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种族而非性别与骨科住院医师项目录取有关。

Race, But Not Gender, Is Associated With Admissions Into Orthopaedic Residency Programs.

机构信息

Orthopaedic Surgery Department, Shriners for Children Medical Center at Pasadena, Pasadena, CA, USA.

Department of Orthopaedic Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Great Neck, NY, USA.

出版信息

Clin Orthop Relat Res. 2022 Aug 1;480(8):1441-1449. doi: 10.1097/CORR.0000000000001553. Epub 2022 Dec 20.

DOI:10.1097/CORR.0000000000001553
PMID:33229901
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9278929/
Abstract

BACKGROUND

Orthopaedic surgery is one of the most competitive but least diverse surgical specialties, with ever-increasing academic achievements (such as test scores) shown by applicants. Prior research shows that white applicants had higher United States Medical Licensing Exam (USMLE) Step 1 and Step 2 Clinical Knowledge scores as well as higher odds of Alpha Omega Alpha status compared with Black, Hispanic, and other applicant groups. Yet, it still remains unknown whether differences in application metrics by race/ethnicity sufficiently explain the underrepresentation of certain racial or ethnic minority groups in orthopaedic residency programs.

QUESTIONS/PURPOSES: In this study, we sought to determine (1) the relative weight of academic variables for admission into orthopaedic residency, and (2) whether race and gender are independently associated with admission into an orthopedic residency.

METHODS

The Electronic Residency Application System (ERAS) data from the Association of American Medical Colleges (AAMC) and the National Board of Medical Examiners (NBME) of first-time MD applicants (n = 8966) for orthopaedic surgery residency positions in the United States and of admitted orthopaedic residents (n = 6218) from 2005 to 2014 were reviewed. This dataset is the first and most comprehensive of its kind to date in orthopaedic surgery. Academic metrics, such as USMLE Step 1 and Step 2 Clinical Knowledge scores, number of publications, Alpha Omega Alpha status, volunteer experiences, work experience, as well as race and gender, were analyzed using hierarchical logistic regression models. The first model analyzed the association of academic metrics with admission into orthopaedic residency. In the second model, we added race and gender and controlled for metrics of academic performance. To determine how well the models simulated the actual admissions data, we computed the receiver operating characteristics (ROC) including the area under curve (AUC), which measures the model's ability to simulate which applicants were admitted or not admitted, with an AUC = 1.0 representing a perfect simulation. The odds ratio and confidence interval of each variable were computed.

RESULTS

When only academic variables were analyzed in the first model, Alpha Omega Alpha status (odds ratio 2.12 [95% CI 1.80 to 2.50]; p < 0.001), the USMLE Step 1 score (OR 1.04 [95% CI 1.03 to 1.04]; p < 0.001), the USMLE Step 2 Clinical Knowledge score (OR 1.01 [95% CI 1.01 to 1.02]; p < 0.001), publication count (OR 1.04 [95% CI 1.03 to 1.05]; p < 0.001), and volunteer experience (OR 1.03 [95% CI 1.01 to 1.04]; p < 0.001) were associated with admissions into orthopaedics while work and research experience were not. This model yielded a good prediction of the results with an AUC of 0.755. The second model, in which the variables of race and gender were added to the academic variables, also had a good prediction of the results with an AUC of 0.759. This model indicates that applicant race, but not gender, is associated with admissions into orthopaedic residency. Applicants from Asian (OR 0.78 [95% CI 0.67 to 0.92]), Black (OR 0.63 [95% CI 0.51 to 0.77], Hispanic (OR 0.48 [95% CI 0.36 to 0.65]), or other race groups (OR 0.65 [95% CI 0.55 to 0.77]) had lower odds of admission into residency compared with white applicants.

CONCLUSION

Minority applicants, but not women, have lower odds of admission into orthopaedic surgery residency, even when accounting for academic performance metrics. Changes in the residency selection processes are needed to eliminate the lower admission probability of qualified minority applicants in orthopaedic residency and to improve the diversity and inclusion of orthopaedic surgery. Changes including increasing the diversity of the selection committee, bias training, blinding applications before review, removal of metrics with history of racial disparities from an interviewer's candidate profile before an interview, and use of holistic application review (where an applicants' experiences, attributes, and academic metrics are all considered) can improve the diversity landscape in training. In addition, cultivating an environment of inclusion will be necessary to address these long-standing trends in orthopaedic surgery.

