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Landscape of Area-Level Deprivation Measures and Other Approaches to Account for Social Risk and Social Determinants of Health in Health Care Payments

Publication Date
Joshua Breslau, Laurie Martin, Justin Timbie, Nabeel Qureshi, Deborah Zajdman

Improving health equity in the United States is a priority for the Biden-Harris Administration in order to address longstanding disparities in health outcomes. Health inequities can be conceptualized and measured as drivers of differences in health outcomes. These drivers begin upstream with structural discrimination which results in differences in social determinants of health (SDOH), health-related social needs (HRSN), access to care, and, finally, differential quality of care within the health care system. The Department of Health and Human Services (HHS) has focused research efforts on better understanding the social drivers of health inequities and developing policies to improve equity. A key policy question is what measures the federal government should use to target payments to screen patients for HRSN and refer them to appropriate services. It is important, therefore, to understand existing area-level indices in terms of their validity, the SDOH and HRSN components they reflect, their availability and timeliness, the geographic level for which they are calculated, and usefulness for focusing funding on communities with the greatest need.

To better understand the options for using area-level and/or administrative data to target Medicare payments to providers treating greater proportions of beneficiaries with HRSN, ASPE commissioned RAND to conduct three environmental scans of: (1) area-level indices of social risk, (2) measures used in government programs that target areas, providers, or populations with social risk, and (3) existing payment models that incorporate measures of social risk. The report finds that while there are many precedents for assessing social risk factors (SRF) in the study of health care and administration of health care systems in the United States, there remains considerable heterogeneity in how social risk is measured. Together, the scans highlight the variation in area-level indices for specific policy uses.

Product Type
Low-Income Populations
Location- & Geography-Based Data
County Data