Centralized or decentralized perinatal surgical care for rural women: a realist review of the evidence on safety
Bibliographic record
Abstract
BACKGROUND: The precipitous closure of rural maternity services in British Columbia (BC), Canada, and internationally has demanded a reevaluation of how to meet the perinatal surgical needs of rural women in accordance with the Triple Aim objectives of safety, cost-effectiveness, and satisfaction of all key stakeholders. There is emerging international evidence that General Practitioners with Enhanced Surgical Skills (GPESS) are a well-positioned health service solution due to their generalist nature in low-volume settings. A realist review was undertaken to evaluate international evidence on efficacious models of perinatal surgical care. This article presents findings of the safety of such practice, one discrete part of the full realist review. METHODS: This paper was derived from a larger review, which used a realist review methodology to guide the approach, and adhered to the RAMESES quality standard for realist reviews. Seven academic databases were searched in December 2013, using year (1990) and language (English) limiters in keeping with a rapid review approach. Mining of bibliographies in addition to consultation with international experts led to further inclusion of academic and grey literature up to March 2014. RESULTS: Two hundred fifty-four articles were originally identified; 119 articles were removed from consideration for lack of fit, resulting in the review of 191 articles from the peer reviewed and grey literature. Of these, 53 pertained to safety and are considered herein. Evidence on the safety of GPESS was consistent in the literature cited. Clinical, case study, and qualitative evidence demonstrates that perinatal surgical care is equally safe when provided by GPESS and specialist physicians. CONCLUSION: Findings allow health planners to confidently build perinatal surgical services around the contribution of GPs with enhanced surgical skills and focus on educational, regulatory, and continuing professional development mechanisms to ensure their sustainability. Volume-to-outcomes associations are variable and inconclusive with regards to safety, suggesting the need for more evidence. These findings, and the attendant health services planning directions, are reassuring as they suggest the viability of local models of care where feasible.
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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 | 0.036 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".