/10.5435/ JAAOS-D-19-00609. 170 Henke RM, Karaca Z, Gibson TB, et al. Medicare Advantage and Traditional Medicare Hospitalization Intensity and Readmissions. Medical Care Research and Review. 2018;75(4):434– 453. https://doi.org/10.1177%2F107755 8717692103. 171 Panagiotou OA, Kumar A, Gutman R, et al. Hospital Readmission Rates in Medicare Advantage and Traditional Medicare: A Retrospective Population-Based Analysis. Annals of Internal Medicine. 2019;171(2):99–106. https://doi.org/ 10.7326/M18-1795. 172 CMS M admission Rates in Medicare Advantage and Traditional Medicare: A Retrospective Population-Based Analysis. Annals of Internal Medicine. 2019;171(2):99–106. https://doi.org/ 10.7326/M18-1795. 172 CMS Measures Inventory Tool. Available at: https://cmit.cms.gov/cmit/#. 173 CMS Quality Net. Available at: https:// qualitynet.cms.gov/inpatient/measures/ readmission/methodology. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00389 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36924 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations Program measure set would expand the measures’ inclusion criteria to include MA beneficiaries. Currently, the measure denominator for the Hospital Readmissions Reduction Program measure set includes beneficiaries ‘‘Enrolled in Medicare FFS Part A and Part B for the first 12 months prior to the date of admission and enrolled in Part A during the index admission.’’ 174 We proposed to modify the measure cohort to ‘‘Enrolled in Medicare FFS and/or MA for the 12 months prior to the date of admission; and enrolled in FFS or MA during the index admission. dmission.’’ 174 We proposed to modify the measure cohort to ‘‘Enrolled in Medicare FFS and/or MA for the 12 months prior to the date of admission; and enrolled in FFS or MA during the index admission.’’ 175 The addition of MA data to the measure doubles the cohort size and more accurately reflects the quality of care for both FFS and MA beneficiaries. We are also providing a non- substantive update which would re- specify the risk model for each measure to primarily use individual ICD–10 codes, leveraging the specificity of individual ICD–10 coding in place of the previously used HCCs. This technical update would improve the performance of the risk adjustment models for condition- and procedure- specific mortality and complication measures.176 We refer readers to QualityNet for more on the list of ICD– 10 codes used in the risk adjustment model, available at: https:// qualitynet.cms.gov/inpatient/measures/ readmission/resources.177 (3) Pre-Rulemaking Process and Measure Endorsement (a) Recommendation From the PRMR Process We refer readers to the FY 2025 IPPS/ LTCH PPS final rule (89 FR 69457 through 69458) for details on the Pre- Rulemaking Measure Review (PRMR) process, including Recommendation From the PRMR Process We refer readers to the FY 2025 IPPS/ LTCH PPS final rule (89 FR 69457 through 69458) for details on the Pre- Rulemaking Measure Review (PRMR) process, including the voting procedures that the PRMR process uses to reach consensus on measure recommendations. The PRMR Hospital Committee, comprised of the PRMR 174 CMS Measures Inventory Tool. Available at: https://cmit.cms.gov/cmit/#. 175 2024 Measures Under Consideration List. Available at: https://mmshub.cms.gov/2024/2024- 11/2024-measures-under-consideration-list-now- available. 176 Krumholz HM, Coppi AC, Warner F, et al. Comparative effectiveness of new approaches to improve mortality risk models from Medicare claims data. JAMA Network Open. 2019;2(7):e197314–e197314 Available at: https:// pmc.ncbi.nlm.nih.gov/articles/PMC6647547/. 177 In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18284), we referred readers to the CMS Measures Management System, available at: https:// mmshub.cms.gov/measure-lifecycle/measure- implementation/pre-rulemaking/lists-and-reports/ 2024-MUC-List-materials for the list of ICD–10 codes used. Subsequently, we issued a correction notice, available at 90 FR 23867. Hos ifecycle/measure- implementation/pre-rulemaking/lists-and-reports/ 2024-MUC-List-materials for the list of ICD–10 codes used. Subsequently, we issued a correction notice, available at 90 FR 23867. Hospital Advisory Group and PRMR Hospital Recommendation Group, reviewed the proposed updated versions of the Hospital Readmissions Reduction Program measure set. Consensus is reached when there is 75 percent or higher agreement among members of a committee.178 The PRMR Hospital Recommendation Group reviewed the proposed updated Hospital Readmissions Reduction Program measure set specifications (MUC2024– 030, MUC2024–032, MUC2024–040, MUC2024–041, MUC2024–045, MUC2024–046) during a meeting on January 16, 2025, to vote on a recommendation about use of these measures for the Hospital Readmissions Reduction Program.179 The PRMR Hospital Recommendation Group reached consensus for each of the measures. For each measure, they voted to recommend the addition of MA data to each measure, with conditions.180 The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital 30- Day, All-Cause, RSRR Following AMI Hospitalization measure were: 18 members of the grou ns.180 The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital 30- Day, All-Cause, RSRR Following AMI Hospitalization measure were: 18 members of the group recommended adopting the updates without conditions; 9 members recommended adoption with conditions; and 0 members voted not to recommend the updates for adoption. Taken together, 100 percent of the votes were between ‘‘recommend’’ and ‘‘recommend with conditions.’’ Thus, the committee reached consensus and recommended with conditions the updates to the Hospital 30-Day, All-Cause, RSRR Following AMI Hospitalization measure. The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital 30- Day, All-Cause, RSRR Following HF Hospitalization measure were: 17 members of the group recommended adopting the updates without conditions; 10 members recommended adoption with conditions; and 0 members voted not to recommend the updates for adoption. Taken together, 100 percent of the votes were between 178 Battelle—Partnership for Quality Measurement. (February 2025). Guidebook of Policies and Procedures for Pre-Rulemaking Measure Review (PRMR) and Measure her, 100 percent of the votes were between 178 Battelle—Partnership for Quality Measurement. (February 2025). Guidebook of Policies and Procedures for Pre-Rulemaking Measure Review (PRMR) and Measure Set Review (MSR). Available at: https://p4qm.org/sites/default/ files/2024-12/Final-Draft-Multi-Stakeholder-Group- Guidebook-of-Policies-and-Procedures.pdf. 179 Battelle—Partnership for Quality Measurement. (February 2025). PRMR 2024 MUC Recommendations Spreadsheet Final. Available at: https://p4qm.org/PRMR/Resources. 180 Battelle—Partnership for Quality Measurement. (February 2025). PRMR 2024 MUC Recommendations Spreadsheet Final. Available at: https://p4qm.org/media/3891. ‘‘recommend’’ and ‘‘recommend with conditions.’’ Thus, the committee reached consensus and recommended with conditions the updates to the Hospital 30-Day, All-Cause, RSRR Following HF Hospitalization measure. The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital-Level, 30-Day, All-Cause, RSRR Following COPD Hospitalization measure were: 18 members of the group recommended adopting the updates without conditions; 9 members recommended adoption with conditions; and 0 mem Day, All-Cause, RSRR Following COPD Hospitalization measure were: 18 members of the group recommended adopting the updates without conditions; 9 members recommended adoption with conditions; and 0 members voted not to recommend the updates for adoption. Taken together, 100 percent of the votes were between ‘‘recommend’’ and ‘‘recommend with conditions.’’ Thus, the committee reached consensus and recommended with conditions the updates to the Hospital-Level, 30-Day, All-Cause, RSRR Following COPD Hospitalization measure. The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital 30- Day, All-Cause, RSRR Following THA and/or TKA Hospitalization measure were: 19 members of the group recommended adopting the updates without conditions; 7 members recommended adoption with conditions; and 1 member voted not to recommend the updates for adoption. Taken together, 96 percent of the votes were between ‘‘recommend’’ and ‘‘recommend with conditions.’’ Thus, the committee reached consensus and recommended with conditions the updates to the Hospital 30-Day, All- Cause, RSRR Following THA and/or TKA Hospitalization measure. The voting results of the PRMR s, the committee reached consensus and recommended with conditions the updates to the Hospital 30-Day, All- Cause, RSRR Following THA and/or TKA Hospitalization measure. The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital 30- Day, All-Cause, RSRR Following PN Hospitalization measure were: 17 members of the group recommended adopting the updates without conditions; 10 members recommended adoption with conditions; and 0 members voted not to recommend the updates for adoption. Taken together, 100 percent of the votes were between ‘‘recommend’’ and ‘‘recommend with conditions.’’ Thus, the committee reached consensus and recommended with conditions the updates to the Hospital 30-Day, All-Cause, RSRR Following PN Hospitalization measure. The voting results of the PRMR Hospital Recommendation Group for the proposed updates to the Hospital 30- Day, All-Cause, RSRR Following CABG Surgery measure were: 19 members of the group recommended adopting the updates without conditions; 8 members VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00390 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S the updates without conditions; 8 members VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00390 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36925 recommended adoption with conditions; and 0 members voted not to recommend the updates for adoption. Taken together, 100 percent of the votes were between ‘‘recommend’’ and ‘‘recommend with conditions.’’ Thus, the committee reached consensus and recommended with conditions the updates to the Hospital 30-Day, All- Cause, RSRR Following CABG Surgery measure. The measure set was discussed as a group during the Hospital Recommendation Group meeting, with committee members providing recommendations that spanned across measures. The conditions submitted included: revising the inclusion criteria to include care provided in ambulatory settings; stratification of measure data by MA and FFS; consideration of a shorter 7- or 14-day readmission time period; and conducting additional testing to evaluate whether the measure is topped out for all subgroups reporting. After taking these co FFS; consideration of a shorter 7- or 14-day readmission time period; and conducting additional testing to evaluate whether the measure is topped out for all subgroups reporting. After taking these conditions into account, we proposed to adopt the updated Hospital Readmissions Reduction Program measure set in the Hospital Readmissions Reduction Program. We note that the conditions were not specific to the addition of MA data into the measures but addressed the measures in totality. Therefore, we will review the applicability of stratifying the measures by MA or FFS data and provide that information through the confidential feedback reports for hospitals. We will also evaluate a shorter 7- or 14-day readmission time period and review the criteria to include care provided in ambulatory settings and its applicability to each measure. We continue to review each measure’s topped out status through our internal measure evaluation reports. (b) Measure Endorsement We refer readers to FY 2025 IPPS/ LTCH PPS final rule (89 FR 69457 through 69458) for details on the endorsement and maintenance (E&M) process including the procedures the CBE’s E&M Committees use to evaluate measures and whether PPS/ LTCH PPS final rule (89 FR 69457 through 69458) for details on the endorsement and maintenance (E&M) process including the procedures the CBE’s E&M Committees use to evaluate measures and whether they meet endorsement criteria. The currently implemented version of these measures in the Hospital Readmissions Reduction Program were previously evaluated and endorsed by the CBE.181 The proposed 181 Hospital 30-Day, All-Cause, RSRR Following PN Hospitalization (CBE #0506), Hospital 30-Day, All-Cause, RSRR Following HF Hospitalization (CBE #0330), Hospital 30-Day, All-Cause, RSRR Following THA and/or TKA Hospitalization (CBE #1551), Hospital 30-Day, All-Cause, RSRR Following CABG Surgery (CBE #2515), Hospital- updated measures that include MA beneficiaries in the patient cohorts will each be considered for future endorsement. (4) Data Submission and Reporting The proposed updated Hospital Readmissions Reduction Program measure set would use index admission diagnoses and in-hospital comorbidity data from Medicare FFS Part A, hospital-submitted MA claims, and MAO-submitted encounter data. Additional comorbidities prior to the index admission are assessed using Part A and Part B Medica rbidity data from Medicare FFS Part A, hospital-submitted MA claims, and MAO-submitted encounter data. Additional comorbidities prior to the index admission are assessed using Part A and Part B Medicare claims and/or MA encounters in the 12 months prior to index (initial) admission. A patient’s Medicare FFS or MA enrollment status would be obtained from the Medicare enrollment data which contains beneficiary demographic, benefit/ coverage, and vital status information. We proposed to use claims and encounter data with admission dates beginning from July 1, 2023, through June 30, 2025, which is associated with the FY 2027 program year. By using CMS administrative data, hospitals would not be required to submit additional data for calculating the measures. If these measure updates are finalized, we would continue to publicly report readmission rates by posting the readmission measure results for the applicable conditions for a fiscal year for each applicable hospital on the Compare tool or successor website(s), currently available at https:// www.medicare.gov/care-compare/, and on the Provider Data Catalog, available at https://data.cms.gov/provider-data/, as codified at § 412.154(f) or successor website(s), currently available at https:// www.medicare.gov/care-compare/, and on the Provider Data Catalog, available at https://data.cms.gov/provider-data/, as