Promoting Anti-Racism in Clinical Practice: Lessons Learned in the Process of Removing the Race Coefficient from the Estimated Glomerular Filtration Rate Algorithm.

IF 2.6 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Health Equity Pub Date : 2023-11-30 eCollection Date: 2023-01-01 DOI:10.1089/heq.2023.0095
Carla Boutin-Foster, Camille A Clare, Jameela Yusuff, Moro Salifu
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引用次数: 0

Abstract

Background: Promoting anti-racism in medicine entails naming racism as a contributor to health inequities and being intentional about changing race-based practices in health care. Unscientific assumptions about race have led to the proliferation of race-based coefficients in clinical algorithms. Identifying and eliminating this practice is a critical step to promoting anti-racism in health care. The New York City Department of Health and Mental Hygiene (NYC-DOHMH) formed the Coalition to End Racism in Clinical Algorithms (CERCA), a health system consortium charged with eliminating clinical practices and policies that perpetuate racism.

Objective: This article describes the process by which an academic medical center guided by the NYC-DOHMH tackled race-based clinical algorithms.

Methods: Multiple key interested parties representing department chairs, hospital leaders, researchers, legal experts, and clinical pathologists were convened. A series of steps ensued, including selecting a specific clinical algorithm to address, conducting key informant interviews, reviewing relevant literature, reviewing clinical data, and identifying alternative and valid algorithms.

Key outcomes: Given the disproportionately higher rates of chronic kidney disease risk factors, estimated glomerular filtration rate (eGFR) was prioritized for change. Key informant interviews revealed concerns about the clinical impact that removing race from the equation would have on patients, potential legal implications, challenges of integrating revised algorithms in practice, and aligning this change in clinical practice with medical education. This collaborative process enabled us to tackle these concerns and successfully eliminate race as a coefficient in the eGFR algorithm.

Conclusions: CERCA serves as a model for developing academic and public health department partnerships that advance health equity and promote anti-racism in practice. Lessons learned can be adapted to identify, review, and remove the use of race as a coefficient from other clinical guidelines.

促进临床实践中的反种族主义:从估算肾小球滤过率算法中去除种族系数的过程中汲取的经验教训》。
背景:在医学中提倡反种族主义,就必须指出种族主义是造成健康不平等的原因之一,并有意识地改变医疗保健中基于种族的做法。对种族的不科学假设导致临床算法中基于种族的系数激增。识别并消除这种做法是在医疗保健中促进反种族主义的关键一步。纽约市卫生和心理卫生局(NYC-DOHMH)成立了 "消除临床算法中的种族主义联盟"(CERCA),这是一个医疗系统联盟,负责消除使种族主义长期存在的临床实践和政策:本文描述了一个学术医疗中心在纽约市卫生部的指导下处理基于种族的临床算法的过程:方法:召集了多个主要相关方,包括科室主任、医院领导、研究人员、法律专家和临床病理学家。随后采取了一系列步骤,包括选择要解决的特定临床算法、进行关键信息提供者访谈、审查相关文献、审查临床数据以及确定替代的有效算法:鉴于慢性肾脏病风险因素的比例过高,估计肾小球滤过率(eGFR)被优先考虑进行修改。对主要信息提供者的访谈显示,他们担心将种族从等式中剔除会对患者产生临床影响、潜在的法律影响、在实践中整合修订算法的挑战,以及将临床实践中的这一变化与医学教育相结合。这一合作过程使我们能够解决这些问题,并成功地在 eGFR 算法中取消了种族这一系数:结论:CERCA 是发展学术界与公共卫生部门合作关系的典范,可在实践中促进健康公平和反种族主义。吸取的经验教训可用于识别、审查和消除其他临床指南中使用种族作为系数的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Health Equity
Health Equity Social Sciences-Health (social science)
CiteScore
3.80
自引率
3.70%
发文量
97
审稿时长
24 weeks
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