Diagnosis: Volume 10, Issue 1, Pages 54-60
This op-ed discusses the advantages of leveraging natural language processing (NLP) in the assessment of clinical reasoning. It also provides an overview of INCITE, the Intelligent Clinical Text Evaluator, a scalable NLP-based computer-assisted scoring system that was developed to measure clinical reasoning ability as assessed in the written documentation portion of the now-discontinued USMLE Step 2 Clinical Skills examination.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - p 2880–2886
This paper presents a corpus of 43,985 clinical patient notes (PNs) written by 35,156 examinees during the high-stakes USMLE® Step 2 Clinical Skills examination.
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).
Academic Medicine: May 2018 - Volume 93 - Issue 5 - p 781-785
In 2007, the United States Medical Licensing Examination embedded multimedia simulations of heart sounds into multiple-choice questions. This study investigated changes in item difficulty as determined by examinee performance over time. The data reflect outcomes obtained following initial use of multimedia items from 2007 through 2012, after which an interface change occurred.