Department of Surgery, Boston University School of Medicine, Boston, Massachusetts.
Departments of Obstetrics and Gynecology, Surgery and Medicine, Tufts University School of Medicine, Boston, Massachusetts.
J Surg Res. 2021 Jan;257:246-251. doi: 10.1016/j.jss.2020.08.001. Epub 2020 Aug 27.
Training diverse house staff, including those who are underrepresented in medicine, is vital to provide high-quality patient care for the communities that we serve. In 2018, the Accreditation Council for Graduate Medical Education announced new common program requirements for systematic efforts to recruit and retain a diverse workforce. However, questions remain about how to implement such efforts.
Electronic Residency Application Service (ERAS) data from eight residency programs spanning two recruitment cycles (2017-2018, 2018-2019) was reviewed. The number of candidates at each stage in the process (applicant, invited to interview, interviewed, and matched) was examined by self-identified race or ethnicity. These data were presented to residency program directors at our Graduate Medical Education committee meeting before the next recruitment cycle. Data were analyzed following the 2019-20 residency match. Odds ratios and Pearson's chi-squared test were used to assess statistical significance.
A total of 10,445 and 10,982 medical students applied to our 8 core residency programs in 2017 and 2018, respectively. Medical students who applied and self-identified as Asian, Black or African American, and Hispanic or Latino or Spanish origin had lower odds of being invited to interview than those who self-identified as White. After data presentation, the odds of inviting Black or African American applicants to interview increased significantly. The odds of attending an interview once invited were the same across groups.
Sharing ERAS data patterns with residency program directors was associated with a significant year over year change in interviewee diversity. Structured analysis of institutional ERAS data can provide insight into the resident selection process and may be a useful tool to improve house staff diversity.
培训多元化的住院医师，包括那些在医学领域代表性不足的人群，对于为我们所服务的社区提供高质量的患者护理至关重要。2018 年，毕业后医学教育认证委员会宣布了新的共同项目要求，以系统地努力招聘和留住多元化的劳动力。然而，如何实施这些努力仍存在疑问。
对跨越两个招聘周期（2017-2018 年和 2018-2019 年）的八个住院医师项目的电子住院医师申请服务（ERAS）数据进行了审查。根据自我认定的种族或族裔，在招聘过程的每个阶段（申请人、受邀面试、面试和匹配）的候选人数进行了检查。在下次招聘周期前，将这些数据提交给我们的研究生医学教育委员会会议上的住院医师项目主管。在 2019-20 年住院医师匹配后进行数据分析。使用优势比和皮尔逊卡方检验评估统计学意义。
共有 10445 名和 10982 名医学生分别在 2017 年和 2018 年申请了我们的 8 个核心住院医师项目。与自我认定为白人的医学生相比，申请并自我认定为亚裔、非裔美国人和西班牙裔或拉丁裔或西班牙语裔的医学生被邀请面试的几率较低。在数据呈现后，邀请非裔美国申请人面试的几率显著增加。一旦受邀，参加面试的几率在各个群体中是相同的。
与住院医师项目主管分享 ERAS 数据模式与面试人员多样性的显著逐年变化有关。对机构 ERAS 数据的结构化分析可以深入了解住院医师选拔过程，并且可能是改善住院医师多样性的有用工具。
