Effect of United States Medical Licensing Examination Score Cutoffs on Recruitment of Underrepresented Applicants in the Urology Match

Urology. 2024 May:187:25-30. doi: 10.1016/j.urology.2023.11.036. Epub 2024 Feb 10.

Abstract

Objective: To determine how the use of United States Medical Licensing Examination (USMLE) score cutoffs during the screening process of the Urology Residency Match Program may affect recruitment of applicants who are underrepresented in medicine (URM).

Materials and methods: Deidentified data from the Association of American Medical Colleges' (AAMC) Electronic Residency Application Service (ERAS) system was reviewed, representing all applicants to our institution's urology residency program from 2018 to 2022. We analyzed self-reported demographic variables including race/ethnicity, age, sex/gender, as well as USMLE Step 1 and Step 2 scores. Chi-square tests and ANOVA were used to determine the association between race/ethnicity and other sociodemographic factors and academic metrics. Applicants were stratified according to USMLE Step 1 cutoff scores and the distribution of applicants by race/ethnicity was assessed using a Gaussian nonlinear regression fit.

Results: A total of 1258 applicants submitted applications to our program during the 5-year period, including 872 males (69.3%) and 386 females (30.7%). Most applicants were White (43.5%), followed by Asian (28.3%), Hispanic/Latino (11.7%), and Black (7.0%). There was an association between race/ethnicity and USMLE scores. Median USMLE Step 1 scores for White, Asian, Hispanic/Latino, and Black applicants were 242, 242, 237, and 232, respectively (P < .001). As cutoff score increases, percentage of URM applicants decreases.

Conclusion: The use of cutoffs based on USMLE scores disproportionately affects URM applicants. Transitioning from numeric scores to pass/fail may enhance holistic review processes and increase the representation of URM applicants offered interviews at urology residency programs.

MeSH terms

  • Adult
  • Female
  • Humans
  • Internship and Residency* / statistics & numerical data
  • Licensure, Medical / statistics & numerical data
  • Male
  • Minority Groups / statistics & numerical data
  • Personnel Selection / standards
  • Personnel Selection / statistics & numerical data
  • United States
  • Urology* / education