消除临床决策支持算法中的种族偏见:退伍军人健康管理局的使用案例。

IF 2.6 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Health Equity Pub Date : 2023-11-30 eCollection Date: 2023-01-01 DOI:10.1089/heq.2023.0037
Justin M List, Paul Palevsky, Suzanne Tamang, Susan Crowley, David Au, William C Yarbrough, Amol S Navathe, Craig Kreisler, Ravi B Parikh, Jessica Wang-Rodriguez, J Stacey Klutts, Paul Conlin, Leonard Pogach, Esther Meerwijk, Ernest Moy
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引用次数: 0

摘要

退伍军人健康管理局采用公平和循证原则来检查、纠正和消除使用可能存在偏见的临床方程和预测模型。我们通过四个实例讨论了这一过程、成功、挑战和下一步措施。我们详细介绍了取消估计肾功能种族修饰符的情况,并讨论了实现更公平的肺功能测试测量的步骤。我们详细介绍了在两个预测性临床建模工具中使用公平透镜的情况:阿片类药物风险缓解分层工具 (STORM) 和护理评估需求 (CAN) 预测模型。最后,我们将探讨如何在临床决策支持算法中促进种族健康公平。
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Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration.

The Veterans Health Administration uses equity- and evidence-based principles to examine, correct, and eliminate use of potentially biased clinical equations and predictive models. We discuss the processes, successes, challenges, and next steps in four examples. We detail elimination of the race modifier for estimated kidney function and discuss steps to achieve more equitable pulmonary function testing measurement. We detail the use of equity lenses in two predictive clinical modeling tools: Stratification Tool for Opioid Risk Mitigation (STORM) and Care Assessment Need (CAN) predictive models. We conclude with consideration of ways to advance racial health equity in clinical decision support algorithms.

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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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