Toward the Assessment of Core Procedural Competencies among Canadian Plastic Surgery Residents
Bibliographic record
Abstract
BACKGROUND: Plastic surgery residency training programs are working toward integrating competency-based education into program curriculum and training, a key component of which involves establishing core procedural competencies. This study aims to determine the exposure of graduating Canadian plastic surgery residents to established core procedural competencies. METHODS: A retrospective review of case log procedure data using three databases (T-Res, POWER, and New Innovations) from graduating residents at all 10 Canadian English-speaking plastic surgery training programs between 2004 and 2014 was completed. Case logs were coded according to 177 core procedural competencies identified as "core" by the Delphi method among an expert panel of Canadian plastic surgeons. RESULTS: A total of 59,405 procedures were logged by 55 graduating residents across Canada between 2004 and 2014 (average, 1080 ± 352 procedures per resident). Of 13 plastic surgery domains, 44 percent of all procedures were within either hand, upper extremity, and peripheral nerve (28.3 percent) or nonaesthetic breast (16.1 percent). The most frequently performed core procedural competencies (average case logs per resident) included breast reduction (65.3 ± 33.9); open carpal tunnel release (46.7 ± 34.2); breast reconstruction, implant-based (39.6 ± 20.5); and wound management (35.7 ± 28.6). Sixty-two of 177 procedures were logged on average less than once in 5 years of residency, including escharotomy, temporal parietal fascia flap, Guyon canal release, and soft-tissue fillers. CONCLUSION: This study identifies areas of exposure and underexposure to plastic surgery core procedural competencies, and can help focus surgical education on areas of greater need for surgical skills training and acquisition.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".