Current and Optimal Training in High-Value Care in the Internal Medicine Clerkship: A National Curricular Needs Assessment
Bibliographic record
Abstract
PURPOSE: The clinical skills needed to practice high-value care (HVC) are core to all medical disciplines. Medical students form practice habits early, and HVC instruction is essential to this formation. The purpose of this study was to describe the state of HVC instruction and assessment in internal medicine clerkships and identify needs for additional curricula. METHOD: In 2014, the Clerkship Directors in Internal Medicine conducted its annual survey of 121 U.S. and Canadian medical schools. The authors evaluated a subset of questions from that survey asking clerkship directors about the perceived importance of HVC instruction, type and amount of formal instruction and assessment, achievement of student competence, prioritization of topics, and barriers to curriculum implementation. Descriptive statistics were used to summarize responses, and chi-square tests were used to examine associations between response categories. RESULTS: The overall response rate was 77.7% (94/121). The majority (85; 91.4%) agreed that medical schools have a responsibility to teach about HVC across all phases of the curriculum. Of respondents, 31 (32.9%) reported their curricula as having some formal instruction on HVC, and 66 (70.2%) felt the amount was inadequate. Highest-priority topics for inclusion included overuse of diagnostic tests and treatments, defining value and its application to clinical reasoning, and balancing benefit and harm. Only 11 (17.8%) assessed students' competence in HVC. CONCLUSIONS: Internal medicine clerkship directors reported that HVC is insufficiently taught and assessed in medical school, despite relevance to practice. Developing generalizable curricular materials, faculty development, and dedicated curricular time may enhance HVC education.
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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 | 0.015 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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".