Burn Care and Surgical Exposure amongst Canadian Plastic Surgery Residents: Recommendations for Transitioning to a Competency-Based Medical Education Model
Bibliographic record
Abstract
With the ongoing implementation of a competency-based medical education (CMBE) model for residency programs in North America, emphasis on the duration of training has been refocused onto ability and competence. This study aims to determine the exposure of burn-related core procedural competencies (CPCs) in Canadian Plastic Surgery Residents in order to enhance curricular development and help define its goals. A retrospective review of burn-related resident case logs encompassing all 10 English-speaking plastic surgery residency programs from 2004 to 2014 was performed, including analysis of personal competence scores and resident role by Postgraduate Year (PGY)-year. Case logs of a total of 55 graduating plastic surgery residents were included in the study. Overall, 4033 procedures in burn and burn-related care were logged, accounting for 6.8% of all procedures logged. On average, each resident logged 73 burn procedures, 99% of which were CPCs. The most frequently performed procedure was harvest and application of autograft, allograft, or xenograft, while emergent procedures such as escharotomy and compartment release were performed on average less than one time per resident. Personal competence scores as well as role of the resident (surgical responsibility) increased as PGY-year progressed during residency. Canadian plastic surgery residency programs provide adequate exposure to the majority of the scope of burn care and surgery. However, infrequently encountered but critical procedures such as escharotomy and fasciotomy may require supplementation through dedicated educational opportunities. CMBE should identify these gaps in learning through facilitation of resident competency evaluation. With consideration for the amount of exposure to burn-related CPCs as identified, plastic surgery residency programs can work toward achieving competency in all aspects of burn care and surgery prior to the completion of residency.
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How this classification was reachedexpand
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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".