Entrusting Observable Practice Activities and Milestones Over the 36 Months of an Internal Medicine Residency
Bibliographic record
Abstract
PURPOSE: Competency-based medical education and milestone reporting have led to increased interest in work-based assessments using entrustment over time as an assessment framework. Little is known about data collected from these assessments during residency. This study describes the results of entrustment of discrete work-based skills over 36 months in the University of Cincinnati internal medicine (IM) residency program. METHOD: Attending physician and peer/allied health assessors provided entrustment ratings of resident performance on work-based observable practice activities (OPAs) mapped to Accreditation Council for Graduate Medicine Education/American Board of Internal Medicine reporting milestones for IM. These data were translated into milestones data and tracked longitudinally. The authors analyzed data from this new entrustment system's first 36 months (July 2012-June 2015). RESULTS: During the 36-month period, assessors made 364,728 milestone assessments (mapped from OPAs) of 189 residents. Residents received an annualized average of 83 assessment encounters, producing means of 3,987 milestone assessments and 4,325 words of narrative assessment. Mean entrustment ratings (range 1-5) from all assessors for all milestones rose from 2.46 for first-month residents to 3.92 for 36th-month residents (r = 0.9252, P < .001). Attending physicians' entrustment ratings were lower than peer/allied health assessors' ratings. Medical knowledge and patient care milestones were rated lower than professionalism and interpersonal and communication skills milestones. CONCLUSIONS: Entrustment of milestones appears to rise progressively over time, with differences by assessor type, competency, milestone, and resident. Further research is needed to elucidate the validity of these data in promotion, remediation, and reporting decisions.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".