Secondary Logo

Journal Logo

Institutional members access full text with Ovid®

Dynamic Measurement in Health Professions Education: Rationale, Application, and Possibilities

Dumas, Denis PhD; McNeish, Daniel PhD; Schreiber-Gregory, Deanna MS; Durning, Steven J. MD, PhD; Torre, Dario M. MD, PhD, MPH

doi: 10.1097/ACM.0000000000002729

Dynamic measurement modeling (DMM) is a psychometric paradigm that uses longitudinal data to estimate individual students’ growth in measured skills over the course of an educational program (i.e., growth scores). DMM represents a more formal way of assessing learning progress across the health professions education continuum. In this article, the authors provide justification for this approach in health professions education and demonstrate its proof-of-concept use with three time points of United States Medical Licensing Examination Step exams to generate growth scores for 454 current and recent medical learners. The authors demonstrate that learners vary substantially on their growth scores, and those growth scores exhibit psychometric reliability. In addition, growth scores significantly and positively correlated with indicators of medical learner readiness (e.g., undergraduate grade point average and Medical College Admission Test scores). These growth scores were also capable of significantly and positively correlating with future ratings of clinical competencies during internship as assessed through a survey sent to their program directors at the end of the first postgraduate year (e.g., patient care, interpersonal skills). These preliminary findings of reliability and validity for DMM growth scores provide initial evidence for further investigation into the suitability of a dynamic measurement paradigm in health professions education.

D. Dumas is assistant professor of research methods and information science, University of Denver, Denver, Colorado.

D. McNeish is assistant professor of quantitative psychology, Arizona State University, Phoenix, Arizona.

D. Schreiber-Gregory is data analyst, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

S.J. Durning is professor of medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

D.M. Torre is associate professor of medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

Funding/Support: None reported.

Other disclosures: None reported.

Ethical approval: The study described in this article was approved by the institutional review board at the Uniformed Services University of the Health Sciences.

Supplemental digital content for this article is available at and

Correspondence should be addressed to Denis Dumas, Department of Research Methods and Information Science, University of Denver, Denver, CO 80208; email:

Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.