codified at § 412.154(f). We invited public comment on this proposal. Comment: Many commenters supported the inclusion of MA beneficiaries into the Hospital Readmissions Reduction Program measure set stating that inclusion would result in a fairer, more representative evaluation of hospital performance; improve data accuracy and timeliness; and align with broader initiatives in value-based care. Commenters stated that this inclusion enhances representativeness and fairness by creating a more comprehensive view of the Medicare population since MA beneficiaries comprise a growing share of Medicare beneficiaries. A commenter supported the inclusion because the PRMR Hospital Committee reviewed and supported these changes. Level, 30-Day, All-Cause, RSRR Following COPD Hospitalization (CBE #1891), and Hospital 30-Day, All-Cause, RSRR Following AMI Hospitalization (CBE #0505) can all be found at https:// cmit.cms.gov/cmit/#/MeasureInventory. Response: We thank these commenters for their support. Comment: A few comme All-Cause, RSRR Following AMI Hospitalization (CBE #0505) can all be found at https:// cmit.cms.gov/cmit/#/MeasureInventory. Response: We thank these commenters for their support. Comment: A few commenters recommended that CMS stratify performance results by payer type, which would allow comparison of performance between MA and FFS populations. A commenter stated that stratification by payer would allow analysis of the effects of MA plan design on readmissions rates. Some elements of MA plan design cited by the commenter were a limited post-acute care network, a limited specialty network, referral restrictions, and denials of post-acute care coverage. Response: We thank commenters for this recommendation. Consistent with the recommendation from the PRMR Hospital Recommendation Group, we intend to review the applicability of stratifying the measures by MA or FFS data. We note that stratifying the model by FFS and MA did not yield meaningful differences in performance, supporting the decision to model them together with an indicator variable. Finally, keeping FFS and MA patients together for purposes of this measure’s calculation will keep the hospitals’ total volume higher for more ision to model them together with an indicator variable. Finally, keeping FFS and MA patients together for purposes of this measure’s calculation will keep the hospitals’ total volume higher for more reliable measure scores. We would provide data regarding payer for hospitals to review through annual confidential feedback reports provided as part of participation in the Hospital Readmissions Reduction Program. Comment: A commenter supported inclusion of index admissions for MA beneficiaries in the measure cohorts but did not support stratifying by Medicare FFS and MA data. This commenter stated that the measures were not developed and have not been tested for reporting at the health plan level. Response: We understand the commenter’s concern about potential stratification of measure results and will consider whether the lack of testing at the health plan level affects the applicability of stratifying the measures by MA or FFS data. We would only make data regarding payer available through the confidential feedback reports for hospitals. Any potential public reporting of stratified measure data would be through future notice- and-comment rulemaking. Comment: Several commenters expre ugh the confidential feedback reports for hospitals. Any potential public reporting of stratified measure data would be through future notice- and-comment rulemaking. Comment: Several commenters expressed concern that MA plans do not follow the same readmission calculation methodologies and reimbursement policies as traditional Medicare. These commenters recommended requiring MA plans to adhere to traditional Medicare payment policies prior to incorporating index admissions for MA beneficiaries into the cohorts for Hospital Readmissions Reduction VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00391 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36926 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations Program measures. Commenters specifically expressed concern that MA plans bundle multiple admissions into one or refuse to pay for readmissions within defined windows which could result in hospitals being penalized for events related to MA plan policies. Some commenters requested clarification regarding whether admissions for which MA plans denied payments would be excluded ld result in hospitals being penalized for events related to MA plan policies. Some commenters requested clarification regarding whether admissions for which MA plans denied payments would be excluded as readmissions for the purposes of the Hospital Readmissions Reduction Program. Response: We acknowledge commenters concerns regarding readmission calculation methodologies and reimbursement policies differences between MA plans and traditional Medicare. However, adding MA beneficiaries into the cohorts of the Hospital Readmissions Reduction Program measure set will provide a more robust and holistic view of quality of care provided to all Medicare beneficiaries despite reimbursement differences. For measure calculation, we identify index admissions and subsequent admissions (that is, readmissions) for patients enrolled in MA plans using MA encounter data and information-only claims for MA inpatient stays. We note that neither of these data sources are dependent on the MA plan’s coverage determinations (including bundling or denying coverage) for that admission. Therefore, the measures would continue to encourage hospitals to focus on preventing readmissions, which are often an adver determinations (including bundling or denying coverage) for that admission. Therefore, the measures would continue to encourage hospitals to focus on preventing readmissions, which are often an adverse event for patients and impose a financial burden on the patient and the healthcare system. Because an increasing portion of Medicare beneficiaries are covered by MA plans, including index admissions for these patients in our measure cohorts is an important step in ensuring high-quality, safe care for all Medicare beneficiaries. Including index admissions for Medicare beneficiaries enrolled in MA also increases the cohort size for the Hospital Readmissions Reduction Program measures, which in turn improves the measures’ precision for each hospital. Due to the benefits of improving accuracy and reliability of the measures, we do not think it is appropriate to exclude any readmissions for which MA plans may have denied payment for the readmission if the administrative data reflect that a readmission occurred. Comment: A few commenters recommended the development of separate or modified quality measures designed specifically for MA’s capitated payment model. Response: While separate qua eadmission occurred. Comment: A few commenters recommended the development of separate or modified quality measures designed specifically for MA’s capitated payment model. Response: While separate quality measures designed specifically for MA’s capitated payment model could be possible, the Hospital Readmissions Reduction Program is designed to encourage hospitals to improve communication and care coordination to better engage patients and caregivers in discharge plans and, in turn, reduce avoidable readmissions. As previously stated, adding the MA cohort to the Hospital Readmissions Reduction Program measures would provide a more robust and holistic view of quality of care provided to all Medicare beneficiaries. Therefore, we find the addition of the MA cohort to the Hospital Readmissions Reduction Program measures to further the Hospital Readmissions Reduction Program goals. Comment: A few commenters requested that CMS clarify whether readmissions data regarding MA beneficiaries would be based on shadow claims that hospitals submit to CMS or whether the MA plan would be responsible for reporting readmissions. Response: For determining readmissions for the Hospital Readmissions Re d be based on shadow claims that hospitals submit to CMS or whether the MA plan would be responsible for reporting readmissions. Response: For determining readmissions for the Hospital Readmissions Reduction Program, we would evaluate the detailed data regarding enrollee health care encounters that MA plans are already required to submit to CMS as well as the information-only claims that hospitals submit (that is, ‘‘shadow claims’’). We would use index admission diagnoses from Medicare FFS Part A claims and MA encounter data as well as data from hospital inpatient information-only claims, outpatient and physician Medicare FFS claims (information-only claims), and MA encounter data from the 12 months prior to the index admission to identify comorbidities for risk adjustments. We would use the MA encounter data, information-only claims, and Medicare Part A claims to identify index admissions and applicable readmissions such that neither hospitals nor MA plans would be required to submit any additional data for this cohort expansion. Comment: Many commenters expressed concern that MA encounter data are neither as complete nor as reliable as FFS claims, which they stated could affect t any additional data for this cohort expansion. Comment: Many commenters expressed concern that MA encounter data are neither as complete nor as reliable as FFS claims, which they stated could affect the fairness and accuracy of Hospital Readmissions Reduction Program performance assessments. Some commenters expressed concern that basing performance calculations on data which could be incomplete or unreliable could cause financial or reputational harm to hospitals. Some commenters noted that MedPAC and the Government Accountability Office (GAO) have found that variations in coding practices, historical discrepancies, and a lack of data validation have impacted the completeness and reliability of MA encounter data. Some commenters also stated that under the current Health Effectiveness Data and Information Set (HEDIS) data submission requirements, MA plans are not obligated to report all hospital readmissions, only those for which they have approved payment, which could potentially undercount readmissions for index admissions for beneficiaries enrolled in MA plans. Response: We refer readers to the Announcement of Calendar Year (CY) 2022 Medicare Advantage (MA) Capitation Rates and P count readmissions for index admissions for beneficiaries enrolled in MA plans. Response: We refer readers to the Announcement of Calendar Year (CY) 2022 Medicare Advantage (MA) Capitation Rates and Part C and Part D Payment Policies where CMS discussed the efforts undertaken to improve the completeness and validity of encounter data, and transitioned to calculating 100 percent of the risk score using diagnoses from encounter data and FFS (see discussion in Attachment III, Sections G and M of this Announcement). We respectfully disagree that the level of completeness of the MA data presents a significant issue with regard to measure reliability. We have been evaluating the MA data for use in quality measurement since 2017, and we note recent CMS policies have aimed to improve timeliness, completeness, and accuracy of MA data, thereby further enhancing its usability for hospital outcome measures.182 183 Hospital-submitted MA claims data are currently already in use for DSH and GME payment calculations and Medicare Advantage Organization (MAO)-submitted encounter data are currently already in use for calculating MA beneficiary risk scores.184 In calculating both the Hybrid Hospital- nt calculations and Medicare Advantage Organization (MAO)-submitted encounter data are currently already in use for calculating MA beneficiary risk scores.184 In calculating both the Hybrid Hospital- Wide All-Cause Readmission and Hybrid Hospital-Wide All-Cause Risk Standardized Mortality measures in the Hospital Inpatient Quality Reporting Program, we specify that for each MA admission, we would use either the hospital-submitted MA claim or the 182 Centers for Medicare & Medicaid Services. Calendar Year (CY) 2024 Advance Notice of Methodological Changes for Medicare Advantage (MA) Capitation Rates and Part C and Part D Payment Policies (the Advance Notice). Accessed March 5, 2023. Available from: https:// www.cms.gov/files/document/2024-advance- notice.pdf. 183 Medicare Payment Advisory Commission. March 2022 report to the Congress: Medicare Payment Policy: The Medicare Advantage program: Status Report and mandated report on dual-eligible special needs plans. May 30, 2022. Available from: https://www.medpac.gov/wp-content/uploads/ 2022/03/Mar22_MedPAC_ReportToCongress_Ch12_ SEC.pdf. 184 Medicare monthly enrollment data available at: https://data.cms.gov/summary-statistics-on- bene rom: https://www.medpac.gov/wp-content/uploads/ 2022/03/Mar22_MedPAC_ReportToCongress_Ch12_ SEC.pdf. 184 Medicare monthly enrollment data available at: https://data.cms.gov/summary-statistics-on- beneficiary-enrollment/medicare-and-medicaid- reports/medicare-monthly-enrollment VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00392 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36927 MAO-submitted MA encounter data record, whichever is available. If the MA admission information for a patient is available in both sources, we would use the hospital-submitted MA claim because it is timelier and already associated with the applicable hospital’s CMS Certification Number (CCN). More generally, we have found that incorporating data regarding MA patients into the readmission measures improve reliability, narrow the confidence intervals of measure scores, and lead to more hospitals and beneficiaries being included in the measures. Based on internal analyses of MA data reported to CMS by hospitals and MAOs for the years 2017 through s of measure scores, and lead to more hospitals and beneficiaries being included in the measures. Based on internal analyses of MA data reported to CMS by hospitals and MAOs for the years 2017 through 2021, we determined that it is feasible to use MA admissions in CMS hospital outcome measures. Hospitals and MAOs submit the data on a schedule that allows for their use. National Provider Identifiers (NPIs) from inpatient MA encounter data in CMS’ Integrated Data Repository (IDR) can be matched to CMS CCNs currently used to identify hospitals in the CMS outcome measures. A high