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Novel Formative Approach of the ESAP-ITE Provides Strong Predictive Value for ABIM Certification Outcomes
William B Horton1, James T Patrie2, Lauren M Duhigg3
1Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
Background:
The Endocrine Self-Assessment Program In-Training Examination (ESAP-ITE) has the novel formative approach of allowing open access to all questions and answers after secure examination administration is complete, resulting in the creation of an entirely new in-training examination annually.
Objective:
To determine whether scores on the novel ESAP-ITE predict pass/fail outcomes on the American Board of Internal Medicine Endocrinology, Diabetes, and Metabolism Certification Examination (ABIM-ECE).
Methods:
All endocrine fellows-in-training who took the ESAP-ITE between 2016 and 2019 and then subsequently attempted the ABIM-ECE within the same calendar year were included (n = 982). Primary analyses used the ESAP-ITE score from the final year of fellowship training. Covariates included sex, age on date of ABIM-ECE, medical school country, fellowship program region, pass/fail outcomes on the ABIM Internal Medicine Certification Examination, and ESAP-ITE score. All variables were analyzed using multivariable logistic regression.
Results:
ESAP-ITE score (P < 0.001), ABIM Internal Medicine Certification Examination outcome (P < 0.001), and age (P = 0.005) were each significant predictors of passing the ABIM-ECE on the first attempt. ESAP-ITE score was the strongest predictor of passing the ABIM-ECE, and this relationship was such that a score of 75% correct yielded a 97% probability of passing the ABIM-ECE, whereas a score of 50% correct generated only a 70% probability of doing so. Sex, fellowship program region, and medical school country were not significant predictors of ABIM-ECE outcomes.
Conclusions:
In addition to serving as an important learning instrument for endocrine fellowship programs, ESAP-ITE is a robust predictive tool for pass/fail outcomes on the ABIM-ECE.
