An evidence-based program for rural surgical and obstetrical networks
Bibliographic record
Abstract
CONTEXT: Over the past 25 years, the attrition of small volume rural surgery programs across Western Canada has been significant and sustained. The 'Joint position paper on rural surgery and operative delivery' (JPP) offers a consensus policy framework for the sustainability of rural surgical programs by nesting them within larger regional programs. The many recommendations in the JPP coalesce around the recognition that surgical care should be provided as close to home as possible. To achieve this, surgical care should be delivered within rural and regional surgical programs integrated into well-functioning networks staffed by generalist specialist surgeons trained across surgical disciplines and family physicians with enhanced surgical skills (FPESS). ISSUES: There are important issues to be addressed in the creation of these networks, not the least of which is the sometimes challenging relationships between the stakeholders in these networks and skepticism about the training of FPESS and the safety and quality of low volume surgical programs. Relationships extend from the patient-provider nexus to include interprofessional relationships and those between the pentagram partners (patients/communities, care providers, administrators, researchers and policymakers). Equally important to resolve is the issue of the minimum threshold volume of local surgical activity required for a sustainable professional workforce in a small rural program. LESSONS LEARNED: A collaborative effort by key stakeholders in British Columbia has produced a program designed to overcome these challenges and build effective networks of rural surgical care, based on the synergistic interplay of five key pillars to support small surgical sites. These five pillars include clinical coaching, continuing quality improvement (CQI), remote presence technology to mitigate geographic challenges, sustainable local surgical capacity, and evaluation of dimensions of network function and clinical outcomes. This is the first time that the integration of these five pillars, each derived from best available evidence, have been positioned together as deliberate strategic policy to improve rural surgical care.
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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 | 0.046 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".