Innovation-Oriented Medical School Curricula: Review of the Literature
Bibliographic record
Abstract
Innovation and entrepreneurship (I&E) programs in medical education have become available as medical schools recognize the need to train forward-thinking physicians. There is considerable diversity in the design and implementation of these curricula, which represents a challenge and possibly serves as a deterrent for the development of additional I&E programs. A comprehensive search of medical school I&E programs and review of all Association of American Medical Colleges member websites (n = 171) were conducted. This review sought to (1) identify all American and Canadian allopathic medical schools with I&E curricula, (2) evaluate their structure/integration in the context of medical education, (3) outline core learning themes, and (4) describe the evaluative metrics. Information was collected through published or publicly available websites and through a questionnaire sent to identified I&E program leaders. Twenty-eight I&E-oriented medical education programs were identified from 26 schools; all of the programs integrated faculty leadership with backgrounds in medicine, engineering, and/or business/entrepreneurship. Of the programs, 57% (16/28) had been launched within the past four years and 75% (21/28) based program enrollment on a selective application process. Nearly all (27/28) incorporated lecture series and/or hands-on modules as a teaching technique. The most prevalent metric was completion of a capstone project (22/28; 79%). At least 15.2% (26/171) of American and Canadian allopathic medical schools include the option for students to participate in an I&E curriculum-based program. This review can be used to help medical school faculty with developing I&E curricula.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".