National Internal Medicine Milestone Ratings: Validity Evidence From Longitudinal Three-Year Follow-up
Bibliographic record
Abstract
PURPOSE: To evaluate validity evidence for internal medicine milestone ratings across programs for three resident cohorts by quantifying "not assessable" ratings; reporting mean longitudinal milestone ratings for individual residents; and correlating medical knowledge ratings across training years with certification examination scores to determine predictive validity of milestone ratings for certification outcomes. METHOD: This retrospective study examined milestone ratings for postgraduate year (PGY) 1-3 residents in U.S. internal medicine residency programs. Data sources included milestone ratings, program characteristics, and certification examination scores. RESULTS: Among 35,217 participants, there was a decreased percentage with "not assessable" ratings across years: 1,566 (22.5%) PGY1s in 2013-2014 versus 1,219 (16.6%) in 2015-2016 (P = .01), and 342 (5.1%) PGY3s in 2013-2014 versus 177 (2.6%) in 2015-2016 (P = .04). For individual residents with three years of ratings, mean milestone ratings increased from around 3 (behaviors of an early learner or advancing resident) in PGY1 (ranging from a mean of 2.73 to 3.19 across subcompetencies) to around 4 (ready for unsupervised practice) in PGY3 (mean of 4.00 to 4.22 across subcompetencies, P < .001 for all subcompetencies). For each increase of 0.5 units in two medical knowledge (MK1, MK2) subcompetency ratings, the difference in examination scores for PGY3s was 19.5 points for MK1 (P < .001) and 19.0 for MK2 (P < .001). CONCLUSIONS: These findings provide evidence of validity of the milestones by showing how training programs have applied them over time and how milestones predict other training outcomes.
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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 | 0.020 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".