Effects of Moving the United States Medical Licensing Examination Step 1 After Core Clerkships on Step 2 Clinical Knowledge Performance

Acad Med. 2020 Jan;95(1):111-121. doi: 10.1097/ACM.0000000000002921.

Abstract

Purpose: To investigate the effect of a change in the United States Medical Licensing Examination Step 1 timing on Step 2 Clinical Knowledge (CK) scores, the effect of lag time on Step 2 CK performance, and the relationship of incoming Medical College Admission Test (MCAT) score to Step 2 CK performance pre and post change.

Method: Four schools that moved Step 1 after core clerkships between academic years 2008-2009 and 2017-2018 were analyzed. Standard t tests were used to examine the change in Step 2 CK scores pre and post change. Tests of differences in proportions were used to evaluate whether Step 2 CK failure rates differed between curricular change groups. Linear regressions were used to examine the relationships between Step 2 CK performance, lag time and incoming MCAT score, and curricular change group.

Results: Step 2 CK performance did not change significantly (P = .20). Failure rates remained highly consistent (pre change: 1.83%; post change: 1.79%). The regression indicated that lag time had a significant effect on Step 2 CK performance, with scores declining with increasing lag time, with small but significant interaction effects between MCAT and Step 2 CK scores. Students with lower incoming MCAT scores tended to perform better on Step 2 CK when Step 1 was after clerkships.

Conclusions: Moving Step 1 after core clerkships appears to have had no significant impact on Step 2 CK scores or failure rates, supporting the argument that such a change is noninferior to the traditional model. Students with lower MCAT scores benefit most from the change.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Academic Failure / trends
  • Clinical Clerkship / statistics & numerical data*
  • Clinical Competence / statistics & numerical data*
  • College Admission Test / statistics & numerical data
  • Curriculum / standards
  • Curriculum / trends
  • Female
  • Humans
  • Knowledge
  • Licensure, Medical / statistics & numerical data
  • Licensure, Medical / trends*
  • Linear Models
  • Male
  • Students, Medical / classification
  • Students, Medical / statistics & numerical data
  • United States / epidemiology