论文标题

估计紧急普通手术中的种族差异

Estimating Racial Disparities in Emergency General Surgery

论文作者

Ben-Michael, Eli, Feller, Avi, Kelz, Rachel, Keele, Luke

论文摘要

黑人患者的一般手术结果比美国白人患者的研究文件更糟糕。在本文中,我们关注一个重要但较少的类别:紧急通用外科手术(EGS)疾病的手术治疗,它是指伤害是“内源性”的医疗紧急情况,例如爆发附录。我们的目标是使用纽约,佛罗里达州和宾夕法尼亚州医院索赔的行政数据库来评估EGS治疗后共同结果的种族差异,并了解差异在多大程度上归因于患者水平的风险因素与医院水平的因素。为此,我们使用一类线性加权估计器,这些估计量将重量重量的患者与黑人患者具有相似的基线特征分布。该框架筑巢了许多常见的方法,包括匹配和线性回归,但在控制组之间的不平衡,最小化外推和减少计算时间方面具有重要的优势。将这种方法应用于索赔数据时,我们发现差异估计,调整医院仅小于调整患者基线特征的估计,这表明医院特异性因素是EGS结果中种族差异的重要驱动因素。

Research documents that Black patients experience worse general surgery outcomes than white patients in the United States. In this paper, we focus on an important but less-examined category: the surgical treatment of emergency general surgery (EGS) conditions, which refers to medical emergencies where the injury is "endogenous," such as a burst appendix. Our goal is to assess racial disparities for common outcomes after EGS treatment using an administrative database of hospital claims in New York, Florida, and Pennsylvania, and to understand the extent to which differences are attributable to patient-level risk factors versus hospital-level factors. To do so, we use a class of linear weighting estimators that re-weight white patients to have a similar distribution of baseline characteristics as Black patients. This framework nests many common approaches, including matching and linear regression, but offers important advantages over these methods in terms of controlling imbalance between groups, minimizing extrapolation, and reducing computation time. Applying this approach to the claims data, we find that disparities estimates that adjust for the admitting hospital are substantially smaller than estimates that adjust for patient baseline characteristics only, suggesting that hospital-specific factors are important drivers of racial disparities in EGS outcomes.

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