在临床决策支持算法中消除算法种族偏见:来自退伍军人卫生管理局的用例
Justin M List1,2, Paul Palevsky3,4, Suzanne Tamang5,6
1VA Office of Health Equity, Washington, District of Columbia, USA.
Health equity
|December 11, 2023
概括
退伍军人卫生管理局正在消除临床工具中的基于种族的调整,以确保公平的患者护理. 这个倡议解决了功能,肺功能和风险预测算法的偏差,促进健康公平.
科学领域:
- 健康 公平 卫生 公平
- 临床信息学 临床信息学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 临床算法和预测模型可以延续健康差异.
- 退伍军人卫生管理局 (VHA) 致力于识别和减轻其医疗保健工具中的偏见.
- 之前在临床方程中使用种族修饰剂引起了对公平性的担忧.
研究的目的:
- 检查和消除在VHA中使用潜在偏差的临床方程和预测模型.
- 详细说明处理算法偏差的流程,成功,挑战和未来步骤.
- 在临床决策支持算法中推进种族健康公平.
主要方法:
- 应用公平和基于证据的原则来审查临床工具.
- 在估计功能计算中消除了种族修饰符.
- 在阿片类药物风险缓解 (STORM) 和护理评估需求 (CAN) 预测模型的分层工具中实施股权镜头.
- 制定更公平的肺功能测试测量策略.
主要成果:
- 在估计的功能中成功消除了种族修饰剂,这是减少种族偏见的重要一步.
- 在对肺功能检测应用公平考虑方面的进展.
- 在STORM和CAN预测模型中证明了股权镜头的应用,提高了它们的公平性.
- 识别算法偏差缓解中的关键过程和挑战.
结论:
- VHA的系统方法表明了致力于推进种族健康平等的承诺.
- 消除临床算法中的偏见组件对于公平的医疗保健服务至关重要.
- 持续的警和临床决策支持工具的调整是必要的,以确保公平性和改善患者的结果.
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