CLINICAL RELEVANCE

Race, but not gender, is associated with the odds of acceptance into orthopaedic surgery residency despite equivalent academic metrics. Changes in residency selection processes are suggested to eliminate the lower admission probability of qualified minority applicants into orthopaedic residency and to improve the diversity and inclusion of orthopaedic surgery.

摘要

背景

矫形外科是竞争最激烈但多样性最低的外科专业之一,申请人的学术成就(如考试成绩)不断提高。先前的研究表明,与黑种人、西班牙裔和其他申请人群体相比,白人申请人的美国医师执照考试(USMLE)第 1 步和第 2 步临床知识成绩更高,并且成为 Alpha Omega Alpha 会员的几率更高。然而,目前尚不清楚种族/族裔差异在申请指标上的差异是否足以解释某些少数族裔或少数民族在矫形住院医师项目中代表性不足的问题。

问题/目的:在这项研究中,我们试图确定(1)入学的学术变量的相对权重,以及(2)种族和性别是否与骨科住院医师的录取独立相关。

方法

从美国医学院协会(AAMC)的电子住院医师申请系统(ERAS)和全国医师考试委员会(NBME)的数据中审查了美国骨科住院医师职位的第一次 MD 申请人(n = 8966)和被录取的骨科住院医师(n = 6218),时间范围为 2005 年至 2014 年。这是迄今为止在矫形外科领域中最全面和最早的数据集。使用分层逻辑回归模型分析了 USMLE 第 1 步和第 2 步临床知识成绩、出版物数量、Alpha Omega Alpha 状态、志愿者经历、工作经验以及种族和性别等学术指标。在第一个模型中分析了学术指标与骨科住院医师录取的相关性。在第二个模型中,我们添加了种族和性别,并控制了学术表现的指标。为了确定模型如何模拟实际的招生数据,我们计算了接收者操作特征(ROC),包括曲线下面积(AUC),这衡量了模型模拟哪些申请人被录取或未被录取的能力,AUC = 1.0 表示完美模拟。计算了每个变量的优势比和置信区间。

结果

当仅在第一个模型中分析学术变量时,Alpha Omega Alpha 状态(优势比 2.12 [95%CI 1.80 至 2.50];p < 0.001)、USMLE 第 1 步成绩(OR 1.04 [95%CI 1.03 至 1.04];p < 0.001)、USMLE 第 2 步临床知识成绩(OR 1.01 [95%CI 1.01 至 1.02];p < 0.001)、出版物数量(OR 1.04 [95%CI 1.03 至 1.05];p < 0.001)和志愿者经历(OR 1.03 [95%CI 1.01 至 1.04];p < 0.001)与骨科住院医师录取相关,而工作和研究经验则没有。该模型对结果的预测效果良好,AUC 为 0.755。在第二个模型中,其中添加了种族和性别变量到学术变量中,对结果的预测效果也很好,AUC 为 0.759。该模型表明,申请人的种族,但不是性别,与骨科住院医师的录取有关。与白人申请人相比,来自亚洲(OR 0.78 [95%CI 0.67 至 0.92])、黑人(OR 0.63 [95%CI 0.51 至 0.77])、西班牙裔(OR 0.48 [95%CI 0.36 至 0.65])或其他种族群体(OR 0.65 [95%CI 0.55 至 0.77])的申请人被录取的几率较低。

结论

少数族裔申请人,而不是女性,即使考虑到学术表现指标,他们被骨科住院医师录取的几率也较低。需要改变住院医师选拔过程,以消除合格的少数族裔申请人在骨科住院医师培训中录取概率较低的问题,并提高骨科手术的多样性和包容性。改变包括增加选拔委员会的多样性、进行偏见培训、在审查前对申请材料进行盲审、在面试前从面试官的候选人资料中删除具有历史种族差异的指标,以及使用整体申请审查(其中考虑申请人的经历、属性和学术指标),可以改善培训中的多样性格局。此外,还需要营造包容的环境,以解决骨科手术中长期存在的这些趋势。

临床相关性

尽管学术指标相当,但种族(而非性别)与接受骨科手术住院医师的几率相关。建议改变住院医师选拔过程,以消除合格的少数族裔申请人进入骨科住院医师培训的机会较低的问题,并提高骨科手术的多样性和包容性。