The Haiti Medical Education Project: development and analysis of a competency based continuing medical education course in Haiti through distance learning
Bibliographic record
Abstract
BACKGROUND: Recent calls for reform in healthcare training emphasize using competency-based curricula and information technology-empowered learning. Continuing Medical Education programs are essential in maintaining physician accreditation. Haitian physicians have expressed a lack access to these activities. The Haiti Medical Education Project works in alliance with Haitian medical leadership, faculty and students to support the Country's medical education system. We present the creation, delivery and evaluation of a competency-based continuing medical education curriculum for physicians in rural Haiti. METHODS: Real time lectures from local and international institutions were teleconferenced to physicians in remote Haitian sites using VidyoConferencing™ technology. With American Academy of Family Physicians (AAFP) and College of Family Physicians Canada (CFPC) guidelines as references, a competency-derived syllabus was created for a Haitian continuing medical education program. The resulting educational goals were reviewed by a committee of Haitian and North American physician/medical education practitioners to reflect local needs. All authors reviewed lectures and then conferred to establish agreement on competencies presented for each lecture. RESULTS: Sixty-seven lectures were delivered. Human immunodeficiency virus/Acquired Immunodeficiency Syndrome, ophthalmologic, infectious diseases, renal and endocrine competencies were well-represented, with more than 50 % of the joint AAFP and CFPC recommended competencies outlined. Areas under-represented included allergy and immunology, cardiology, surgery, pain management, gastroenterology, neurology, pulmonology, men's health and rheumatology; these topics accounted for less than 25 % of AAFP/CFPC recommended competencies. Areas not covered included geriatrics, nutrition, occupational health and women's health. Within practice-based lectures, only disaster medicine, health promotion and information management were included, but only partially covered. CONCLUSIONS: We identified teaching goals covered and competencies that were missing from a CME program for rural Haitian physicians. We aim to use this analysis to provide a competency-based CME lecture series that proportionally meets local needs while following recommendations of recognized national family medicine organizations.
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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 | 0.005 | 0.082 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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 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".