2023-07115.pdf

12APR2ddrumheller on DSK120RN23PROD with RULES222288 Federal Register / Vol. 88, No. 70 / Wednesday, April 12, 2023 / Rules and Regulations 159https://www.aspe.hhs.gov/sites/default/files/ migrated_ legacy_ files/171041/ ASPESESRTCfull.pdf?_ ga=2.49530854.1703779054.1662938643-470268562.1638986031. 160Beckett MK, Martino SC, Agniel D, Mathews M, Hudson Scholle S, James C, Wilson-Frederick S, Orr N, Darabidian B, Elliott MN. (2021). Distinguishing neighborhood and individual social risk factors in health care Health Services Research: 114. 161https://www.govinfo.gov/content/pkg/FR- 2022-11-18/pdf/2022-23873.pdf. 162Social deprivation index (SDI). Robert Graham CenterPolicy Studies in Family Medicine & Primary Care. (2018, November 5). Accessed 2/23/ 23, from https://www.graham-center.org/rgc/maps- data-tools/sdi/social-deprivation-index.html. 163Goodman DC, Mick SS, Bott D, et al. Primary care service areas: a new tool for the evaluation of primary care services. Health Services Research 2002; 38(1 Pt 1):287309. doi: 10.1111/1475 6773.00116. 164Herb J, Dunham L, and Stitzenberg K. A comparison of area-level socioeconomic status indices in colorectal cancer care. J Surg Res 2022; 280:304311. 165Social deprivation index (SDI). Robert Graham CenterPolicy Studies in Family Medicine & Primary Care. (2018, November 5). Accessed 2/23/ 23, from https://www.graham-center.org/rgc/maps- data-tools/sdi/social-deprivation-index.html. those who experience SRFs. A commenter stated that focusing on limited SRFs ignores other SRFs where there are disparities and requested a timeline for the inclusion of additional SRFs in the HEI reward. Another commenter recommended including additional SRFs beginning with the 2027 Star Ratings or as soon as possible. Response: CMS appreciates these suggestions and will consider including additional SRFs with data readily available at this time, such as rurality and gender, in the HEI reward methodology in the future. Other SRFs will be considered over time as data become available to measure the specified SRFs. The addition of SRFs would be proposed through notice-and- comment rulemaking. While it is true that not all populations with SRFs are captured in the HEI reward we proposed and are finalizing in this rule, CMS does not believe this biases the HEI reward. Health plans should strive to perform well among all populations with SRFs regardless of whether they are included in the HEI reward. We see differences in performance for the SRFs included in the HEI reward. For example, prior research has shown that dual eligibility is one of the most influential predictors of poor health outcomes, and disability is also an important risk factor linked to health outcomes.159 Comment: Several commenters suggested using the ADI, the Social Vulnerability Index (SVI), or the Social Deprivation Index (SDI) in the HEI instead of LIS/DE and disabled status. A commenter recommended that CMS continue to monitor different indices that measure socioeconomic status and adopt them if they are found to be more accurate measures than the ADI. Response: We will continue to consider additional SRFs for the HEI reward over time through notice-and- comment rulemaking. As we noted in the preamble to the proposed rule, consistent with literature on the ADI, and other neighborhood-based indices,160our analyses showed that for the Part C and D Star Ratings measures, the ADI explains very little of the variation in the quality of care received beyond enrollee-level LIS/DE and disability information. The ADI is more useful in situations where there is a lack of beneficiary-level quality performance data, which is the case for the MSSP, for example. The MSSPs health equity adjustment applies to Accountable Care Organizations (ACOs) that report the all- payer/patient electronic clinical quality measures (eCQMs) or Merit-based Incentive Payment System (MIPS) CQMs; these measures are reported in aggregate, so beneficiary-level data are not readily available. The MSSP adopted a health equity adjustment that will upwardly adjust an ACOs quality performance score to reward ACOs that report all-payer eCQMs/MIPS CQMs, and are high performing on quality and serve a high proportion of underserved beneficiaries. The health equity adjustment adds up to 10 bonus points to the ACOs MIPS quality performance category score based on the percentage of the ACOs assigned beneficiaries who are LIS and/or DE and reside in census blocks with high ADI as described at 87 FR 69781.161Since the MSSP does not have Medicare-only beneficiary-level data linked to the quality performance data, CMS does not stratify the quality measure data by LIS/DE and disability status and analyze performance like we can for the Part C and D Star Ratings program. In the CY 2023 Advance Notice, we solicited feedback on the use of the ADI in the HEI reward methodology. At that time there was limited support for adding the ADI to the index. A number of concerns were raised, including that the ADI does not always reflect some of the more deprived areas; it does not adequately distinguish between areas that have both extreme poverty and extreme wealth; and it is not fully representative of systemic disparities for historically marginalized communities. There was also concern that including the ADI may create incentives for plans to focus on certain geographic areas versus focusing on improving care for those with the greatest needs. The SVI was designed to identify communities at increased risk of negative impacts from natural disasters and infectious disease outbreaks that require community-level response and is calculated at both the census tract and county level. Similar to other geography-based measures of social risk, the SVI is constructed using census data on socioeconomic status, household composition and disability, minority status and language, and housing and transportation characteristics. The Social Deprivation Index (SDI) was developed to identify the extent of disadvantage in small geographic areas and assess the association of level of disadvantage with health outcomes and health inequities. The SDI is a composite of sociodemographic characteristics, including poverty, education, unemployment, housing characteristics, household composition, and car ownership.162It is constructed at the county, census tract, aggregated Zip Code Tabulation Areas, and Primary Care Service Area163levels using 5-year estimates from the American Community Survey. Studies have shown that different geography-based measures of social risk have very similar associations with measures of quality of care and health