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种族指标在临床预测中的应用:决策、患者健康和公平性。

Using measures of race to make clinical predictions: Decision making, patient health, and fairness.

机构信息

Department of Economics, Northwestern University, Evanston, IL 60208.

Institute for Policy Research, Northwestern University, Evanston, IL 60208.

出版信息

Proc Natl Acad Sci U S A. 2023 Aug 29;120(35):e2303370120. doi: 10.1073/pnas.2303370120. Epub 2023 Aug 22.

Abstract

The use of race measures in clinical prediction models is contentious. We seek to inform the discourse by evaluating the inclusion of race in probabilistic predictions of illness that support clinical decision making. Adopting a static utilitarian framework to formalize social welfare, we show that patients of all races benefit when clinical decisions are jointly guided by patient race and other observable covariates. Similar conclusions emerge when the model is extended to a two-period setting where prevention activities target systemic drivers of disease. We also discuss non-utilitarian concepts that have been proposed to guide allocation of health care resources.

摘要

种族测量在临床预测模型中的使用是有争议的。我们通过评估种族在支持临床决策的疾病概率预测中的纳入情况来推动这一讨论。我们采用静态功利主义框架将社会福利形式化,结果表明,当临床决策同时由患者种族和其他可观察的协变量共同指导时,所有种族的患者都将受益。当模型扩展到包括针对疾病系统驱动因素的预防活动的两期设置时,也会得出类似的结论。我们还讨论了一些被提议用于指导医疗资源分配的非功利主义概念。

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