percentage of MA encounter data were submitted within the three-month time frame needed for reporting hospital measures and has improved over time (90.3% in 2018 compared to 95.2% in 2021 for inpatient encounters for acute care and critical access hospitals). Our internal analysis found a high rate of matching diagnoses between the MAO- submitted MA encounter data and the hospital-submitted MA claims, supporting the use of either data source for a given admission for measure calculation As stated previously, the measures will capture readmissions from information-only hospital claims and/or MA encounter data r he use of either data source for a given admission for measure calculation As stated previously, the measures will capture readmissions from information-only hospital claims and/or MA encounter data regardless of whether the plan paid for them or reported (or not reported) them in other information sets, such as HEDIS. Generally, while HEDIS evaluates the quality of care at the population plan level where MA plans submit HEDIS- required data elements to evaluate quality across the enrolled population, the Hospital Readmissions Reduction Program uses fee-for-service claims, hospital-submitted MA claims or the MAO-submitted MA encounter records to calculate condition or procedure- specific hospital-level readmission rates to hold hospitals directly accountable for excess readmission rates. Essentially, HEDIS focuses on broad plan quality, while the Hospital Readmissions Reduction Program focuses on condition- and procedure-specific hospital outcomes at the facility-level. The fundamental difference is that HEDIS measures evaluate how well MA plans manage their members’ overall health and care experience, while the Hospital Readmissions Reduction Program condition- and procedure- spec difference is that HEDIS measures evaluate how well MA plans manage their members’ overall health and care experience, while the Hospital Readmissions Reduction Program condition- and procedure- specific measures evaluate how well individual hospitals prevent unnecessary readmissions after discharge. Comment: Many commenters expressed concern about the proposal, stating that MA beneficiaries experience different benefit designs, network restrictions, utilization management requirements, and prior authorization practices than beneficiaries covered under Medicare FFS. Some commenters were also concerned that MA plan policies may affect readmissions, leading to higher readmission rates, due to policies such as restrictive formularies, denials or delays in home care services, or limited specialist access. Commenters stated that this could cause hospitals to be penalized for delays or denials that originate in MA plan policies rather than from substandard hospital care. Response: We recognize that Medicare Advantage payment policies are not the same as Medicare FFS payment policies, and by design, MAOs are given more flexibility in benefit and provider reimbursement design. However, fr ize that Medicare Advantage payment policies are not the same as Medicare FFS payment policies, and by design, MAOs are given more flexibility in benefit and provider reimbursement design. However, from a patient’s perspective, a readmission is an adverse outcome irrespective of benefit or payment policies. It is important to measure and provide transparency as to readmission rates for all Medicare beneficiaries. Using data from calendar year (CY) 2022 to 2023, internal analyses showed no statistical difference in the average risk- standardized readmission rates (RSRR) across the condition- and procedure- specific measures for the FFS-only and MA-only patients. While we understand that MA enrollees are subject to different benefits design and payment approaches than FFS enrollees, we do not agree that these differences mean that their clinical outcomes are beyond the hospital’s control. We continue to encourage hospitals to work closely with insurers, including MA plans, to coordinate the highest quality care for their patients. Comment: Some commenters requested that CMS communicate any shifts in benchmarks, distributions, or penalty thresholds that result from the inclusion of MA the highest quality care for their patients. Comment: Some commenters requested that CMS communicate any shifts in benchmarks, distributions, or penalty thresholds that result from the inclusion of MA data. A few commenters also requested analysis of the impact of including index admissions for beneficiaries enrolled in MA plans in the measure cohort on hospital reimbursement, including identification of regional and local trends. Response: We note that there is no baseline or benchmark period under the Hospital Readmissions Reduction Program. We will continue to use excess readmission ratios (ERRs) to assess a hospital’s excess readmissions during the applicable period for each of the conditions or procedures included in the program. The ERR is a measure of a hospital’s relative performance compared with an average hospital with a patient case mix similar to that hospital’s (that is, if patients with the same characteristics had been treated at an average hospital, rather than at that hospital). Additionally, under the peer grouping methodology as required by section 1886(q)(3)(D) of the Act, we assess hospitals’ performance relative to other hospitals with a similar proportion of hospital). Additionally, under the peer grouping methodology as required by section 1886(q)(3)(D) of the Act, we assess hospitals’ performance relative to other hospitals with a similar proportion of stays for beneficiaries who are dually eligible for Medicare and full Medicaid benefits during the applicable period. Under the peer grouping methodology, we use the peer group median ERR (that is, the median ERR within a peer group) as the threshold to assess hospital performance on each measure. We will continue to communicate information on peer groups and peer group median ERRs during the Review and Correction period. Comment: Some commenters expressed concern that inclusion of index admissions for MA beneficiaries in the measure cohort would disproportionately affect hospitals in regions with high MA adoption rates. Response: Table VI.K–02 of this final rule displays a comparison of hospital performance under the proposed updates to performance under the current methodology. This table analyzes performance across a number of hospital characteristics, including geographic region. The table shows that the number of penalized hospitals increases moderately (up to 7 percentage points le analyzes performance across a number of hospital characteristics, including geographic region. The table shows that the number of penalized hospitals increases moderately (up to 7 percentage points) among all regions, with the exception of hospitals in the West South Central and Mountain regions. Additionally, although the penalty as a share of payments, which indicates the estimated financial impact on hospitals, increases for hospitals in the Middle Atlantic, East North Central, West North Central, and Pacific regions, no region is disproportionately impacted by the addition of MA beneficiaries in the measure cohort. With respect to the concern that this update would disproportionately affect hospitals in regions with high MA adoption rates, we note that MA beneficiaries comprise a majority of Medicare enrollees (51.2 percent as of VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00393 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36928 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations March 2025 185) and that hospitals are responsible for providing high quality ca 9 K S D n o d n o m m a h k 36928 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations March 2025 185) and that hospitals are responsible for providing high quality care to all their patients, regardless of payer. We continue to encourage hospitals to work closely with insurers, including MA plans, to coordinate the highest quality care for their patients. By adding the MA cohort to the Hospital Readmissions Reduction Program measures we would provide a more robust and holistic view of quality of care provided to all Medicare beneficiaries. We note that our analysis of the mean risk-standardized readmission rates (RSRRs) using calendar years (CYs) 2022 and 2023, the rates are similar between FFS-only and MA-only patients for most conditions and procedures. The largest difference was 0.5 percentage points for performance both on the Hospital 30- Day, All-Cause, RSRR Following CABG Surgery measure and the Hospital 30- Day, All-Cause, RSRR Following HF Hospitalization measure (the results were statistically significant at the 0.05 level).186 Comment: A commenter requested clarification on when baseline reports including the MA patient cohort data will pitalization measure (the results were statistically significant at the 0.05 level).186 Comment: A commenter requested clarification on when baseline reports including the MA patient cohort data will be distributed. Response: We assume the commenter is referring to baseline reports such as are used in the Hospital VBP Program and note that the Hospital Readmissions Reduction Program does not use baseline reports. For the Hospital Readmissions Reduction Program, hospitals will receive annual confidential feedback reports that include details such as a hospital’s payment reduction percentage, payment adjustment factors, dual proportion, peer group assignment, measure results, ratio of base operating DRG payments per measure to total payments, national readmission rates, detailed discharge- level data, and risk factor information for the readmission measures, and a flag to indicate whether the index admission data originated from FFS or MA. Comment: A few commenters requested CMS clarify how risk adjustment methodologies will be adapted to account for differences in MA populations and ensure that hospitals are not unfairly penalized. Response: The risk adjustment for each readmission how risk adjustment methodologies will be adapted to account for differences in MA populations and ensure that hospitals are not unfairly penalized. Response: The risk adjustment for each readmission measure in the Hospital Readmissions Reduction Program is based on patient comorbidities as identified through an analysis of the admission diagnoses and in-hospital comorbidity data as well as clinical data (currently assessed from Medicare Part A and Part B claims) for the 12 months prior to the index admission. Under this updated measure cohort, we would also include MA encounter data for the index admission and the 12 months prior to the index admission to identify clinical risk factors to risk adjust the measures. Internal analyses showed that stratification of the model by FFS and MA did not yield meaningful differences in risk profiles. And as previously discussed, we saw similar readmission rates between FFS-only and MA-only patients for most conditions and procedures. Therefore, the clinical variables for risk adjustment were identified through an analysis of a combined MA and FFS cohort.187 This cohort was approximately evenly split between FFS and MA beneficiaries, and the p he clinical variables for risk adjustment were identified through an analysis of a combined MA and FFS cohort.187 This cohort was approximately evenly split between FFS and MA beneficiaries, and the prevalence of clinical risk factors and their associations with readmission outcomes were similar across both groups. The final models also included an indicator for MA versus FFS enrollment to adjust for any potential residual case-mix differences between the two beneficiary groups. Comment: A commenter expressed concern that the URL provided in the proposed rule for the CMS Measures Management System does not actually display the list of applicable ICD–10 codes used in the risk adjustment model. The commenter requested that CMS clearly identify the location or provide a document containing those ICD–10 codes so that stakeholders may verify the standards underlying risk adjustment. Response: The commenter is correct that the cited website did not display the list of applicable ICD–10 codes used in the risk adjustment model. We subsequently issued a correction notice to correctly refer readers to the QualityNet website for a crosswalk between ICD–10 codes and condition categories used f used in the risk adjustment model. We subsequently issued a correction notice to correctly refer readers to the QualityNet website for a crosswalk between ICD–10 codes and condition categories used for risk adjustment (90 FR 23867). This crosswalk is available at: https://qualitynet.cms.gov/inpatient/ measures/readmission/resources. Comment: A few commenters stated that adding MA beneficiaries to the Hospital Readmissions Reduction Program would likely increase administrative burden on hospitals. Some commenters stated that the incorporation of MA data would require significant updates to reporting systems, staff training, and potentially new 185 Medicare monthly enrollment data available at: https://data.coms.gov/summary-statistics-on- beneficiary-enrollment/medicare-and-medicaid- reports//medicare-monthly-enrollment. 186 CMS internal analysis. February 2025. 