Surgery in the Western Canadian Arctic : Using a logic model to understand and strengthen a rural surgical system
Bibliographic record
Abstract
Introduction: Rural, remote, indigenous, and circumpolar populations have worse health outcomes when compared with their urban counterparts. Little is known about the surgical needs of such populations, and the delivery of surgical services to such geographically isolated regions poses many challenges. The networked model of care integrating family physicians with enhanced surgical skills (FPESS) and specialist surgeons (SS) provides a sustainable solution to these challenges. This project studied the system of surgical care delivery for the population living in one circumpolar region of the western Canadian Arctic, the Beaufort Delta. Methods: Using a participatory approach, a logic model was developed to describe the delivery of surgical services to the Beaufort Delta Region. Semi-structured interviews were conducted with relevant stakeholders working within the Northwest Territories Health & Social Services Authority in an iterative process following grounded theory. Quantitative methods were also proposed to contribute to an understanding of the surgical needs of the population, as well as the relative impact of each type of surgical care provider in the overall care for the region, but these data remain unavailable at the time of writing. Results: The logic model is presented in graphic and narrative form, detailing the roles of providers involved in surgical care, from community health nurses (CHNs) to sub-specialist surgeons at the tertiary care centres of Edmonton, Alberta. The focus, however, is on the role and interactions between FPESS and SS in the surgical care provided to the region in the demonstration of this networked model of care. Recommendations to improve the host surgical system, based on the interviews with stakeholders and on the literature review, are made. Discussion: This study provides insight into a functioning example of a networked model of surgical care. FPESS and SS work together to improve access to surgical care for this disadvantaged population. Although there is room for improvement, the BDR model demonstrates many of the qualities of networked care as described in the literature. Further study into this model can contribute to a better understanding of circumpolar surgical needs and care delivery, which is a current gap in knowledge, and may benefit other global regions facing similar challenges in the delivery of surgical care. Recommendations from this project can also serve as a platform for knowledge translation to the host surgical system.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".