OBJECTIVE: The predictive value of application data for future general surgery resident performance and attrition are poorly understood. We sought to determine what variables obtained in the application process might predict future resident success. METHODS: We performed an 18-year review (1990-2008) of all matched residents (n = 101) to a university program. Both categorical graduates (CG) and nongraduates (CNG) and nondesignated preliminaries matching (PM) and preliminaries nonmatching (PNM) were evaluated. We also screened for previous high-performance accomplishments outside of the medical field such as in the performing arts or collegiate athletics (SKILL). Outcome data include graduation or match status, American Board of Surgery In-service Training Examination (ABSITE), and faculty Accreditation Council for Graduate Medical Education (ACGME) core competency evaluations. RESULTS: Background data from the Electronic Residency Application Service (ERAS) application between the various groups was compared with univariate analysis and logistic regression. There were significant differences between the groups on the measures of USMLE step 1 (STEP1) (p = 0.001), medical school grade point average (GPA) (p = 0.023), interview data (INTERVIEW) (p < 0.001), and ABSITE (p < 0.001). The variable of INTERVIEW had an odds ratio of 188.27 (95% confidence interval, 3.757-9435.405). Overall attrition was 23.7% (n = 24) and was evenly divided between those who left for lifestyle reasons and those who were encouraged to leave. CONCLUSIONS: Within our system, INTERVIEW, USMLE STEP1, and SKILL predict successful completion of a general surgery residency. In contrast to prior reports, female sex, ethnicity, medical school grades, or Alpha Omega Alpha Honor Society (AOA) status were not significant. The variable SKILL is novel and highlights the importance of nonacademic background data. Our data indicate STEP1 is an independent predictor of resident success in general surgery and should maintain an important role in general surgery applicant screening. The ideal screening threshold is likely > 215.
OBJECTIVE: The predictive value of application data for future general surgery resident performance and attrition are poorly understood. We sought to determine what variables obtained in the application process might predict future resident success. METHODS: We performed an 18-year review (1990-2008) of all matched residents (n = 101) to a university program. Both categorical graduates (CG) and nongraduates (CNG) and nondesignated preliminaries matching (PM) and preliminaries nonmatching (PNM) were evaluated. We also screened for previous high-performance accomplishments outside of the medical field such as in the performing arts or collegiate athletics (SKILL). Outcome data include graduation or match status, American Board of Surgery In-service Training Examination (ABSITE), and faculty Accreditation Council for Graduate Medical Education (ACGME) core competency evaluations. RESULTS: Background data from the Electronic Residency Application Service (ERAS) application between the various groups was compared with univariate analysis and logistic regression. There were significant differences between the groups on the measures of USMLE step 1 (STEP1) (p = 0.001), medical school grade point average (GPA) (p = 0.023), interview data (INTERVIEW) (p < 0.001), and ABSITE (p < 0.001). The variable of INTERVIEW had an odds ratio of 188.27 (95% confidence interval, 3.757-9435.405). Overall attrition was 23.7% (n = 24) and was evenly divided between those who left for lifestyle reasons and those who were encouraged to leave. CONCLUSIONS: Within our system, INTERVIEW, USMLE STEP1, and SKILL predict successful completion of a general surgery residency. In contrast to prior reports, female sex, ethnicity, medical school grades, or Alpha Omega Alpha Honor Society (AOA) status were not significant. The variable SKILL is novel and highlights the importance of nonacademic background data. Our data indicate STEP1 is an independent predictor of resident success in general surgery and should maintain an important role in general surgery applicant screening. The ideal screening threshold is likely > 215.
Authors: Byron D Hughes; Jennifer A Perone; Claire B Cummins; Christian Sommerhalder; Douglas S Tyler; Kanika A Bowen-Jallow; Ravi S Radhakrishnan Journal: J Surg Res Date: 2018-09-03 Impact factor: 2.192
Authors: Michael E Busha; Brock McMillen; Jeffrey Greene; Kristine Gibson; Charlotte Milnes; Peter Ziemkowski Journal: BMC Med Educ Date: 2021-02-02 Impact factor: 2.463