Accounting for Social Risk Factors in Medicare Payment (2017) / Chapter Skim
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DS: Summary
DS: Summary
Pages 455-474
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From page 455... ...
Because current VBP programs do not account for social risk factors for poor health outcomes, these programs may underestimate the quality of care provided by providers disproportionally serving socially at-risk populations. Consequently, these providers may be more likely to fare poorly on quality rankings (Berenson and Shih, 2012; Elliott et al., in press; Gilman et al., 2014, 2015; Joynt and Jha, 2013a; Rajaram et al., 2015; Ryan, 2013; Shih et al., 2015; Williams et al., 2014)
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. If CMS chooses to account for social risk factors, it must first acquire accurate data on the social risk factors of Medicare beneficiaries.
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The committee also concluded that some indicators of social risk factors capture the basic underlying constructs and currently present practical challenges, but they are worth attention for potential inclusion in the longer term. These include • wealth, • acculturation, • gender identity and sexual orientation, • emotional and instrumental social support, and • environmental measures of residential and community context.
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If CMS collects new social risk factor data, it could design measures and data collection methodologies to ensure collection of accurate data that meet the needs of the intended method to account for those social risk factors in Medicare quality measurement and payment. New data collection would not be subject to the potentially substantial barriers of collaborating with other federal government agencies, but it would require substantial cost.
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and state agencies oversee and maintain and that could be linked to Medicare beneficiary data. This includes data that could be linked to Medicare beneficiary data at the individual level, arealevel data that could be used to describe a Medicare beneficiary's residential environment or serve as a proxy for individual effects, and data that could help CMS to determine how to elicit information on social risk factors from Medicare beneficiaries.
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They all capture social risk factor data that could be useful to CMS when determining how best to elicit information from Medicare beneficiaries on their social risk factors. The primary advantage of using administrative and survey data from other agencies is that these data sources contain substantial information on social risk factors, and data from these sources are collected using standardized and validated measures and methodologies.
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The committee notes that its focus is on social risk factors important for use in Medicare quality measurement and payment. The EHR may include information on social and behavioral risk factors important to the clinical encounter, but that would not be relevant or be the best source of data for application to Medicare performance measurement and payment.
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• Where social risk factors change over time and have clinical utility, requiring data collection through electronic health records or other types of provider reporting may be the best approach. • For social risk factors that reflect a person's context or environ ment, existing data sources that can be used to develop area-level measures should be considered.
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However, Medicare beneficiaries' place of birth could be collected either by CMS or via EHRs with relatively little burden to patients, providers and plans, or CMS. Nativity is a stable social risk factor, which supports one-time collection by CMS to reduce burden, but nativity also has clinical utility, which supports collection through EHRs.
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Marital/partnership status is a structural element of social relationships and an indicator of social support. CMS maintains data on marital status, because it is important for Social Security benefits, but CMS does not have partnership data.
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In the long term, research is needed on measurement and data collection for partnership. In particular, CMS could examine whether including partnership in any method to account for social risk factors that already includes marital status and living alone adds substantial additional precision and explanatory value.
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However, for the long term, because living arrangements can change rapidly for older adults and living alone has clinical utility as an indicator, living alone may best be captured in the clinical setting. CMS should develop standardized measures and methods for data collection through EHRs.
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Recommendation 6: The committee recommends that research be con ducted on the effect of acculturation, sexual orientation and gender identity, and environmental measures of residential and community context on health care outcomes of Medicare beneficiaries, and on methods to accurately collect relevant data in the Medicare population. Acculturation describes how much an individual adheres to the social norms, values, and practices of his or her own home country or ethnic group or to those of the United States (NASEM, 2016a)
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Thus, normative gender is a strong candidate for inclusion in methods to account for social risk factors in Medicare quality measurement and payment programs. However, the committee notes that gender is already included as a risk factor in clinical risk adjustments in Medicare.
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Table DS-1 summarizes the availability of data for social risk factor indicators that could be accounted for in Medicare payment programs. GENERAL CONCLUSIONS The committee identified several general conclusions for CMS in its overall approach to collecting data on social risk factors for use in Medicare payment.
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TABLE DS-1 Summary of Data Availability for Social Risk Factor Indicators 470
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Conclusion 3: Any specific social risk factor indicator may require a multimodal approach to data collection. Conclusion 4: Regardless of the source, research on how to accurately and reliably collect social risk factor data across different modes and in different settings will be needed.
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1988. Social relationships and health.
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From page 473... ...
2016a. Accounting for social risk factors in Medicare payment: Identifying social risk factors.
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