Academic Medicine: July 2019 - Volume 94 - Issue 7 - p 926-927
A response to concerns regarding potential bias in the implementation of machine learning (ML) to scoring of the United States Medical Licensing Examination Step 2 Clinical Skills (CS) patient notes (PN).
Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 371-377
Schools undergoing curricular reform are reconsidering the optimal timing of Step 1. This study provides a psychometric investigation of the impact on United States Medical Licensing Examination Step 1 scores of changing the timing of Step 1 from after completion of the basic science curricula to after core clerkships.
Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 314-316
The United States Medical Licensing Examination Step 2 Clinical Skills (CS) exam uses physician raters to evaluate patient notes written by examinees. In this Invited Commentary, the authors describe the ways in which the Step 2 CS exam could benefit from adopting a computer-assisted scoring approach that combines physician raters’ judgments with computer-generated scores based on natural language processing (NLP).
Investigación en Educación Médica, Vol. 8, Núm. 29, 2019
Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, 19(1)
This review is a descriptive summary of the development of National EM M4 examinations, Version 1 (V1) and Version 2 (V2), and the NBME EM Advanced Clinical Examination (ACE) and their relevant usage and performance data. In particular, it describes how examination content was edited to affect desired changes in examination performance data and offers a model for educators seeking to develop their own examinations.
The authors examined the extent to which USMLE scores relate to the odds of receiving a disciplinary action from a U.S. state medical board.