BACKGROUND: Residency programs strive to accurately assess applicants' qualifications and predict future performance. However, there is little evidence-based guidance on how to do this. The aim of this study was to design an algorithm for ranking applicants to an internal medicine residency program. METHODS: Ratings of overall performance in residency were compared to application characteristics of 230 graduating residents from 2000-2005. We analyzed 5 characteristics of the application: medical school, overall medical school performance, performance in junior medicine clerkship, United States Medical Licensing Examination (USMLE) Step 1 score, and interview ratings. Using bivariate correlations and multiple regression analysis, we calculated the association of each characteristic with mean performance ratings during residency. RESULTS: In multiple regression analysis, the most significant application factors (r(2) = 0.22) were the quality of the medical school and the applicant's overall performance in medical school (P < .001). CONCLUSION: This data has allowed the creation of a weighted algorithm to rank applicants that uses 4 application factors-school quality, overall medical school performance, medicine performance, and USMLE Step 1 score.
BACKGROUND: Residency programs strive to accurately assess applicants' qualifications and predict future performance. However, there is little evidence-based guidance on how to do this. The aim of this study was to design an algorithm for ranking applicants to an internal medicine residency program. METHODS: Ratings of overall performance in residency were compared to application characteristics of 230 graduating residents from 2000-2005. We analyzed 5 characteristics of the application: medical school, overall medical school performance, performance in junior medicine clerkship, United States Medical Licensing Examination (USMLE) Step 1 score, and interview ratings. Using bivariate correlations and multiple regression analysis, we calculated the association of each characteristic with mean performance ratings during residency. RESULTS: In multiple regression analysis, the most significant application factors (r(2) = 0.22) were the quality of the medical school and the applicant's overall performance in medical school (P < .001). CONCLUSION: This data has allowed the creation of a weighted algorithm to rank applicants that uses 4 application factors-school quality, overall medical school performance, medicine performance, and USMLE Step 1 score.
Authors: Amanda C Filiberto; Lou Ann Cooper; Tyler J Loftus; Sonja S Samant; George A Sarosi; Sanda A Tan Journal: BMC Med Educ Date: 2021-01-26 Impact factor: 2.463