The Association of ACGME Milestones With Performance on American Board of Surgery Assessments
Bibliographic record
Abstract
OBJECTIVE: To determine the relationship between, and predictive utility of, milestone ratings and subsequent American Board of Surgery (ABS) vascular surgery in-training examination (VSITE), vascular qualifying examination (VQE), and vascular certifying examination (VCE) performance in a national cohort of vascular surgery trainees. BACKGROUND: Specialty board certification is an important indicator of physician competence. However, predicting future board certification examination performance during training continues to be challenging. METHODS: This is a national longitudinal cohort study examining relational and predictive associations between Accreditation Council for Graduate Medical Education (ACGME) Milestone ratings and performance on VSITE, VQE, and VCE for all vascular surgery trainees from 2015 to 2021. Predictive associations between milestone ratings and VSITE were conducted using cross-classified random-effects regression. Cross-classified random-effects logistic regression was used to identify predictive associations between milestone ratings and VQE and VCE. RESULTS: Milestone ratings were obtained for all residents and fellows(n=1,118) from 164 programs during the study period (from July 2015 to June 2021), including 145,959 total trainee assessments. Medical knowledge (MK) and patient care (PC) milestone ratings were strongly predictive of VSITE performance across all postgraduate years (PGYs) of training, with MK ratings demonstrating a slightly stronger predictive association overall (MK coefficient 17.26 to 35.76, β = 0.15 to 0.23). All core competency ratings were predictive of VSITE performance in PGYs 4 and 5. PGY 5 MK was highly predictive of VQE performance [OR 4.73, (95% CI, 3.87-5.78), P <0.001]. PC subcompetencies were also highly predictive of VQE performance in the final year of training [OR 4.14, (95% CI, 3.17-5.41), P <0.001]. All other competencies were also significantly predictive of first-attempt VQE pass with ORs of 1.53 and higher. PGY 4 ICS ratings [OR 4.0, (95% CI, 3.06-5.21), P <0.001] emerged as the strongest predictor of VCE first-attempt pass. Again, all subcompetency ratings remained significant predictors of first-attempt pass on CE with ORs of 1.48 and higher. CONCLUSIONS: ACGME Milestone ratings are highly predictive of future VSITE performance, and first-attempt pass achievement on VQE and VCE in a national cohort of surgical trainees.
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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 | 0.003 | 0.022 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".