Abstract：
OBJECTIVE: The lack of underrepresented in medicine physicians in academic plastic surgery has been a topic of interest for many years, and accordingly outreach has been undertaken to address the pipeline from medical school to residency and beyond.
OBJECTIVE: This study aims to assess and identify the characteristics associated with plastic surgery match success for underrepresented in medicine applicants.
METHODS: Residency application data for first time, US allopathic medical school seniors from the 2017-2018 to 2021-2022 applicant cycles were abstracted from Electronic Residency Application Service applications, and match results were determined using the National Residency Matching Program database and online public sources. Data included self-reported race, and multiple application characteristics. Multivariable logistic regression of application characteristics were used to assess the relationship between underrepresented in medicine status and successfully matching. Binary logistic regression was used in subgroup analyses of each application characteristic, and interactions regression was used to evaluate the relative weight of each characteristic on successfully matching.
RESULTS: Underrepresented in medicine applicants were 57% less likely to match than non-underrepresented in medicine applicants (OR 0.43, p = 0.001), though they were 60% less likely to match (ORadj 0.4, p = 0.216) when adjusted. Subgroup analysis revealed that odds of matching as an underrepresented in medicine applicant were significantly increased if the applicant had a home program, took a research year, and had an increased number of published research and presentations (ORs 0.43-0.48, all p < 0.05). Odds of matching as an underrepresented in medicine applicant were significantly decreased if the applicant went to a medical school ranked in the highest or lowest third (ORs 0.41-0.42, all p < 0.01); however, on interaction regression the odds of matching from a highly ranked medical school was increased (OR 3.5, 95% CI 0.98-12.55, p = 0.05).
CONCLUSIONS: The likelihood of matching as an underrepresented in medicine applicant is lower than the rest of the applicant population, and there are no individual applicant characteristics that can increase these odds to equal that of the general applicant population.
OBJECTIVE: This study aims to assess and identify the characteristics associated with plastic surgery match success for underrepresented in medicine applicants.
METHODS: Residency application data for first time, US allopathic medical school seniors from the 2017-2018 to 2021-2022 applicant cycles were abstracted from Electronic Residency Application Service applications, and match results were determined using the National Residency Matching Program database and online public sources. Data included self-reported race, and multiple application characteristics. Multivariable logistic regression of application characteristics were used to assess the relationship between underrepresented in medicine status and successfully matching. Binary logistic regression was used in subgroup analyses of each application characteristic, and interactions regression was used to evaluate the relative weight of each characteristic on successfully matching.
RESULTS: Underrepresented in medicine applicants were 57% less likely to match than non-underrepresented in medicine applicants (OR 0.43, p = 0.001), though they were 60% less likely to match (ORadj 0.4, p = 0.216) when adjusted. Subgroup analysis revealed that odds of matching as an underrepresented in medicine applicant were significantly increased if the applicant had a home program, took a research year, and had an increased number of published research and presentations (ORs 0.43-0.48, all p < 0.05). Odds of matching as an underrepresented in medicine applicant were significantly decreased if the applicant went to a medical school ranked in the highest or lowest third (ORs 0.41-0.42, all p < 0.01); however, on interaction regression the odds of matching from a highly ranked medical school was increased (OR 3.5, 95% CI 0.98-12.55, p = 0.05).
CONCLUSIONS: The likelihood of matching as an underrepresented in medicine applicant is lower than the rest of the applicant population, and there are no individual applicant characteristics that can increase these odds to equal that of the general applicant population.
摘要：
目的：多年来，在学术整形外科中，医学医师的代表性不足一直是人们感兴趣的话题，因此，已经开展了外联工作，以解决从医学院到住院医师及以后的问题。
目的：本研究旨在评估和确定与医学申请人中代表性不足的整形手术匹配成功相关的特征。
方法：首次居留申请数据，2017-2018年至2021-2022年申请周期的美国同种疗法医学院毕业生从电子居留申请服务申请中抽象出来，使用国家居民匹配计划数据库和在线公共资源确定匹配结果。数据包括自我报告的种族，和多种应用特性。使用应用特征的多变量逻辑回归来评估药物状态代表性不足与成功匹配之间的关系。二元逻辑回归用于每个应用特征的亚组分析，并使用交互作用回归来评估成功匹配时每个特征的相对权重。
结果：在医学申请人中代表性不足的比例比在医学申请人中代表性不足的比例低57％（OR0.43，p=0.001），尽管调整后它们匹配的可能性降低了60%(ORadj0.4，p=0.216)。亚组分析显示，如果申请人有家庭计划，则作为药物申请人代表性不足的匹配几率显着增加，花了一年的研究时间，并且发表的研究和报告数量增加(ORs0.43-0.48，所有p<0.05)。如果申请人进入排名最高或最低的三分之一的医学院（ORs0.41-0.42，所有p<0.01），则作为医学申请人代表性不足的匹配几率显着降低；但是，在交互作用回归中,来自排名较高的医学院的匹配几率增加(OR3.5,95%CI0.98-12.55,p=0.05).
结论：在医学申请人中，匹配的可能性低于其他申请人人群，并且没有个人申请人特征可以将这些几率提高到与一般申请人人群相同的水平。
目的：本研究旨在评估和确定与医学申请人中代表性不足的整形手术匹配成功相关的特征。
方法：首次居留申请数据，2017-2018年至2021-2022年申请周期的美国同种疗法医学院毕业生从电子居留申请服务申请中抽象出来，使用国家居民匹配计划数据库和在线公共资源确定匹配结果。数据包括自我报告的种族，和多种应用特性。使用应用特征的多变量逻辑回归来评估药物状态代表性不足与成功匹配之间的关系。二元逻辑回归用于每个应用特征的亚组分析，并使用交互作用回归来评估成功匹配时每个特征的相对权重。
结果：在医学申请人中代表性不足的比例比在医学申请人中代表性不足的比例低57％（OR0.43，p=0.001），尽管调整后它们匹配的可能性降低了60%(ORadj0.4，p=0.216)。亚组分析显示，如果申请人有家庭计划，则作为药物申请人代表性不足的匹配几率显着增加，花了一年的研究时间，并且发表的研究和报告数量增加(ORs0.43-0.48，所有p<0.05)。如果申请人进入排名最高或最低的三分之一的医学院（ORs0.41-0.42，所有p<0.01），则作为医学申请人代表性不足的匹配几率显着降低；但是，在交互作用回归中,来自排名较高的医学院的匹配几率增加(OR3.5,95%CI0.98-12.55,p=0.05).
结论：在医学申请人中，匹配的可能性低于其他申请人人群，并且没有个人申请人特征可以将这些几率提高到与一般申请人人群相同的水平。
