LO53: The correlation of workplace-based assessments with periodic performance assessment of emergency medicine residents
Bibliographic record
Abstract
Introduction: Competency-based medical education (CBME) relies on pragmatic assessment to inform trainee progression decisions. It is unclear whether face-to-face workplace-based assessment (WBA) scoring by faculty reflects their true perception of trainee competence, as many factors influence individual assessments. To better defend competence committee decisions, it is critical to understand how accurately WBAs reflect the faculty's honest perception of resident competence and entrustment. Methods: To best capture faculty perception of trainee competence, we created a periodic performance assessment (PPA) tool for anonymous faculty assessment of residents after repeated clinical interactions. PPA surveys were distributed to full-time EM faculty at a single Canadian FRCPC-EM training site. Faculty were asked to score residents on entrustable professional activities (EPAs) based on encounters over the previous 6-months, and were advised that all data would be anonymized. All WBA scores for FRCPC-EM residents (N = 21) were collected from the 6-months preceding PPA completion. Analysis compared paired WBA and PPA entrustment scores for an individual resident, faculty, and EPA using Wilcoxon Signed Ranks tests and Spearman correlations. Data were analyzed across faculty, EPAs, and both faculty and EPA. Results: About half (17/33) of all invited full-time EM faculty participated. Overall, anonymous PPAs had a significantly lower mean score compared to face-to-face WBAs (3.61-3.69 vs. 3.92-4.06, p < 0.001 for all) across all groupings. Individual WBAs had a low-moderate correlation with individual PPAs (rho = 0.44). When scores were averaged across 1) faculty or 2) EPA, there was an increase in correlation, but it remained moderate (rho = 0.53 and 0.54, respectively). When scores were averaged for an individual resident across 3) faculty and EPA, there was a strong correlation between WBA and PPA (rho = 0.86). Conclusion: There is only moderate correlation between an individual faculty's WBAs and their anonymous longitudinal entrustment for a given resident on a specific EPA. These results may signal caution when interpreting WBA scores in the context of high stakes decisions. Aggregated scores from multiple faculty and/or multiple EPAs substantially increased the correlation between WBA and PPA. These findings highlight the importance of using aggregated WBA scores across multiple assessors and EPA for high-stakes resident progression decisions, to minimize the noise and bias in individual assessment.
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".