Racial disparities in healthcare expenditures are well-documented, yet the underlying drivers remain complex. This study develops a framework to decompose such disparities through shifts in the distributions of mediating variables, rather than treating race itself as a manipulable exposure. We define disparities as differences in covariate-adjusted outcome distributions across racial groups, and decompose the total disparity into a component attributable to differences in mediator distributions, and a residual component that remains after equalizing those distributions. Using data from the Medical Expenditures Panel Survey (MEPS), we examine the extent to which expenditure disparities would persist or be reduced if mediators such as socioeconomic status (SES), insurance access, health behaviors, or health status were equalized across racial groups. To ensure valid inference, we derive asymptotically linear estimators based on influence-function techniques and flexible machine learning, including super learners and a two-part model designed for the zero-inflated, right-skewed nature of expenditure data. Applying this framework to MEPS data from 2009 and 2016, substantial disparities were observed across all pairwise racial comparisons, with the largest gaps observed between non-Hispanic Whites and Hispanics in both years. Differences in SES and health status were the largest contributors to these disparities, with insurance access also playing a meaningful role, particularly for Hispanic populations, whereas health behaviors contributed minimally. Residual disparities persisted, especially in comparisons involving non-Hispanic Whites, suggesting the influence of unmeasured or structural factors.

翻译：种族在医疗支出上的差异已有充分文献记载，但其潜在驱动因素仍十分复杂。本研究提出一个框架，通过中介变量分布的变化来分解此类差异，而非将种族本身视为可操纵的暴露变量。我们将差异定义为调整协变量后不同种族群体的结果分布差异，并将总差异分解为两部分：一部分归因于中介变量分布的差异，另一部分为均衡中介分布后的残留差异。利用医疗支出面板调查（MEPS）数据，本研究考察了若中介变量（如社会经济地位（SES）、保险可及性、健康行为或健康状况）在种族间均衡后，支出差异将持续或缩小的程度。为确保推断的有效性，我们基于影响函数技术和灵活机器学习方法（包括超级学习器及专为零膨胀、右偏态支出数据设计的两部分模型）推导了渐近线性估计量。将该框架应用于2009年和2016年MEPS数据，所有种族配对比较中均观察到显著差异，其中非西班牙裔白人与西班牙裔之间的差距在两年中均为最大。社会经济地位和健康状况的差异是这些差异的最大贡献因素，保险可及性也对差异产生显著影响（尤其在西班牙裔人群中），而健康行为的贡献最小。残留差异依然存在（尤其在涉及非西班牙裔白人的比较中），表明未测量因素或结构性因素的作用。