Estimating Racial Disparities in Emergency General Surgery

TL;DR

This study assesses racial disparities in emergency general surgery outcomes using hospital claims data, revealing that hospital-specific factors significantly contribute to observed disparities between Black and white patients.

Contribution

Introduces a linear weighting estimator framework to analyze racial disparities, effectively controlling for patient and hospital-level factors in emergency general surgery outcomes.

Findings

Hospital factors largely explain disparities in EGS outcomes.

Adjusting for hospital effects reduces estimated racial disparities.

Method outperforms traditional approaches in controlling imbalance.

Abstract

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.