Delivery models of rural surgical services in British Columbia (1996-2005): are general practitioner-surgeons still part of the picture?
Bibliographic record
Abstract
OBJECTIVE: To define the models of surgical service delivery in rural communities that rely solely on general practitioner (GP)-surgeons for emergency care, to examine how they have changed over the past decade and to identify some effects on communities that have lost their local surgical program. METHODS: We undertook a retrospective study using the Population Utilization Rates and Referrals For Easy Comparative Tables database (versions 6.0 and 9.0) and telephone interviews to hospitals that we identified. We included all hospitals in rural British Columbia with surgical programs that had no resident specialist surgeon and that relied on general practitioner-surgeons (GP-surgeons) for emergency surgical care. We examined surgical program characteristics, community size, distance from referral centre, role of itinerant surgery, where GPs were trained, their age and years of experience and referral rates for appendectomies and obstetrics. RESULTS: Changes over the past decade include a decrease in the total number of GP-surgeons operating in these communities, more itinerant surgery and the loss of 3 of 12 programs. GP-surgeons are older, are usually foreign-trained and have more than 5 years of experience. Communities with no local program or that rely on solo practitioners refer more emergencies out of the community and do less maternity care than those with more than a single GP-surgeon. CONCLUSION: GP-surgeons still play an integral role in the provision of emergency and elective surgical services in rural communities without the population base to sustain resident specialist surgeons. As GP-surgeons retire and surgical programs close, there is no accredited training program to replace them. More outcome comparisons between procedures performed by GP-surgeons and general surgeons are needed, as is the creation of a nationally accredited training program to replace these practitioners as they retire.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".