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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.085 | 0.304 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.047 | 0.051 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".