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临床医生应该如何应对种族主义算法导致的医源性伤害?

How Should Clinicians Respond to Race-Based Algorithms as Sources of Iatrogenic Harm?

机构信息

Medical student in the UC Berkeley-UC San Francisco Joint Medical Program and a co-founder of the Institute of Healing and Justice in Medicine.

Physician and reproductive health advocate based in the greater Washington, DC area.

出版信息

AMA J Ethics. 2022 Aug 1;24(8):E720-728. doi: 10.1001/amajethics.2022.720.

Abstract

Some clinical algorithms use race as an epidemiological shorthand to "correct" for health determinants that are clinically influential but also variable because they are historical, social, cultural, or economic in origin. Such "correction factors" are both clinically and ethically relevant when their use reinforces racial essentialism and exacerbates racial health inequity. This commentary on a case in which the original vaginal birth after cesarean calculator is used argues that this and similar race-based algorithms should be considered sources of iatrogenic harm by undermining decision sharing in patient-clinician relationships and Black birthing peoples' rights to self-determination.

摘要

一些临床算法将种族用作流行病学的简写,以“纠正”具有临床影响力但因历史、社会、文化或经济起源而变化的健康决定因素。当这些“校正因素”的使用强化种族本质论并加剧种族健康不平等时,它们在临床和伦理上都是相关的。本文对一个案例进行了评论,该案例中使用了原始的剖宫产后阴道分娩计算器,认为这种和类似的基于种族的算法应该被视为医源性伤害的来源,因为它们破坏了医患关系中的决策共享以及黑人产妇的自决权。

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