Tufts University School of Medicine, Boston, Massachusetts.
MassGeneral Brigham, Boston, Massachusetts.
JAMA Health Forum. 2023 Mar 3;4(3):e230266. doi: 10.1001/jamahealthforum.2023.0266.
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.
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.
Census block group-level ADI.
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 R2) and predictive accuracy (ratio of predicted to actual spending) for subgroups of potentially vulnerable beneficiaries.
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 R2 = 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.
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.
支付方越来越多地采用将社区层面的社会风险措施与基于价值的支付模式与改善健康公平的目标相结合的风险调整方法。
研究社区层面的社会风险与医疗保健支出之间的关系，并探讨在考虑社区层面的社会风险时如何影响医疗保险受益人的风险调整。
设计、地点和参与者：本研究使用医疗保险优势计划的数据与自我报告社会需求的调查数据进行关联，采用横断面研究方法，估计医疗保健支出，医疗保健支出被估计为人口统计学和临床特征的函数，包括和不包括区域贫困指数（ADI），这是社区层面社会风险的衡量指标。研究期间为 2019 年 1 月至 12 月。所有分析均于 2021 年 12 月至 2022 年 8 月进行。
普查块组级 ADI。
回归模型估计了 2019 年的总医疗保健支出，并模拟了不同的社会风险调整方法。通过对潜在弱势群体受益人的总体模型校准（调整后的 R2）和预测准确性（预测支出与实际支出的比率）来评估模型性能。
在最终的研究人群中，共有 61469 名受益人（平均[标准差]年龄 70.7[8.9]岁；35801[58.2%]女性；48514[78.9%]白人；6680[10.9%]有医疗保险-医疗补助双重资格；中位数[IQR]ADI 为 61[42-79]），ADI 与自我报告的社会需求呈弱相关（r=0.16），仅解释了支出观察变异的 0.02%。在人口统计学和临床特征的条件下，ADI 每增加一个百分点（即更多劣势），年支出就会减少 11.08 美元。直接将 ADI 纳入使用人口统计学和临床特征的风险调整模型中，并没有显著提高模型校准（调整后的 R2为 7.90%比 7.93%），也没有显著减少农村受益人和自我报告社会需求负担较重的受益人的支付不平等。对居住在 ADI 较高地区的双重合格受益人的预测支出进行事后调整，也没有显著减少农村受益人和有自我报告社会需求的受益人的支付不平等。
在这项对医疗保险受益人的横断面研究中，ADI 解释了医疗保健支出变化的很小一部分，与基于人口统计学和临床特征的支出呈负相关，与自我报告的社会风险因素相关性较差。这在使用医疗保险基于价值的支付计划中的社区层面的社会风险措施（如 ADI）进行社会风险调整时，需要谨慎和细致。
