Multivariable analysis of factors associated with USMLE scores across U.S. medical schools

Abstract

Background: Gauging medical education quality has always remained challenging. Many studies have examined predictors of standardized exam performance; however, data sets do not distinguish by institution or curriculum. Our objective is to present a summary of variables associated with the United States Medical Licensing Examination (USMLE) scores, and thus identify institutions (and therefore curriculums) which deviate from trend lines by producing higher USMLE scores despite having lower entrance grade point averages and medical college admissions test (MCAT) scores. Methods: Data was obtained from U.S. News and World Report's 2014 evaluation of allopathic U.S. medical schools. A univariate analysis was performed first for each variable using two sample t-test or Wilcoxon rank sum test for categorical variables, and Pearson or Spearman correlation coefficients for continuous variables. A multivariable linear regression model was developed to identify the factors contributing to USMLE scores. All statistical analyses were two-sided and performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC). Results: Univariate analysis reveals a significant association between USMLE Step 1 and 2 scores with medical college admissions test scores, grade point averages, school type (private vs. public), full-time faculty-to-student ratio, National Institute of Health funds, residency director assessment score, peer assessment score, and class size. Of these nine variables, MCAT scores and Step 1 scores display the strongest correlation (corr = 0.72, P