187 2024 Condition- and Procedure-Specific Readmission Measures Supplemental Methodology Report (available at: https://qualitynet.cms.gov/ inpatient/measures/readmission/methodology). infrastructure, thereby diverting resources from direct patient care. Response: These measures will continue to be calculated using administra net.cms.gov/ inpatient/measures/readmission/methodology). infrastructure, thereby diverting resources from direct patient care. Response: These measures will continue to be calculated using administrative data already reported to CMS by hospitals and MA plans. Therefore, we do not agree that hospitals would be required to invest in reporting systems, staff training, or new infrastructure. In addition, we note that MA plans have been using hospital readmission measures and hospitals have been preparing for the addition of MA data to several Hospital IQR Program measures, including the Hybrid Hospital-Wide All-Cause Readmission and Hybrid Hospital-Wide All-Cause Risk Standardized Mortality measures (88 FR 59161 through 59168) and the Thirty-day Risk-Standardized Death Rate among Surgical Inpatients with Complications measure (89 FR 69545 through 69552). Comment: Many commenters recommended a phased implementation approach with a confidential review period during which hospitals could assess the data’s accuracy and understand its impact on performance. Some commenters further requested that CMS release detailed, provider-level data and analyses before final adoption of the new methodo ess the data’s accuracy and understand its impact on performance. Some commenters further requested that CMS release detailed, provider-level data and analyses before final adoption of the new methodology. A few commenters urged a phased rollout which initially integrates MA data in quality reporting programs (such as the Hospital IQR Program) rather than in pay-for-performance programs. A few commenters recommended that CMS establish stakeholder workgroups to harmonize definitions and reporting requirements across Medicare populations. Response: As discussed previously, several Hospital IQR Program measures have integrated MA data similar to our proposal for the Hospital Readmissions Reduction Program measure set. We are also finalizing the integration of MA data for the Hospital-level Risk- Standardized Complication Rate Following Elective Primary Total Hip Arthroplasty and/or Total Knee Arthroplasty measure in the Hospital IQR and Hospital VBP programs, as discussed in section X.C.3.b and VI.L.2.a., respectively, of the preamble of this final rule. We note that restricting the measure cohort to only include index admissions for patients covered by Medicare FFS does not incentivi .b and VI.L.2.a., respectively, of the preamble of this final rule. We note that restricting the measure cohort to only include index admissions for patients covered by Medicare FFS does not incentivize hospitals to improve care- coordination for Medicare beneficiaries enrolled in MA plans. Expanding the measure cohort to include index admissions for this patient population will enable us to address this, and encourage high-quality, safe care for all Medicare beneficiaries regardless of VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00394 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36929 payer. Therefore, we believe it is appropriate to include these index admissions in the measure cohort as early as technically feasible. We will continue to monitor and evaluate the effects of including these data in the cohorts for the Hospital Readmissions Reduction Program measures. We welcome continued input on harmonizing definitions and reporting requirements to ensure that our quality programs serve the largest number of patie Hospital Readmissions Reduction Program measures. We welcome continued input on harmonizing definitions and reporting requirements to ensure that our quality programs serve the largest number of patients possible. Comment: A few commenters supported CMS’s technical update to transition from Hierarchical Condition Categories (HCCs) to International Classification of Diseases (ICD)–10 codes, stating that this would reduce incentives for upcoding and improve comparisons. Another commenter stated that the transition would increase precision and clinical relevance, particularly for high-variability conditions, as well as promote more accurate modeling and benchmarking, potentially allowing for better differentiation between hospitals serving complex and socially vulnerable patient populations. Response: We thank commenters for their support. Comment: A commenter expressed concern that removing key clinical risk adjustment covariates from the Excess Readmission Ratio (ERR) calculation would unfairly penalize hospitals that serve complex and vulnerable populations. The commenter recommended retaining the current clinical risk adjustment until Z-codes and comprehensive social risk data are unfairly penalize hospitals that serve complex and vulnerable populations. The commenter recommended retaining the current clinical risk adjustment until Z-codes and comprehensive social risk data are available to avoid unwarranted penalties. A commenter noted that the projected increase in aggregate penalties may signal that the program thresholds are too stringent or not sufficiently adjusted for social risk. Response: We note that the technical update does not remove risk adjustment for the ERRs, rather the update transitions to the more specific ICD–10– CM codes as opposed to the grouped HCC. This risk adjustment continues to be based on patient-level comorbidities as identified through an analysis of the admission diagnoses and in-hospital comorbidity data as well as clinical data for the 12 months prior to the index admission. The Hospital Readmissions Reduction Program is intended to encourage high-quality, safe care for all Medicare beneficiaries, and beginning in FY 2019, CMS used the peer grouping methodology to evaluate a hospital’s performance by assessing hospitals’ performance relative to the performance of other hospitals with a similar proportion of stays for benefi used the peer grouping methodology to evaluate a hospital’s performance by assessing hospitals’ performance relative to the performance of other hospitals with a similar proportion of stays for beneficiaries who are dually eligible for Medicare and full Medicaid benefits. Our analysis of the estimated impact of adding MA data to the readmission measures, shortening the performance period to two years, the technical updates to the measures, and adding MA data to the aggregate payments for each condition/procedure and all discharges indicated that, while those changes are likely to increase payment reductions, the addition of MA data to the aggregate payments for each condition/procedure and all discharges is the largest driver of payment reduction increases. Refer to section VI.K.3.b.(1) for more detailed information about our analysis. Comment: Several commenters raised concerns about CMS’s technical update to base the risk adjustment model directly on individual ICD–10–CM diagnosis codes instead of on HCC-based variables for the measures in the Hospital Readmissions Reduction Program. Some commenters stated that this is inconsistent with CMS’s continued use of HCC models for some des instead of on HCC-based variables for the measures in the Hospital Readmissions Reduction Program. Some commenters stated that this is inconsistent with CMS’s continued use of HCC models for some payment models. Some commenters expressed concern that the transition to ICD–10–CM diagnosis codes could result in unintended changes in reported outcomes, particularly for smaller, rural, or safety net hospitals. Some commenters urged CMS either to postpone the switch to an ICD–10–based model or to implement a transition period during which both HCC and ICD-10–based risk models are reported to monitor impact. Some commenters requested that CMS conduct clinical validations and implement rigorous testing and consistent application of risk adjustment methodology across all programs to ensure transparency and comparability. A commenter further advised caution and transparency in model development, recommending that CMS clearly document the rationale and process for ICD–10 code selection and grouping. Response: We note that individual ICD–10 codes are more specific than HCCs. By re-specifying the risk models for each measure with individual ICD– 10 codes, we improve the performance of the rouping. Response: We note that individual ICD–10 codes are more specific than HCCs. By re-specifying the risk models for each measure with individual ICD– 10 codes, we improve the performance of the risk adjustment models for our condition- and procedure-specific measures. We understand that some payment models continue to use HCC models to calculate payments and note that because different programs are focused on achieving different elements of our priorities, it is sometimes appropriate to use different methods of calculating risk. We note that we conduct annual measure re-evaluations to ensure that the risk-standardized complication model is continually assessed and remains valid, given possible changes in clinical practice and coding standards over time.188 Modifications made to the measure cohort, risk model, and outcomes are informed by review of the most recent literature related to measure conditions or outcomes, feedback from various stakeholders, empirical analyses, and assessment of coding trends that reveal shifts in clinical practice or billing patterns.189 Input is solicited from a workgroup composed of up to 20 clinical and measure experts, inclusive of internal and ssment of coding trends that reveal shifts in clinical practice or billing patterns.189 Input is solicited from a workgroup composed of up to 20 clinical and measure experts, inclusive of internal and external consultants and subcontractors. As a part of annual re- evaluations, one of the activities we undertook was reviewing select pre- existing ICD–10 code-based specifications with our workgroup to confirm appropriateness unaffected by the updates, as well as review any potentially clinically relevant codes that ‘‘neighbor’’ existing codes used in the measure to identify any warranted specification changes.190 As a part of our routine monitoring and evaluation, we will watch for any unintended consequences from this updated risk model. After consideration of the public comments we received, we are finalizing our proposal to integrate Medicare Advantage (MA) beneficiaries into the cohorts of the Hospital Readmissions Reduction Program measure set beginning with the FY 2027 program year as proposed. b. Technical Updates to the Specifications of the Hospital Readmissions Reduction Program Measures Beginning With the FY 2027 Program Year During the COVID–19 public health emergency (P r as proposed. b. Technical Updates to the Specifications of the Hospital Readmissions Reduction Program Measures Beginning With the FY 2027 Program Year During the COVID–19 public health emergency (PHE), in the FY 2022 IPPS/ LTCH PPS final rule (86 FR 45256 through 45258), we updated the Hospital 30-Day All-Cause RSRR Following AMI Hospitalization; Hospital 30-Day, All-Cause, RSRR Following CABG Surgery; Hospital- Level, 30-Day, All-Cause, RSRR Following COPD Hospitalization; Hospital 30-Day, All-Cause, RSRR Following HF Hospitalization; and Hospital 30-Day, All-Cause, RSRR Following THA and/or TKA Hospitalization measures to exclude patients diagnosed with COVID–19, including a primary or secondary diagnosis present on admission (POA) of COVID–19, from both index 188 Centers for Medicare & Medicaid Services. 2025 Condition-Specific Readmission Measures Updates and Specifications Reports. Available at: https://qualitynet.cms.gov/inpatient/measures/ readmission/methodology. 189 Ibid. 190 Ibid. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00395 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36930 Feder 90 Ibid. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00395 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36930 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations admissions and readmissions (86 FR 45257 through 45258). In the FY 2023 IPPS/LTCH PPS final rule, we provided an update regarding the technical specifications for the Hospital 30-Day, All-Cause, RSRR Following PN Hospitalization measure to exclude patients with either principal or secondary diagnosis POA of COVID–19 from both index admissions and readmissions (87 FR 49083 through 49086). Additionally, in the FY 2023 IPPS/LTCH PPS final rule, we modified the technical measure specifications of each of the six readmission measures to include a covariate adjustment for patient history of COVID–19 in the 12 months prior to the admission beginning with the FY 2023 program year (87 FR 49086 through 49088). We stated that we were making these updates pursuant to the technical updates policy we finalized in the FY 2015 IPPS/LTCH PPS final rule. Under this policy, we finalized a subregulatory process to incorporate that we were making these updates pursuant to the technical updates policy we finalized in the FY 2015 IPPS/LTCH PPS final rule. Under this policy, we finalized a subregulatory process to incorporate technical measure specification updates into the measure specifications we had previously adopted for the Hospital Readmissions Reduction Program (79 FR 50039). We reiterated this policy in the FY 2020 IPPS/LTCH PPS final rule, stating our continued belief that the subregulatory process is the most expeditious manner possible to ensure that quality measures remain fully up to date while preserving the public’s ability to comment on updates that so fundamentally change a measure that it is no longer the same measure that we originally adopted (84 FR 42385 through 42387). We are providing notice in this final rule that we intend to remove the COVID–19 exclusion from the readmission measures beginning with the FY 2027 program year. This technical update will modify these readmission measures to remove the exclusion of COVID–19 diagnosed patients from the index admissions and readmissions, including the removal of the exclusion of certain ICD–10 Codes that represented patients with a secon to remove the exclusion of COVID–19 diagnosed patients from the index admissions and readmissions, including the removal of the exclusion of certain ICD–10 Codes that represented patients with a secondary diagnosis of COVID–19, and the history of COVID–19 risk variable. The exclusion began as a response to the COVID–19 PHE which expired May 11, 2023. We believe that hospitals have had adequate time to adjust to the presence of COVID–19 as an ongoing virus. Using data from the last four years, July 2020–June 2024, our internal analysis showed a decline over time of the number of patients excluded from the various measure cohorts. Therefore, we believe that removing the exclusion of COVID–19 patients will ensure that these readmission measures continue to account for readmissions as intended and meet the goals of the Hospital Readmissions Reduction Program. Additional resources about current measure technical specifications and the methodology for the Hospital Technical specification of the current readmission measures are provided at our website in the Measure Methodology Reports (available at: https://qualitynet.cms.gov/ inpatient/measures/readmission/ methodology). Hospital Readmi the current readmission measures are provided at our website in the Measure Methodology Reports (available at: https://qualitynet.cms.gov/ inpatient/measures/readmission/ methodology). Hospital Readmissions Reduction Program resources are located at the Resources web page of the QualityNet website (available at: https:// qualitynet.cms.gov/inpatient/hrrp/ resources). An updated measure methodology report will be made available in May 2026. While we are not required to solicit comments for technical updates, we received public comment on this proposed update. Comment: Many commenters supported the technical update to remove COVID–19 exclusions from the Hospital Readmissions Reduction Program measure set as part of the transition from a public health emergency to managing COVID–19 as an endemic risk. A commenter stated that eliminating the exclusion of COVID–19 diagnosed patients from index admissions and readmissions will reflect a more accurate depiction of all Medicare patients, improve data collection, and therefore measure hospitals more accurately and fairly. In addition, a commenter noted that the removal of these exclusions will incentivize hospitals to implement robust infec ve data collection, and therefore measure hospitals more accurately and fairly. In addition, a commenter noted that the removal of these exclusions will incentivize hospitals to implement robust infection prevention strategies and ensure that care for all Medicare patients is measured consistently. Response: We thank commenters for their support. Comment: Several commenters emphasized the need for careful risk adjustment given the potential long- term clinical effects of COVID–19. Commenters noted that patients with prior COVID–19 exposure may experience persistent complications that could influence post-acute outcomes and readmission rates and recommended that CMS update its risk adjustment models to account for the long-term clinical effects of COVID–19 to avoid penalizing hospitals that care for a higher proportion of post COVID patients. A commenter recommended that CMS continue to closely monitor the data to ensure that the removal of this exclusion accurately reflects hospital performance, and that hospitals are not being penalized due to variation in local disease spread. Another commenter recommended incorporating COVID–19 on the co-condition list for risk adjustment strati rformance, and that hospitals are not being penalized due to variation in local disease spread. Another commenter recommended incorporating COVID–19 on the co-condition list for risk adjustment stratification. Response: We thank commenters for their recommendations. As a part of our routine monitoring and evaluation, we will watch for any unintended consequences from this updated risk model. We note that we conduct annual measure re-evaluations to ensure that the risk-standardized complication model is continually assessed and remains valid, given possible changes in clinical practice and coding standards over time.191 Comment: A few commenters recommended that CMS provide a phased implementation approach to ensure data integrity and support hospitals in adapting to the COVID–19 exclusion removal. A few commenters recommended that the phased implementation contain one to two reporting cycles of data for internal review, delay public reporting of measures that include COVID–19 as a secondary diagnosis, and exclude these measures from the Hospital Readmissions Reduction Program during the initial reporting periods to avoid financial implications. Response: We do not believe that dela ndary diagnosis, and exclude these measures from the Hospital Readmissions Reduction Program during the initial reporting periods to avoid financial implications. Response: We do not believe that delaying technical updates to the measures will help meet the goals the commenters specify—that is, ensuring that accurate and reliable data are scored under the Hospital Readmissions Reduction Program. Rather, including COVID–19 patients provides a broader view of the care that hospitals provide to Medicare beneficiaries. Hospitals will also have the chance to review their measure data during the 30-day review and correction period each year prior to application of payment adjustments and public reporting. Comment: A commenter did not support the technical update to remove COVID–19 exclusions from the Hospital Readmissions Reduction Program measure set because clinical and operational impacts of COVID–19 continue to affect hospital performance; patients with COVID–19 often present with complex conditions, extended lengths of stay, and increased risk of complications; added cases may lead to skewed performance data, especially for those hospitals that serve a disproportionate share of medi x conditions, extended lengths of stay, and increased risk of complications; added cases may lead to skewed performance data, especially for those hospitals that serve a disproportionate share of medically complex or underserved populations; and the health care system is still contending with the long-term effects of COVID–19 on workforce capacity, patient outcomes, and systemic 191 Centers for Medicare & Medicaid Services. 2025 Condition-Specific Readmission Measures Updates and Specifications Reports. Available at: https://qualitynet.cms.gov/inpatient/measures/ readmission/methodology. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00396 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36931 challenges with access to post-acute care. Response: We appreciate the commenter’s concerns. However, while hospitals and other types of health care facilities may face continuing challenges due to the long-term effects of the COVID–19 pandemic, we do not agree that these challenges represent such a significant threat to health care of health care facilities may face continuing challenges due to the long-term effects of the COVID–19 pandemic, we do not agree that these challenges represent such a significant threat to health care operations that patients with a principal or secondary COVID–19 diagnosis should be excluded from these measures’ cohorts. Based on data from July 2021 to June 2024, internal analyses for the Hospital Readmissions Reduction Program measure set showed a small percentage of patients, ranging in cases from 0.15 percent for THA/TKA and 2.5 percent for PN met the COVID– 19 exclusion criteria. Please note that some of these cases could also have been excluded for other reasons besides the COVID–19 exclusion. More importantly, such patients, as with all patients treated by hospitals, should receive the best quality care from their providers, and incorporating them into quality measures represents the best way for us to incentivize high-quality care for all. Rather than unfairly penalizing hospitals, including patients with a principal or secondary diagnosis of COVID–19 will encourage them to provide the best care to a broader patient population. We appreciate commenters’ input on our technic als, including patients with a principal or secondary diagnosis of COVID–19 will encourage them to provide the best care to a broader patient population. We appreciate commenters’ input on our technical update to remove the COVID–19 exclusion from the readmission measures beginning with the FY 2027 program year. 3. Additional Policies for the Hospital Readmissions Reduction Program a. Modification of the Applicable Period for the Hospital Readmissions Reduction Program Measures Set In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18286), we proposed to modify the definition of ‘‘applicable period’’ as specified at § 412.152. Currently, the ‘‘applicable period’’ is the 3-year period from which data are being collected to calculate excess readmission ratios (ERRs) and payment adjustment factors for the fiscal year; this includes aggregate payments for excess readmissions and aggregate payments for all discharges used in the calculation of the payment adjustment. In the FY 2013 IPPS/LTCH PPS final rule, we noted that the 3-year period provided an increase in the number of cases per hospital used for measure calculation, which improved the precision of each hospital’s readmission esti PPS final rule, we noted that the 3-year period provided an increase in the number of cases per hospital used for measure calculation, which improved the precision of each hospital’s readmission estimate (77 FR 53379 through 53382). The ‘‘applicable period for dual eligibility’’ is the same as the ‘‘applicable period’’ that we otherwise adopted for purposes of the Hospital Readmissions Reduction Program. However, in the FY 2026 IPPS/LTCH PPS proposed rule we proposed to reduce the applicable period from 3 to 2 years (90 FR 18286). The proposed update would allow for more recent data when assessing performance. With the proposed inclusion of MA patients in the cohort, we assessed whether the reliability of the measures could reach a satisfactory level when the applicable period is shortened. In testing, all measures showed better between- hospital variance using the 2-year FFS and MA combined cohort as compared to the current measure specifications of a 3-year applicable period and the FFS- only cohort. Beginning in FY 2027, we proposed that the ‘‘applicable period’’ for the Hospital Readmissions Reduction Program would be the 2-year period beginning 1 year advanced from the previo FFS- only cohort. Beginning in FY 2027, we proposed that the ‘‘applicable period’’ for the Hospital Readmissions Reduction Program would be the 2-year period beginning 1 year advanced from the previous program fiscal year’s start of the ‘‘applicable period.’’ For example, for the FY 2027 program determination, claims/encounter data with admission dates beginning from July 1, 2023, through June 30, 2025, would be used. Under this policy, for all subsequent years, we would advance this 2-year period by 1 year unless otherwise specified by the Secretary, which we would revise through notice and comment rulemaking. Similarly, the ‘‘applicable period for dual eligibility’’ would continue to correspond to the ‘‘applicable period’’ for the Hospital Readmissions Reduction Program, unless otherwise specified by the Secretary. We invited public comment on this proposal. Comment: Many commenters supported the proposal to reduce the applicable period from three years to two years. Some commenters stated that a shorter window will ensure that hospital performance metrics reflect more current quality improvements and care practices while maintaining acceptable reliability. A few commenters also stated that a shorter window will ensure that hospital performance metrics reflect more current quality improvements and care practices while maintaining acceptable reliability. A few commenters also stated that a two-year applicable period enables hospitals to implement more responsive and sustainable improvements, promoting more effective allocation of resources and ultimately supporting improved health outcomes. Additionally, a few commenters stated that the proposed update to shorten the applicable period, when considered with the inclusion of MA beneficiaries and enhanced risk adjustment based on individual ICD–10 codes, would improve the measures by creating a larger, more representative patient cohort with more recent, accurate, and actionable information. Response: We thank commenters for their support. Comment: A few commenters stated that decreasing the applicable period to two years may reduce the reliability of hospital comparisons and increase performance variability. A commenter recommended that CMS monitor the statistical reliability of this change for low-volume hospitals. Another commenter recommended a phased implementation or pilot evaluation of the impact on me ommenter recommended that CMS monitor the statistical reliability of this change for low-volume hospitals. Another commenter recommended a phased implementation or pilot evaluation of the impact on measurement validity for a 2-year applicable period. Response: We appreciate commenters’ concerns and recommendations. We reiterate that reducing the applicable period to two years will continue to preserve reliability while ensuring that hospital performance metrics reflect more recent quality improvements and care practices. We note that prior to proposing to shorten the applicable period to 2 years, we assessed whether the reliability of the measures could reach a satisfactory level. In testing, all measures showed better between- hospital variance using the 2-year FFS and MA combined cohort as compared to the current measure specifications of a 3-year applicable period and the FFS- only cohort. The measure reliability remains robust despite the change from a 3-year period to a 2-year period for several key reasons. More low-volume hospitals meet the 25 or more criteria for reporting despite the reduction from 3 to 2 years of data due to the inclusion of MA admissions resulting in nea iod for several key reasons. More low-volume hospitals meet the 25 or more criteria for reporting despite the reduction from 3 to 2 years of data due to the inclusion of MA admissions resulting in nearly doubling of the annual cohort size. The combined effect is a roughly one-third increase in overall hospital volume. Empirical comparisons of the 3-year FFS-only cohort (July 2021–June 2024 FFS data) and the 2-year FFS+MA cohort (CY 2022 and CY 2023) showed that the median hospital volume and number of hospitals included for public reporting were similar to or higher in the 2-year FFS+MA cohort, and median reliability scores improved for every measure except THA/TKA (for example, AMI (0.5589 for 2-year FFS+MA versus 0.4458 for 3-year FFS-only) and HF (0.5832 for 2-year FFS+MA versus 0.4914 for 3-year FFS-only)). Our analysis of THA/TKA procedures under the combined FFS+MA cohort did not demonstrate the anticipated volume increases. This outcome can be attributed to the ongoing migration of these procedures from inpatient to outpatient care settings, reflecting broader trends in healthcare delivery patterns. Given the evolving nature of care delivery for these procedures, we acknowle of these procedures from inpatient to outpatient care settings, reflecting broader trends in healthcare delivery patterns. Given the evolving nature of care delivery for these procedures, we acknowledge uncertainty regarding VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00397 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36932 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations future volume trends and care setting