2019 United States Osteopathic Medical Regulatory Summit: Consensus, Recommendations, and Next Steps in Defining Osteopathic Distinctiveness
Bibliographic record
Abstract
BACKGROUND: Osteopathic distinctiveness is a result of professional education, identity formation, training, credentialing, and qualifications. With the advancement of a single graduate medical education (GME) accreditation system and the continued growth of the osteopathic medical profession, osteopathic distinctiveness and professional identity are seen as lacking clarity and pose a challenge. SUMMIT: To achieve consensus on a succinct definition of osteopathic distinctiveness and to identify steps to more clearly define and advance that distinctiveness, particularly in professional self-regulation, a representative group of osteopathic medical students, residents, physicians, and members of the licensing, GME, and undergraduate medical education (UME) communities convened the 2019 United States Osteopathic Medical Regulatory Summit in February 2019. Key features of osteopathic distinctiveness were discussed. Growth in the profession; changes in health care delivery, technology, and demographics within the profession and patient communities; and associated challenges and opportunities for osteopathic medical practice and patients were considered. CONSENSUS: Osteopathic medicine is a distinctive practice that brings unique, added value to patients, the public, and the health care community at large. A universal definition and common understanding of that distinctiveness is lacking. Efforts to unify messaging that defines osteopathic distinctiveness, to align the distinctive elements of osteopathic medical education and professional self-regulation across a continuum, and to advance research on care and educational program outcomes are critical to the future of the osteopathic medical profession. RECOMMENDATIONS: (1) Convene a task force of groups represented at the Summit to develop a succinct and consistent message defining osteopathic distinctiveness. (2) Demonstrate uniqueness of the profession through research demonstrating efficacy of care and patient outcomes, adding to the public good. (3) Harmonize GME and UME by beginning to align entrustable professional activities with UME milestones. (4) Convene representatives from osteopathic specialty colleges and certification boards to define curricular elements across GME, certification, and osteopathic continuous certification. (5) Build on the Project in Osteopathic Medical Education and Empathy study.
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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 | 0.149 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.012 | 0.024 |
| Research integrity | 0.049 | 0.046 |
| Insufficient payload (model declined to judge) | 0.025 | 0.018 |
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".