Consensus statement on networks for high-quality rural anesthesia, surgery, and obstetric care in Canada
Bibliographic record
Abstract
OBJECTIVE: To describe the essential components of well-resourced and high-functioning multidisciplinary networks that support high-quality anesthesia, surgery, and maternity care for rural Canadians, delivered as close to home as possible. COMPOSITION OF THE COMMITTEE: A volunteer Writers' Group was drawn from the Society of Obstetricians and Gynaecologists of Canada, the Society of Rural Physicians of Canada, the Royal College of Physicians and Surgeons of Canada, the Canadian Association of General Surgeons, the College of Family Physicians of Canada, and the Association of Canadian University Departments of Anesthesia. METHODS: A collaborative effort over the past several years among the professional stakeholders has culminated in this consensus statement on networked care designed to integrate and support a specialist and non-specialist, urban and rural, anesthesia, surgery, and maternity work force into high-functioning networks based on the best available evidence. REPORT: Surgical and maternity triage needs to be embedded within networks to address the tensions between sustainable regional programs and local access to care. Safety and quality must be demonstrated to be equivalent across similar patients and procedures, regardless of network site. Triage of patients across multiple sites is a quality outcome metric requiring continuous iterative scrutiny. Clinical coaching between rural and regional centres can be helpful in building and sustaining high-functioning networks. Maintenance of quality and the provision of continuing professional development in low-volume settings represent a mutual value proposition. CONCLUSION: The trusting relationships that are foundational to successful networks are built through clinical coaching, continuing professional development, and quality improvement. Currently, a collaborative effort in British Columbia is delivering a provincial program-Rural Surgical Obstetrical Networks-built on the principles and supporting evidence described in this consensus statement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.078 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.013 | 0.011 |
| Research integrity | 0.018 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".