Objective predictors of intern performance

Amanda C Filiberto,George A Sarosi,Lou Ann Cooper,Tyler J Loftus,Sonja S Samant,Sanda A Tan

doi:10.1186/s12909-021-02487-0

Abstract

BackgroundResidency programs select medical students for interviews and employment using metrics such as the United States Medical Licensing Examination (USMLE) scores, grade-point average (GPA), and class rank/quartile. It is unclear whether these metrics predict performance as an intern. This study tested the hypothesis that performance on these metrics would predict intern performance.MethodsThis single institution, retrospective cohort analysis included 244 graduates from four classes (2015–2018) who completed an Accreditation Council for Graduate Medical Education (ACGME) certified internship and were evaluated by program directors (PDs) at the end of the year. PDs provided a global assessment rating and ratings addressing ACGME competencies (response rate = 47%) with five response options: excellent = 5, very good = 4, acceptable = 3, marginal = 2, unacceptable = 1. PDs also classified interns as outstanding = 4, above average = 3, average = 2, and below average = 1 relative to other interns from the same residency program. Mean USMLE scores (Step 1 and Step 2CK), third-year GPA, class rank, and core competency ratings were compared using Welch’s ANOVA and follow-up pairwise t-tests.ResultsBetter performance on PD evaluations at the end of intern year was associated with higher USMLE Step 1 (p = 0.006), Step 2CK (p = 0.030), medical school GPA (p = 0.020) and class rank (p = 0.016). Interns rated as average had lower USMLE scores, GPA, and class rank than those rated as above average or outstanding; there were no significant differences between above average and outstanding interns. Higher rating in each of the ACGME core competencies was associated with better intern performance (p < 0.01).ConclusionsBetter performance as an intern was associated with higher USMLE scores, medical school GPA and class rank. When USMLE Step 1 reporting changes from numeric scores to pass/fail, residency programs can use other metrics to select medical students for interviews and employment.

Highlights

In selecting medical students for interview and employment, residency programs seek candidates that will perform well as residents and become excellent physicians
There were no significant differences among the four classes of medical student graduates (2015–2018) in terms of performance metrics, core competencies or global assessment
In addition to Step 1, our study found a significant association between performance as an intern and grade-point average (GPA), class rank and Step 2 CK

Summary

Introduction

In selecting medical students for interview and employment, residency programs seek candidates that will perform well as residents and become excellent physicians. Among the 2018 National Resident Matching Program (NRMP) survey of program directors, 94% of the ~ 1200 programs cited USMLE Step 1 score as an important factor for selecting candidates to interview, and more than half reported the use of a prescribed cutoff score, below which applicants are ineligible [6]. Residency programs select medical students for interviews and employment using metrics such as the United States Medical Licensing Examination (USMLE) scores, grade-point average (GPA), and class rank/quartile. It is unclear whether these metrics predict performance as an intern. This study tested the hypothesis that performance on these metrics would predict intern performance

Methods

Results

Discussion

Conclusion