Association Between Community-Level Social Risk and Spending Among Medicare Beneficiaries: Implications for Social Risk Adjustment and Health Equity

IMPORTANCE: Payers are increasingly using approaches to risk adjustment that incorporate community-level measures of social risk with the goal of better aligning value-based payment models with improvements in health equity. OBJECTIVE: To examine the association between community-level social risk and health care spending and explore how incorporating community-level social risk influences risk adjustment for Medicare beneficiaries. DESIGN, SETTING, AND PARTICIPANTS: Using data from a Medicare Advantage plan linked with survey data on self-reported social needs, this cross-sectional study estimated health care spending health care spending was estimated as a function of demographics and clinical characteristics, with and without the inclusion of Area Deprivation Index (ADI), a measure of community-level social risk. The study period was January to December 2019. All analyses were conducted from December 2021 to August 2022. EXPOSURES: Census block group–level ADI. MAIN OUTCOMES AND MEASURES: Regression models estimated total health care spending in 2019 and approximated different approaches to social risk adjustment. Model performance was assessed with overall model calibration (adjusted R(2)) and predictive accuracy (ratio of predicted to actual spending) for subgroups of potentially vulnerable beneficiaries. RESULTS: Among a final study population of 61 469 beneficiaries (mean [SD] age, 70.7 [8.9] years; 35 801 [58.2%] female; 48 514 [78.9%] White; 6680 [10.9%] with Medicare-Medicaid dual eligibility; median [IQR] ADI, 61 [42-79]), ADI was weakly correlated with self-reported social needs (r = 0.16) and explained only 0.02% of the observed variation in spending. Conditional on demographic and clinical characteristics, every percentile increase in the ADI (ie, more disadvantage) was associated with a $11.08 decrease in annual spending. Directly incorporating ADI into a risk-adjustment model that used demographics and clinical characteristics did not meaningfully improve model calibration (adjusted R(2) = 7.90% vs 7.93%) and did not significantly reduce payment inequities for rural beneficiaries and those with a high burden of self-reported social needs. A postestimation adjustment of predicted spending for dual-eligible beneficiaries residing in high ADI areas also did not significantly reduce payment inequities for rural beneficiaries or beneficiaries with self-reported social needs. CONCLUSIONS AND RELEVANCE: In this cross-sectional study of Medicare beneficiaries, the ADI explained little variation in health care spending, was negatively correlated with spending conditional on demographic and clinical characteristics, and was poorly correlated with self-reported social risk factors. This prompts caution and nuance when using community-level measures of social risk such as the ADI for social risk adjustment within Medicare value-based payment programs.