distributions. The continued shift toward outpatient settings presents challenges for accurate volume projections and measure implementation. To ensure consistency across our quality measurement framework, the applicable period for TKA/THA measure with a 2-year applicable period ensures consistency and alignment with the program’s measure set. However, we intend to monitor the effects of the applicable period length for hospitals, including for low-volume hospitals, and make any future refinements as needed. Comment: A commenter did not support the proposal to reduce the applicable period from 3 years to 2 years stating that this change, along with the addi tals, and make any future refinements as needed. Comment: A commenter did not support the proposal to reduce the applicable period from 3 years to 2 years stating that this change, along with the addition of MA beneficiaries into the Hospital Readmissions Reduction Program measure set and the transition of the risk adjustment model from Hierarchical Condition Categories (HCCs) to individual ICD–10 codes, could increase hospitals’ risk of incurring penalties. This commenter expressed concern that these proposals did not include adequate transparency, impact modeling, or data reliability safeguards. Response: Including MA beneficiaries and enhancing the risk adjustment based on individual ICD–10 codes would generate a broader, more representative patient population with more precise and actionable insights for both the public and providers. Because of the expanded cohort of index admissions, we can obtain the same or better measure precision with a shorter applicable period. We note that we performed impact modeling, as shown in Table VI.K–02. of the proposed rule (90 FR 18287 through 18288) and reprinted below in this final rule. Furthermore, as discussed above in response to concer we performed impact modeling, as shown in Table VI.K–02. of the proposed rule (90 FR 18287 through 18288) and reprinted below in this final rule. Furthermore, as discussed above in response to concerns in the section that discusses the Modification of the Applicable Period for the Hospital Readmissions Reduction Program Measures Set, all measures displayed better between-hospital variance with the 2-year FFS+MA combined cohort compared to the current measure specifications of 3-year FFS-only cohort, more low-volume hospitals now meet the 25 or more criteria for reporting despite the shorter timeframe, MA inclusion nearly doubles the annual cohort size, resulting in roughly one- third increase in overall hospital volume despite the reduction from 3 to 2 years of data. CMS intends to monitor the effects of this change, particularly for low-volume hospitals, and will make refinements as needed. This represents a significant methodological improvement that maintains statistical reliability while providing more timely quality assessments by incorporating a broader patient population. After consideration of the public comments we received, we are finalizing our proposal to reduce the ap y while providing more timely quality assessments by incorporating a broader patient population. After consideration of the public comments we received, we are finalizing our proposal to reduce the applicable period from 3 years to 2 years, as proposed. b. Identification of Aggregate Payments for Each Condition/Procedure and All Discharges for FY 2027 and Subsequent Years When calculating the numerator (aggregate payments for excess readmissions), we determine the base operating DRG payment amount for an individual hospital for the applicable period for each condition/procedure using Medicare FFS inpatient claims from the MedPAR file with discharge dates that are within the applicable period. Under our established methodology, we use the update of the MedPAR file for each Federal fiscal year, which is updated 6 months after the end of each Federal fiscal year within the applicable period, as our data source. In identifying discharges for the applicable conditions/procedures to calculate the aggregate payments for excess readmissions, we apply the same exclusions to the claims in the MedPAR file as are applied in the measure methodology for each of the applicable conditions/procedur e the aggregate payments for excess readmissions, we apply the same exclusions to the claims in the MedPAR file as are applied in the measure methodology for each of the applicable conditions/procedures. For example, for the FY 2025 applicable period, this included the discharge diagnoses for each applicable condition/procedure based on the list of specific ICD–10–CM and ICD–10–PCS code sets, as applicable, for that condition/ procedure, as specified in the 2024 version of the measure methodology reports.192 192 CMS Quality Net. Available at: https:// qualitynet.cms.gov/inpatient/measures/ readmission/methodology. In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18286 through 18288), we proposed to include payment data for Medicare FFS and MA beneficiaries that meet the criteria as previously described for each applicable condition/procedure to calculate the aggregate payments for excess readmissions. We would rely on the MedPAR and/or the latest available data source that would provide the most up- to-date comprehensive information on payment information for Medicare FFS and MA beneficiaries. This proposal resulted from our proposal to include MA beneficiaries in the Hospital Rea de the most up- to-date comprehensive information on payment information for Medicare FFS and MA beneficiaries. This proposal resulted from our proposal to include MA beneficiaries in the Hospital Readmissions Reduction Program measure set cohorts. We noted that § 412.152 defines the terms ‘‘aggregate payments for excess readmissions’’ and ‘‘excess readmissions ratio’’ (ERR) broadly enough to allow us to include MA beneficiaries in the calculation without requiring us to revise the regulatory definition. (1) Analysis of Estimated Impacts on Aggregate Payments In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18286 through 18288), to assess the expected impact on hospital payment adjustments resulting from the changes to the readmission measures, the ‘‘applicable period’’, and calculations for aggregate payments for excess readmissions, we estimated hospitals’ payment adjustment factors using the proposed measures updates to include MA data, the proposed 2-year applicable period, and the proposed updates to the calculations for aggregate payments for each condition/procedure to include MA data. In the proposed rule, we showed the estimated total Medicare savings under the current pa e proposed updates to the calculations for aggregate payments for each condition/procedure to include MA data. In the proposed rule, we showed the estimated total Medicare savings under the current payment adjustment factor calculations and the proposed payment adjustment factor calculations which would use a 2- year applicable period and include MA data in the ERR calculations and calculations for aggregate payments for each condition/procedure. Based on our analysis, the estimated average change in Medicare savings per hospital from the proposed updates was $15,579, with 1,424 hospitals having a greater penalty amount and 1,547 hospitals having the same or lower penalty amount. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00398 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36933 Our proposed rule analysis also assessed the impact of the proposed updates to the number of eligible hospitals, number and percentage of penalized hospitals, and penalties as a share of payments overall and by hospital characteristics. The the impact of the proposed updates to the number of eligible hospitals, number and percentage of penalized hospitals, and penalties as a share of payments overall and by hospital characteristics. The first and fifth columns in Table VI.K–02 of the proposed rule (90 FR 18287 through 18288) and reprinted in the table below indicate the total number of hospitals eligible for a penalty under the Hospital Readmissions Reduction Program. In FY 2025, approximately 3,000 subsection (d) hospitals were included in the Hospital Readmissions Reduction Program. Poorly performing hospitals included in the program may receive a penalty if they are non-Maryland subsection (d) hospitals with 25 or more eligible discharges for at least one measure during the applicable period. The second and sixth columns in the table indicated the total number of non- Maryland hospitals with available data for each characteristic that have an estimated payment adjustment factor less than 1 (that is, penalized hospitals). The third and seventh columns in the table indicated the estimated percentage of penalized hospitals among those eligible to receive a penalty by hospital characteristic. The fourth and eighth col s). The third and seventh columns in the table indicated the estimated percentage of penalized hospitals among those eligible to receive a penalty by hospital characteristic. The fourth and eighth columns in the table estimated the financial impact on hospitals by hospital characteristic, referred to as the penalty as a share of payments. The penalty as a share of payments is calculated as the sum of penalties for all hospitals with that characteristic over the sum of all base operating DRG payments for those hospitals. For example, under the current methodology, the penalty as a share of payments for urban hospitals is 0.42 percent, and with the proposed updates, the penalty as a share of payments for urban hospitals is 0.46 percent. This means that total penalties for all urban hospitals is 0.42 percent of total payments for urban hospitals under the current methodology and 0.46 percent with the proposed updates. Measuring the financial impact on hospitals as a percentage of total base operating DRG payments accounts for differences in the amount of base operating DRG payments for hospitals with the characteristic when comparing the financial impact of the program on different gr se operating DRG payments accounts for differences in the amount of base operating DRG payments for hospitals with the characteristic when comparing the financial impact of the program on different groups of hospitals. BILLING CODE 4120–01–P 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00399 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00400 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00401 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00402 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00403 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36938 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations As shown in TABLE VI.K–04, our analysis also assesses the impact of the newly finalized updates to the number of eligible hospitals, number and percentage of penalized hospitals, ules and Regulations As shown in TABLE VI.K–04, our analysis also assesses the impact of the newly finalized updates to the number of eligible hospitals, number and percentage of penalized hospitals, and penalties as a share of payments overall and by hospital characteristics. The first and fifth columns in the below table indicate the total number of hospitals eligible for a penalty under the Hospital Readmissions Reduction Program. In FY 2025, approximately 3,000 subsection (d) hospitals were included in the Hospital Readmissions Reduction Program. Poorly performing hospitals included in the program may receive a penalty if they are non-Maryland subsection (d) hospitals with 25 or more eligible discharges for at least one measure during the applicable period. The second and sixth columns in the table indicate the total number of non- Maryland hospitals with available data for each characteristic that have an estimated payment adjustment factor less than 1 (that is, penalized hospitals). The third and seventh columns in the table indicate the estimated percentage of penalized hospitals among those eligible to receive a penalty by hospital characteristic. The fourth and eighth colu s). The third and seventh columns in the table indicate the estimated percentage of penalized hospitals among those eligible to receive a penalty by hospital characteristic. The fourth and eighth columns in the table estimate the financial impact on hospitals by hospital characteristic, referred to as the penalty as a share of payments. The penalty as a share of payments is calculated as the sum of penalties for all hospitals with that characteristic over the sum of all base operating DRG payments for those hospitals. For example, under the current methodology (FY 2025), the penalty as a share of payments for urban hospitals is 0.42 percent, and with the newly finalized updates, the penalty as a share of payments for urban hospitals is 0.41 percent. This means that total penalties for all urban hospitals is 0.42 percent of total payments for urban hospitals under the current methodology (FY 2025) and 0.41 percent with the finalized updates. Measuring the financial impact on hospitals as a percentage of total base operating DRG payments accounts for differences in the amount of base operating DRG payments for hospitals with the characteristic when comparing the financial impact of t s a percentage of total base operating DRG payments accounts for differences in the amount of base operating DRG payments for hospitals with the characteristic when comparing the financial impact of the program on different groups of hospitals. BILLING CODE 4120–01–P 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00404 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00405 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00406 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00407 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00408 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36943 L. Hospital Value-Based Purchasing (VBP) Program 1. Background a. Overview For background on the Hospital VBP Program, we refer readers to the CMS websit , August 4, 2025 / Rules and Regulations 36943 L. Hospital Value-Based Purchasing (VBP) Program 1. Background a. Overview For background on the Hospital VBP Program, we refer readers to the CMS website at: https://www.cms.gov/ medicare/quality/initiatives/hospital- quality-initiative/hospital-value-based- purchasing. We also refer readers to our codified requirements for the Hospital VBP Program at 42 CFR 412.160 through 