ArticleJournal of medical education and curricular development
Using Electronic Health Record Time Tracking Metrics to Identify Struggling Pediatric Interns: A Pilot Study.
Article in Journal of medical education and curricular development. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
4 authors.
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Abstract
Background: Early identification of struggling interns is crucial to mitigating academic setbacks. Standardized testing, ACGME Milestones, and narrative evaluations track academic performance, but are fraught with subjectivity. The electronic health record (EHR) can be used to track time completing clinical tasks; this data may be used in the early detection of struggling learners. Objective: To assess if EHR time tracking metrics can be used to identify struggling pediatric interns. Methods: We performed a retrospective study analyzing two years of intern inpatient EHR time (n=45) from 7/2022 to 6/2024. We used Epic Cogito Slicer-Dicer® to quantify time spent daily writing notes ("Notes"), performing chart review ("Review"), and placing orders ("Orders"). We examined task time distributions between clinical inpatient rotations ("blocks"), and the association between EHR task time, Milestones, test scores, and narrative feedback with struggling. Results: The average task time and distributions were measured for each block. There was no difference for Notes or Review over time, but there was a difference in Orders (p<0.001). We identified nine (20%) struggling interns. Clustering analysis showed an association between EHR task time and specific struggling interns (as well as with Milestones). No association was found between struggling with narrative feedback or test scores. Conclusion: We describe the feasibility of a novel metric to identify pediatric interns at risk of struggling, showing an association of struggling with increased EHR task time (Notes, Review) and with Milestones. We also showed less time spent in Orders was indicative of struggling as well. This study highlights the potential of EHR time metrics to identify at-risk interns and guide timely interventions.
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