Workplace‐based Assessment Data in Emergency Medicine: A Scoping Review of the Literature
Bibliographic record
Abstract
OBJECTIVE: In the era of competency-based medical education (CBME), the collection of more and more trainee data is being mandated by accrediting bodies such as the Accreditation Council for Graduate Medical Education and the Royal College of Physicians and Surgeons of Canada. However, few efforts have been made to synthesize the literature around the current issues surrounding workplace-based assessment (WBA) data. This scoping review seeks to synthesize the landscape of literature on the topic of data collection and utilization for trainees' WBAs in emergency medicine (EM). METHODS: The authors conducted a scoping review in the style of Arksey and O'Malley, seeking to synthesize and map literature on collecting, aggregating, and reporting WBA data. The authors extracted, mapped, and synthesized literature that describes, supports, and substantiates effective data collection and utilization in the context of the CBME movement within EM. RESULTS: Our literature search retrieved 189 potentially relevant references (after removing duplicates) that were screened to 29 abstracts and papers relevant to collecting, aggregating, and reporting WBAs. Our analysis shows that there is an increasing temporal trend toward contributions in these topics, with the majority of the papers (16/29) being published in the past 3 years alone. CONCLUSION: There is increasing interest in the areas around data collection and utilization in the age of CBME. The field, however, is only beginning to emerge, leaving more work that can and should be done in this area.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".