412.168. b. FY 2026 Program Year Payment Details Under section 1886(o)(7)(C)(v) of the Act, the applicable percent for the FY 2026 program year is 2.00 percent. Using the methodology we adopted in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53571 through 53573), we estimated in the proposed rule (90 FR 18289) that the total amount available for value-based incentive payments for FY 2026 is approximately $1.7 billion, based on the December 2024 update of the FY 2024 MedPAR file. As finalized in the FY 2013 IPPS/ LTCH PPS final rule (77 FR 53573 through 53576), we utilize a linear exchange function to translate this estimated amount available into a value- based incentive payment percentage for each hospital, based on its Total Performance Score (TPS). We are publish e a linear exchange function to translate this estimated amount available into a value- based incentive payment percentage for each hospital, based on its Total Performance Score (TPS). We are publishing proxy value-based incentive payment adjustment factors in Table 16 associated with this final rule (which is available via the internet on the CMS website). We note that these proxy adjustment factors will not be used to adjust hospital payments. These proxy value-based incentive payment adjustment factors were calculated using the proposed FY 2026 Hospital VBP program methodology and historical baseline and performance periods for the FY 2025 Hospital VBP Program and the SEP–1 measure. These proxy factors were calculated using the March 2025 update to the FY 2024 MedPAR file. The slope of the linear exchange function used to calculate these proxy factors was 4.5252441909, and the estimated amount available for value-based incentive payments to hospitals for FY 2026 remains approximately $1.7 billion. We stated our intent to include an update to this table, as Table 16A, with the FY 2026 IPPS/LTCH PPS final rule, to reflect changes based on the March 2025 update to the FY 2024 MedP ly $1.7 billion. We stated our intent to include an update to this table, as Table 16A, with the FY 2026 IPPS/LTCH PPS final rule, to reflect changes based on the March 2025 update to the FY 2024 MedPAR file and the finalized FY 2026 Hospital VBP program methodology as discussed in section VI.L.6. of the preamble of this final rule. We will add Table 16B to display the actual value-based incentive payment adjustment factors, exchange function slope, and estimated amount available for the FY 2026 Hospital VBP Program. We expect that Table 16B will be posted on the CMS website in Fall 2025. 2. Hospital VBP Program Measures a. Proposed Measure Updates to the Hospital-Level Risk-Standardized Complication Rate (RSCR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) (1) Background In the FY 2026 IPPS/LTCH PPS proposed rule (90 FR 18290 through 18291), we proposed to adopt substantive measure updates to the Hospital-level Risk-Standardized Complication Rate (RSCR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) (hereinafter referred to as the COMP–HIP–KNEE measure), beginning with the FY 2033 program ion Rate (RSCR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) (hereinafter referred to as the COMP–HIP–KNEE measure), beginning with the FY 2033 program year. We proposed these updates contingent on our adopting the same updates to the COMP–HIP–KNEE measure for use in the Hospital IQR Program beginning with the FY 2027 payment determination, which we discuss further in section X.C. of the preamble of this final rule. We adopted the COMP–HIP–KNEE measure in the FY 2015 IPPS/LTCH PPS final rule beginning with the FY 2019 program year for use in the Hospital VBP Program (79 FR 50062 through 50063). We previously adopted substantive updates to the COMP–HIP– KNEE measure in the FY 2024 IPPS/ LTCH PPS final rule (88 FR 59067 through 59070) to include index admission diagnoses and in-hospital comorbidity data from Medicare Part A claims which expanded the measure outcome to include 26 additional mechanical complications as identified from 10th revision of the International Classification of Diseases (ICD–10) codes. We continue to consider the clinical outcomes of the COMP–HIP– KNEE measure a high priority, providing important data on patient vision of the International Classification of Diseases (ICD–10) codes. We continue to consider the clinical outcomes of the COMP–HIP– KNEE measure a high priority, providing important data on patient safety and adverse events, which is why we proposed to adopt additional updates to the COMP–HIP–KNEE measure in the Hospital VBP Program under the Clinical Outcomes Domain beginning with the FY 2033 program year. In Table VI.L.-01, we illustrate the program years for which we have adopted the COMP–HIP–KNEE measure, and the modifications we previously adopted, as well as the additional modifications we proposed in the FY 2026 IPPS/LTCH PPS proposed rule. 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00409 Fmt 4701 Sfmt 4725 E:\FR\FM\04AUR2.SGM 04AUR2 / > H P G 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00410 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36945 We wish to emphasize that this measure has been an important patient safety measure that has d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36945 We wish to emphasize that this measure has been an important patient safety measure that has provided meaningful quality and patient safety information for patients on the hospital inpatient setting for a substantial period of time. Further, we are committed to continually improving quality and patient safety for as many patients as possible within the inpatient setting. Based on our evaluation of the endorsement criteria, the conditions for endorsement have been met. (4) Data Source, Submission and Public Reporting To continue to assess clinical outcomes, we proposed to adopt these measure updates to the COMP–HIP– KNEE measure in the Hospital VBP Program under the Clinical Outcomes Domain beginning with the FY 2033 program year, contingent on our adoption of these changes in the Hospital IQR Program as described in section X.C. of the preamble of this final rule. We stated that, if finalized, we would begin posting the updated measure data on the Compare tool beginning in July 2026, which would enable us to post data on the substantive updates to the measure for at least one if finalized, we would begin posting the updated measure data on the Compare tool beginning in July 2026, which would enable us to post data on the substantive updates to the measure for at least one year before the proposed adoption beginning with the April 1, 2029-March 31, 2031, performance period which is associated with the FY 2033 payment determination, as required by section 1886(o)(2)(C)(i) of the Act.202 We also proposed that the performance standards calculation methodology for the updated COMP–HIP–KNEE measure would be the same as that which we currently use for the measure. The performance standards for the updated measure for FY 2033 are not yet available. We invited public comment on this proposal. Below, we summarize the public comments that we received and our responses. Comment: Many commenters supported CMS’s plans to include MA patients in the COMP–HIP–KNEE measure contingent on adoption of this update in the Hospital IQR Program. The commenters noted that this cohort change will more fully capture care quality in the Medicare Program and more accurately reflect the care quality provided in hospitals with high proportions of MA patients. Response: We thank the co t change will more fully capture care quality in the Medicare Program and more accurately reflect the care quality provided in hospitals with high proportions of MA patients. Response: We thank the commenters for their support. Comment: Some commenters cautioned that CMS should ensure MA encounter data provides enough information to assess quality performance. Response: We have studied the feasibility of incorporating MA encounter data and concluded MA data are feasible for use in CMS’s claims- based hospital outcome measures. We refer readers to published methodology of incorporating MA inpatient data 203 for more information. We will continue monitoring MA encounter data as we incorporate it into the measure’s cohort. Comment: A commenter supported CMS’s proposal to update quality measure populations to include MA beneficiaries, though the commenter also expressed concern that the new population has the potential to shift performance distributions meaningfully if not accounted for in risk adjustment. The commenter stated that some areas of the country have lower MA penetration and benchmarks, which may impact those hospitals disproportionately. The commenter recommended CMS conti risk adjustment. The commenter stated that some areas of the country have lower MA penetration and benchmarks, which may impact those hospitals disproportionately. The commenter recommended CMS continue with the proposal and communicate benchmark adjustments transparently, while also ensuring the risk model fully reflects the population’s characteristics. Response: We thank the commenter for their support. We note that the risk adjustment model has been updated to account for case mix in both fee-for- service (FFS) and MA. The clinical variables included in the risk adjustment model were selected based on analyses using a combined FFS and MA cohort, approximately evenly split between FFS and MA beneficiaries. This approach ensures the model captures the key risk factors relevant to the combined population. The model includes an indicator variable for FFS versus MA enrollment status, which accounts for any potential differences in readmission risk between these groups. We found that the prevalence of clinical risk factors and their associations with readmission outcomes were similar across FFS and MA beneficiaries. Stratifying the model by FFS and MA did not yield meaningful improv e prevalence of clinical risk factors and their associations with readmission outcomes were similar across FFS and MA beneficiaries. Stratifying the model by FFS and MA did not yield meaningful improvements in performance, supporting the decision to model them together with an indicator variable. Finally, keeping FFS and MA patients together for purposes of this measure’s calculation will keep the hospitals’ total volume higher for more precise measure scores. We proposed for these changes to take effect beginning with the FY 2033 Hospital VBP Program year to provide time and data to monitor for any unintended consequences. We intend to provide hospitals with measure performance data with the expanded measure’s patient cohort based on data collected while the ‘Modification 2’ version of the measure is in use in the Hospital IQR Program via annual confidential hospital-specific reports beginning with the FY 2027 program year, as well as via annual Provider Participation Summary Reports under the Hospital VBP Program beginning with the FY 2033 program year. In addition, Hospital VBP Program performance standards for this measure will be published at least 60 days prior to the beginni under the Hospital VBP Program beginning with the FY 2033 program year. In addition, Hospital VBP Program performance standards for this measure will be published at least 60 days prior to the beginning of each applicable performance period as required by section 1886(o)(3)(C) of the Act. Comment: Several commenters supported improved measure reliability and accuracy by adding MA patients to the measure calculations, though urged caution given their questions about data collection. The commenters urged CMS to monitor MA data and its impact on quality measures carefully. A commenter expressed concern about data completeness due to the increased likelihood of MA patients having incomplete or missing Medicare Beneficiary Identifiers (MBIs) at the time of submission, which can lead to challenges in claims documentation. While supportive of adding MA data, the commenter stated hospitals could be penalized due to factors outside their control in high-penetration markets for MA beneficiaries. Response: As stated above, we have studied the feasibility of incorporating MA encounter data and concluded that MA data are feasible for use in CMS’s claims-based hospital outcome measures.204 We in Response: As stated above, we have studied the feasibility of incorporating MA encounter data and concluded that MA data are feasible for use in CMS’s claims-based hospital outcome measures.204 We intend to monitor the effects of the updated patient cohort for this measure carefully, including the impact of using MBIs, and will provide as much information as possible to participating hospitals. We would also like to clarify that the MA encounter data and FFS claims used in the measure are submitted by Medicare Advantage Organizations and providers, respectively, and already include MBIs. These data are processed and validated through CMS systems prior to being made available for use in quality measurement. Hospitals are not required to submit any additional data or ensure MBI completeness beyond their usual billing practices. As such, the inclusion of MA data does not introduce a new 202 We noted that this performance period would only be 2 years instead of 3 if the proposed updates to the COMP–HIP–KNEE measure, which includes shortening of the performance period, are adopted. of inpatient Medicare Advantage data for use in hospital outcome measures.’’ Health Services Research, vo o the COMP–HIP–KNEE measure, which includes shortening of the performance period, are adopted. of inpatient Medicare Advantage data for use in hospital outcome measures.’’ Health Services Research, vol. 59, issue 6. Available at: https:// doi.org/10.1111/1475-6773.14350. of inpatient Medicare Advantage data for use in hospital outcome measures.’’ Health Services Research, vol. 59, issue 6. Available at: https:// doi.org/10.1111/1475-6773.14350. 