From pipelines to pathways: the Memorial experience in educating doctors for rural generalist practice
Bibliographic record
Abstract
CONTEXT: This report describes the community context, concept and mission of The Faculty of Medicine at Memorial University of Newfoundland (Memorial), Canada, and its 'pathways to rural practice' approach, which includes influences at the pre-medical school, medical school experience, postgraduate residency training, and physician practice levels. Memorial's pathways to practice helped Memorial to fulfill its social accountability mandate to populate the province with highly skilled rural generalist practitioners. Programs/interventions/initiatives: The 'pathways to rural practice' include initiatives in four stages: (1) before admission to medical school; (2) during undergraduate medical training (medical degree (MD) program); (3) during postgraduate vocational residency training; and (4) after postgraduate vocational residency training. Memorial's Learners & Locations (L&L) database tracks students through these stages. The Aboriginal initiative - the MedQuest program and the admissions process that considers geographic or minority representation in terms of those selecting candidates and the candidates themselves - occurs before the student is admitted. Once a student starts Memorial's MD program, the student has ample opportunities to have rural-based experiences through pre-clerkship and clerkship, of which some take place exclusively outside of St. John's tertiary hospitals. Memorial's postgraduate (PG) Family Medicine (FM) residency (vocational) training program allows for deeper community integration and longer periods of training within the same community, which increases the likelihood of a physician choosing rural family medicine. After postgraduate training, rural physicians were given many opportunities for professional development as well as faculty development opportunities. Each of the programs and initiatives were assessed through geospatial rurality analysis of administrative data collected upon entry into and during the MD program and PG training (L&L). Among Memorial MD-graduating classes of 2011-2020, 56% spent the majority of their lives before their 18th birthday in a rural location and 44% in an urban location. As of September 2016, 23 Memorial MD students self-identified as Aboriginal, of which 2 (9%) were from an urban location and 20 (91%) were from rural locations. For Year 3 Family Medicine, graduating classes 2011 to 2019, 89% of placement weeks took place in rural communities and 8% took place in rural towns. For Memorial MD graduating classes 2011-2013 who completed Memorial Family Medicine vocational training residencies, (N=49), 100% completed some rural training. For these 49 residents (vocational trainees), the average amount of time spent in rural areas was 52 weeks out of a total average FM training time of 95 weeks. For Family Medicine residencies from July 2011 to October 2016, 29% of all placement weeks took place in rural communities and 21% of all placement weeks took place in rural towns. For 2016-2017 first-year residents, 53% of the first year training is completed in rural locations, reflecting an even greater rural experiential learning focus. LESSONS LEARNED: Memorial's pathways approach has allowed for the comprehensive training of rural generalists for Newfoundland and Labrador and the rest of Canada and may be applicable to other settings. More challenges remain, requiring ongoing collaboration with governments, medical associations, health authorities, communities, and their physicians to help achieve reliable and feasible healthcare delivery for those living in rural and remote areas.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".