Assessment of Entrustable Professional Activities Using a Web-Based Simulation Platform During Transition to Emergency Medicine Residency: Mixed Methods Pilot Study
Bibliographic record
Abstract
BACKGROUND: The 13 core entrustable professional activities (EPAs) are key competency-based learning outcomes in the transition from undergraduate to graduate medical education in the United States. Five of these EPAs (EPA2: prioritizing differentials, EPA3: recommending and interpreting tests, EPA4: entering orders and prescriptions, EPA5: documenting clinical encounters, and EPA10: recognizing urgent and emergent conditions) are uniquely suited for web-based assessment. OBJECTIVE: In this pilot study, we created cases on a web-based simulation platform for the diagnostic assessment of these EPAs and examined the feasibility and acceptability of the platform. METHODS: Four simulation cases underwent 3 rounds of consensus panels and pilot testing. Incoming emergency medicine interns (N=15) completed all cases. A maximum of 4 "look for" statements, which encompassed specific EPAs, were generated for each participant: (1) performing harmful or missing actions, (2) narrowing differential or wrong final diagnosis, (3) errors in documentation, and (4) lack of recognition and stabilization of urgent diagnoses. Finally, we interviewed a sample of interns (n=5) and residency leadership (n=5) and analyzed the responses using thematic analysis. RESULTS: All participants had at least one missing critical action, and 40% (6/15) of the participants performed at least one harmful action across all 4 cases. The final diagnosis was not included in the differential diagnosis in more than half of the assessments (8/15, 54%). Other errors included selecting incorrect documentation passages (6/15, 40%) and indiscriminately applying oxygen (9/15, 60%). The interview themes included psychological safety of the interface, ability to assess learning, and fidelity of cases. The most valuable feature cited was the ability to place orders in a realistic electronic medical record interface. CONCLUSIONS: This study demonstrates the feasibility and acceptability of a web-based platform for diagnostic assessment of specific EPAs. The approach rapidly identifies potential areas of concern for incoming interns using an asynchronous format, provides feedback in a manner appreciated by residency leadership, and informs individualized learning plans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".