Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration.
Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration.
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作者：
退伍军人健康管理局使用公平和循证原则来检查，纠正和消除使用可能有偏见的临床方程和预测模型。我们将通过四个示例讨论流程、成功案例、挑战和后续步骤。我们详细介绍了消除种族修饰估计肾功能，并讨论了步骤，以实现更公平的肺功能测试测量。我们详细介绍了在两种预测性临床建模工具中使用权益镜片：阿片类药物风险缓解分层工具（STORM）和护理需求评估（CAN）预测模型。最后，我们考虑的方式来推进种族健康公平的临床决策支持算法。
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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DOI：
10.1056/nejmoa1114248
发表时间：
2012-07-05
期刊：
The New England journal of medicine
影响因子：
--
作者：
Inker LA;Schmid CH;Tighiouart H;Eckfeldt JH;Feldman HI;Greene T;Kusek JW;Manzi J;Van Lente F;Zhang YL;Coresh J;Levey AS;CKD-EPI Investigators
通讯作者：
CKD-EPI Investigators
影响因子：
9.7
作者：
Fihn, Stephan D.;Francis, Joseph;Graham, Gail L.
通讯作者：
Graham, Gail L.
影响因子：
39.2
作者：
Dickson, Alyson L.;Daniel, Laura L.;Jackson, Elise;Zanussi, Jacy;Yang, Wenjian;Plummer, W. Dale;Dupont, William D.;Wei, Wei-Qi;Nepal, Puran;Hung, Adriana M.;Cox, Nancy J.;Van Driest, Sara L.;Feng, QiPing;Yang, Jun J.;Stein, C. Michael;Mosley, Jonathan D.;Chung, Cecilia P.
通讯作者：
Chung, Cecilia P.
影响因子：
9.6
作者：
Bhakta NR;Kaminsky DA;Bime C;Thakur N;Hall GL;McCormack MC;Stanojevic S
通讯作者：
Stanojevic S
影响因子：
2.3
作者：
Oliva, Elizabeth M.;Bowe, Thomas;Trafton, Jodie A.
通讯作者：
Trafton, Jodie A.