203 See Kyanko et. al. ‘‘Processing and validation 204 See Kyanko et. al. ‘‘Processing and validation VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00411 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k 36946 Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations responsibility for hospitals with respect to MBI submission. The modifications are intended to increase reliability and more accurately reflect the quality of care for both FFS and MA beneficiaries, thus providing hospitals more accurate data. We will continue working with hospitals to ensure that they fully understand any effects this change may have on their performance ass nd MA beneficiaries, thus providing hospitals more accurate data. We will continue working with hospitals to ensure that they fully understand any effects this change may have on their performance assessment under the Hospital VBP Program. Comment: A commenter supported the addition of MA beneficiaries to this measure, noting the measure is episode- specific and reflects all of the major complications that can arise following elective THA/TKA procedures. The commenter recommended CMS consider reporting the inverse complication rate in the future, or the rate without major complications, to support the public’s understanding of the measure’s results, along with volume of associated procedures and patient risk profiles. Response: We thank the commenter for this feedback and will consider it as we continue refining our public reporting policies in the future. Comment: Several commenters requested that CMS conduct a dry run with scoring reports or a phased-in approach showing how the change would affect hospitals’ performance before finalizing the update. The commenters requested that CMS provide a clearer understanding of data collections, assess the associated burden, and analyze pot e would affect hospitals’ performance before finalizing the update. The commenters requested that CMS provide a clearer understanding of data collections, assess the associated burden, and analyze potential shifts in performance. A few commenters opposing the proposed measure changes suggested, if we choose to move forward, CMS adopt a phased implementation approach focused on the Hospital IQR Program first, including a multi-cycle impact analysis, and postpone public reporting and payment adjustments. Response: We thank the commenters for this feedback. We would like to clarify that the inclusion of MA data does not require any additional data collection or submission from hospitals beyond what is already reported for administrative and billing purposes. Specifically, the MA encounter data used for this measure are submitted by Medicare Advantage Organizations (MAOs) to CMS. Hospitals that receive disproportionate-share hospital or medical education payments from Medicare are required to submit information-only claims for inpatient stays of MA beneficiaries for years already. Similarly, FFS claims are submitted through existing hospital billing processes. As such, the proposed mod to submit information-only claims for inpatient stays of MA beneficiaries for years already. Similarly, FFS claims are submitted through existing hospital billing processes. As such, the proposed modifications do not impose additional data submission burden on hospitals. We have also conducted testing to evaluate the effects of including MA data on the measure cohort and the results are detailed in the 2024 Readmission Measures Supplemental Methodology Report. This analysis found that, overall, more than 80% of hospitals remained in the same performance quintile or shifted by no more than one quintile after the addition of MA data. These findings suggest that the inclusion of MA data results in minimal disruption to hospital performance classification while offering a more comprehensive view of quality for hospitals serving both FFS and MA beneficiaries. As proposed, we are finalizing these changes to take effect beginning with the FY 2033 Hospital VBP Program year. Per section 1886(o)(2)(C)(i) of the Act, measures must be specified for use in the Hospital IQR Program and publicly reported for at least one year prior to use in the Hospital VBP Program. This updated measure is bein )(2)(C)(i) of the Act, measures must be specified for use in the Hospital IQR Program and publicly reported for at least one year prior to use in the Hospital VBP Program. This updated measure is being adopted in the Hospital IQR Program beginning with the FY 2027 payment determination, and hospitals will be able to preview their data on this measure in the Hospital IQR Program prior to it being publicly reported. This delay will give hospitals time and data to identify any performance impacts before this updated measure impacts payment under the Hospital VBP Program. We intend to continue to monitor and evaluate the performance of this measure for changes that may be a result of the measure updates, along with any unintended consequences. Comment: A couple of commenters agreed with the reasoning of the Endorsement & Maintenance Cost and Efficiency Committee for not reaching initial consensus on endorsement of the updated measure and expressed concern endorsement was ultimately granted in the appeal process, and recommended CMS reconsider the measure in the Hospital VBP Program. Response: On February 10, 2025,205 the Endorsement & Maintenance Cost and Efficiency Committee voted, an in the appeal process, and recommended CMS reconsider the measure in the Hospital VBP Program. Response: On February 10, 2025,205 the Endorsement & Maintenance Cost and Efficiency Committee voted, and did not reach consensus on this measure, resulting in the measure not being re-endorsed. The decision was appealed and the Appeals Committee unanimously voted to grant the appeal, overturning the initial endorsement decision and endorsing the measure with conditions. The two conditions for endorsement were: (1) explore the 205 Battelle—Partnership for Quality Measurement. (2025). Fall 2024 Cycle Endorsement and Maintenance (E&M) Technical Report: Management of Acute Events and Chronic Conditions. Available at: https://p4qm.org/articles/ now-available-final-fall-2024-e-m-reports. proportion of procedures done in the ambulatory surgical centers and hospital outpatient department setting and evaluate the need for adjustment based on the impact of case mix; and (2) explore additional approaches to the reliability assessment to account for low-volume facilities. Comment: A commenter, who generally supported CMS’s plans to include MA beneficiaries in the measure’s cohort, urged CMS to reco hes to the reliability assessment to account for low-volume facilities. Comment: A commenter, who generally supported CMS’s plans to include MA beneficiaries in the measure’s cohort, urged CMS to reconsider the utility of the measure in the Hospital VBP Program given complications may result from a variety of factors outside the hospital’s control. Response: We thank the commenter for their feedback and support. We continue to consider clinical outcomes for this measure a priority, including clinical outcomes for Medicare patients in MA, as the measure provides important patient safety and adverse events data to providers and patients. Empirically, fee for service and MA patients each represent approximately half of the cohort for this measure. The two groups have similar outcome rates, similar risk variable prevalence, and, with the addition of the MA indicator for risk adjustment, model performance and calibration was good in the combined cohort. Using the modified measure not only in the Hospital IQR Program, but also the Hospital VBP Program under which a portion of payments to hospitals is tied to measure performance, serves as an important incentive for quality improvement. C n the Hospital IQR Program, but also the Hospital VBP Program under which a portion of payments to hospitals is tied to measure performance, serves as an important incentive for quality improvement. Comment: A commenter expressed concerns with the use of mortality measures and the COMP–HIP–KNEE measure for low reliability results. The commenter suggested that none of those measures reached what the commenter described as the minimum acceptable threshold of 0.7 for reliability. Response: We thank the commenter for their feedback. The measure developer conducted rigorous testing and concluded that the addition of MA patients into the measure’s cohort, in conjunction with the performance period changes, resulted in 75 percent of hospitals exceeding a 0.6 reliability score. Based on measures in the program, a 0.7 reliability score does not represent the minimum threshold for a measure’s reliability in the Hospital VBP Program, and we note further that the CBE describes 0.6 as the accepted threshold for reliability when evaluating quality measures.206 This result demonstrates the proposed measure 206 Table 4, Endorsement and Maintenance (E&M) Guidebook, June 2025. Partnership for Qualit threshold for reliability when evaluating quality measures.206 This result demonstrates the proposed measure 206 Table 4, Endorsement and Maintenance (E&M) Guidebook, June 2025. Partnership for Quality Measurement. Available at: https://www.p4qm.org/ e-m-guidebook/e-m/e-m-guidebook-version-3-0. VerDate Sep 2014 00:36 Aug 02, 2025 Jkt 265001 PO 00000 Frm 00412 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR2.SGM 04AUR2 2 S E L U R h t i w D O R P 4 4 1 S 7 W 9 K S D n o d n o m m a h k Federal Register / Vol. 90, No. 147 / Monday, August 4, 2025 / Rules and Regulations 36947 updates balance a focus on more recent data with a sufficiently reliable measure calculation that accurately reflects the quality of care provided by hospitals. Comment: Some commenters opposed inclusion of MA data in quality measure cohorts until hospitals can validate and become comfortable with the data. While the commenters acknowledged MA enrollment is now over 50 percent of Medicare beneficiaries, the commenters stated that MA encounter data is less accessible and sometimes less accurate than FFS claims data. The commenters also noted that MA plans often use their own utilization management tools like lengthy authorizat MA encounter data is less accessible and sometimes less accurate than FFS claims data. The commenters also noted that MA plans often use their own utilization management tools like lengthy authorization processes that can alter care patterns and recommended that CMS implement a transition period before fully including MA data in measurement. Other commenters requested that CMS allow time for hospitals to review MA performance data to understand how their performance cohorts have changed, stating that hospitals need time to determine MA patient data will not skew their performance assessments due to issues beyond the hospital’s control. The commenters requested CMS delay implementation until CMS can provide more information for hospital’s review and understanding or reconsider the proposal entirely. Response: The Hospital VBP Program intends to drive quality improvement for the entire Medicare population and by extension, to all patients served by hospitals. As MA enrollment grows, it becomes necessary to expand the cohort population to more accurately reflect the quality of care for all beneficiaries. As stated earlier, we conducted testing to evaluate the effects of including MA becomes necessary to expand the cohort population to more accurately reflect the quality of care for all beneficiaries. As stated earlier, we conducted testing to evaluate the effects of including MA data on the measure cohort and found more than 80% of hospitals remained in the same performance quintile or shifted by no more than one quintile after the addition of MA data. These findings suggest that the inclusion of MA data results in minimal disruption to hospital performance classification while offering a more comprehensive view of quality for hospitals serving both FFS and MA beneficiaries. CMS is finalizing changes to the COMP–HIP–KNEE measure’s cohort to take effect with the FY 2033 Hospital VBP Program year, following their implementation in the Hospital IQR Program beginning with the FY 2027 payment determination. This effective date will provide hospitals with sufficient time to understand if and how the new patient cohort will affect their performance assessment under the Hospital VBP Program. Comment: Several commenters Response: We intend to provide cautioned CMS about incorporating MA outcomes in FFS quality programs, arguing this policy could lead to duplicative pen ospital VBP Program. Comment: Several commenters Response: We intend to provide cautioned CMS about incorporating MA outcomes in FFS quality programs, arguing this policy could lead to duplicative penalties on hospitals. The commenters explained MA plans have their own value-based programs and MA patients often experience different post-acute care options due to MA plan structures. A commenter encouraged us to analyze performance variations between MA and FFS beneficiaries and provide annual confidential feedback reports to hospitals on any differences. Another commenter suggested that CMS work to develop improved measures of key outcomes rather than using MA data and requested that it not publicly report current measures by insurance type as such reporting contradicts the stated purpose of combining the populations. Response: We thank the commenters for sharing their concerns and we intend to monitor the potential for differences between the MA and FFS populations’ on this measure. While we understand MA plans have their own quality program, we remain concerned that omitting MA patients from the measure provides an incomplete picture of the care quality provided to Medicare benefi ile we understand MA plans have their own quality program, we remain concerned that omitting MA patients from the measure provides an incomplete picture of the care quality provided to Medicare beneficiaries by participating hospitals. As we stated in the proposed rule (90 FR 18290), the addition of MA data in the measure would approximately double the cohort size, and we have concluded that including these patients in the measure provides CMS, providers, patients, caregivers, and others a broader view of care quality. We appreciate the commenter’s concern about public reporting and will take it into account as we refine our public reporting policies in the future. Comment: Some commenters requested CMS release data on the modified THA/TKA measure and how performance changes with the addition of MA patients. The commenters were concerned that MA benefit design means hospitals will have less control over their MA patients’ care, especially due to prior authorization requirements. A commenter recommended that CMS tie outcomes to fee-for-service patient performance within the hospital’s control. The commenter explained that MA enrollees accept different benefit design than FFS patient