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色盲算法:新冠疫情时代的种族主义。

Colorblind Algorithms: Racism in the Era of COVID-19.

机构信息

The Children's Hospital of Philadelphia, Department of Child & Adolescent Psychiatry and Behavioral Sciences, Philadelphia, PA, USA.

Yale University School of Medicine, Department of Psychiatry, New Haven, CT, USA.

出版信息

J Natl Med Assoc. 2020 Oct;112(5):550-552. doi: 10.1016/j.jnma.2020.05.010. Epub 2020 Jun 17.

Abstract

This commentary offers a critique of the recent policy document issued by White et al. (2020) to guide critical care resource (e.g. ventilators) allocation during public health emergencies such as COVID-19. We argue that, if disseminated widely, this criteria would result in a racially inequitable resource distribution in the current COVID-19 crisis. We link the White et al. (2020) resource distribution protocol to other "colorblind" healthcare algorithms that have relied on seemingly objective but fundamentally biased data, thereby reinforcing and exacerbating pre-existing racial health disparities. We suggest a health equity framework to ensure unbiased distribution of critical care resources during COVID-19 and in general practice.

摘要

这篇评论批评了 White 等人(2020 年)最近发布的政策文件,该文件旨在指导在 COVID-19 等公共卫生紧急情况下对重症监护资源(例如呼吸机)进行分配。我们认为,如果广泛传播,该标准将导致当前 COVID-19 危机中资源分配的种族不平等。我们将 White 等人(2020 年)的资源分配协议与其他依赖看似客观但实际上存在根本偏差的数据的“无差别”医疗保健算法联系起来,从而加强和加剧了先前存在的种族健康差距。我们建议采用健康公平框架,以确保在 COVID-19 期间以及在一般实践中公平分配重症监护资源。

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