outcomes.164However, for the Part C and D Star Ratings measures, geography-based indices of social risk do not substantively explain variation in care received beyond beneficiary-level SRFs such as dual- eligibility for Medicare and Medicaid, receipt of the Part D LIS, and disability as the original reason for Medicare eligibility,165which are used in the HEI. Comment: A commenter questioned why CMS decided against using the ADI in the HEI reward but is using the ADI as a factor in calculating the health equity adjustment in the MSSP. Response: The ADI is more useful in situations where there is a lack of beneficiary-level quality performance data, which is the case for the MSSP. Unlike for the Part C and D Star Ratings program, the MSSPs health equity adjustment is only available to those ACOs that report aggregate quality data for all-payer eCQMs/MIPS CQMs. For the HEI reward, CMS has access to beneficiary-level data on each quality measure included in the HEI and can match that beneficiary-level information to dual eligibility, LIS, and disability status. As we noted in the proposed rule, our analyses suggest that ADI explains little variation in care received beyond beneficiary-level LIS/DE and disability information for the Part C and D Star Ratings measures. VerDate Sep<11>2014 21:20 Apr 11, 2023 Jkt 259001 PO 00000 Frm 00170 Fmt 4701 Sfmt 4700 E:\FR\FM\12APR2.SGM 12APR2ddrumheller on DSK120RN23PROD with RULES222289 Federal Register / Vol. 88, No. 70 / Wednesday, April 12, 2023 / Rules and Regulations 166https://www.aspe.hhs.gov/sites/default/files/ migrated_ legacy_ files/171041/ ASPESESRTCfull.pdf?_ ga=2.49530854.1703779054.1662938643-470268562.1638986031. Similar to our goals for the HEI reward in terms of creating incentives for MA plans, cost plans, and Part D plan sponsors to perform well among enrollees with certain SRFs, the MSSP adopted a health equity adjustment that will upwardly adjust an ACOs quality performance score to reward high quality performance across all populations served by an ACO; encourage all ACOs to treat underserved populations; provide an incentive for ACOs to provide high quality care to all of the populations they serve; and ensure there are not incentives for ACOs to avoid underserved populations as CMS transitions to all-payer eCQMs/ MIPS CQMs as described at 87 FR 69839. Comment: A commenter raised concerns about using dual eligibility, LIS, and disability as the SRFs including in the HEI reward. The commenter stated there is mixed evidence on the effectiveness of these variables as indicators for health equity and noted issues with comparability given state-by-state differences in Medicaid eligibility criteria. Response: The HEI reward methodology we proposed not only includes dual eligibility (which could differ by state), but it also includes enrollees who apply for an LIS subsidy (which allows us to capture enrollees whose income and resources are limited) and disability status. Prior research has shown that dual eligibility is one of the most influential predictors of poor health outcomes, and disability is also an important risk factor linked to health outcomes.166Further, we set the minimum percentage of enrollees with the specified SRFs at the relatively low bar of one-half the contract-level median in part to address geographic variation in enrollment. Comment: Some commenters stated that large plans may serve many enrollees with SRFs but not meet the percentage of enrollees with the specified SRFs thresholds to qualify for the HEI reward, and some commenters recommended including thresholds for both the total number of enrollees as well as the percentage of enrollees. A commenter stated that larger plans not meeting the enrollment thresholds set for the HEI for enrollees with specified SRFs may be disincentivized from improving health equity even if they have a significant number of members experiencing SRFs, and another commenter stated that enrollees with SRFs will be overlooked if they are in plans that serve a significant SRF population but do not meet the thresholds. A commenter believes that an unintended consequence of our proposed methodology is that plans will not be eligible for an HEI reward due to the limited number of beneficiaries with those SRFs, and recommended that all plans be eligible for an HEI reward even if the proportion of their members with the specified SRFs is low. This commenter also stated that all plans should be working to improve the care for members with SRFs even if the proportion of enrollees with the specified SRFs does not meet the specifications to be eligible for the HEI reward. Response: CMS believes all plans should work to improve health equity regardless of whether they qualify for the HEI reward. Further, improving performance among members with SRFs will improve performance on Star Ratings measures even in the case where plans do not qualify for the HEI reward. One of the goals CMS considered when developing the HEI reward was to avoid rewarding contracts that may do well among enrollees with the SRFs included in the HEI but serve few enrollees with those SRFs relative to their total enrollment, making it easier to do well. If a number, rather than a percentage, of enrollees with the specified SRFs were used as the threshold for qualifying for the HEI reward, this goal would not be met. Larger contracts might be able to meet a minimum number threshold even though they serve a relatively small number of enrollees with the specified SRFs compared to their total enrollment. This would make it easier for these contracts to do well among these enrollees. Additionally, based on current data, few contracts that do not meet the percentage of enrollees with the specified SRFs threshold serve a large number of LIS/DE/disabled enrollees. In simulations using data from the 2021 Star Ratings data, we see that, on average, 15 percent of enrollees are LIS/ DE/disabled in MA and cost contracts that do not meet the minimum percentage of LIS/DE/disabled enrollees to be eligible for the HEI reward; 5 percent of enrollees are LIS/DE/disabled in PDP contracts that do not meet the minimum percentage of LIS/DE/ disabled enrollees to be eligible for the HEI reward. Thus, most contracts that do not meet the percentage of enrollees with the specified SRFs threshold would also not meet a threshold based on a number of enrollees with the specified SRFs. Additionally, we note that contracts that serve a low percentage of LIS/DE/disabled enrollees tend to perform well in Star Ratings. Contracts are not penalized for not meeting the percentage of enrollees with the specified SRFs threshold. As the