The Application of Entrustable Professional Activities to Inform Competency Decisions in a Family Medicine Residency Program
Bibliographic record
Abstract
Assessing entrustable professional activities (EPAs), or carefully chosen units of work that define a profession and are entrusted to a resident to complete unsupervised once she or he has obtained adequate competence, is a novel and innovative approach to competency-based assessment (CBA). What is currently not well described in the literature is the application of EPAs within a CBA system. In this article, the authors describe the development of 35 EPAs for a Canadian family medicine residency program, including the work by an expert panel of family physician and medical education experts from four universities in three Canadian provinces to identify the relevant EPAs for family medicine in nine curriculum domains. The authors outline how they used these EPAs and the corresponding templates that describe competence at different levels of supervision to create electronic EPA field notes, which has allowed educators to use the EPAs as a formative tool to structure day-to-day assessment and feedback and a summative tool to ground competency declarations about residents. They then describe the system to compile, collate, and use the EPA field notes to make competency declarations and how this system aligns with van der Vleuten's utility index for assessment (valid, reliable, of educational value, acceptable, cost-effective). Early outcomes indicate that preceptors are using the EPA field notes more often than they used the generic field notes. EPAs enable educators to evaluate multiple objectives and important but unwieldy competencies by providing practical, manageable, measurable activities that can be used to assess competency development.
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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 | 0.003 | 0.013 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".