Development and evaluation of the Rural and Northern Community Focused Model of COPD Care (RaNCoM)
Bibliographic record
Abstract
BACKGROUND: The prevalence of COPD continues to rise. To address the challenges to provide high quality COPD care in rural and northern communities, leaders in one rural and northern community in Western Canada sought to change the culture of COPD screening and care. Recognizing effective assessment, diagnosis, and treatment for patients with COPD are crucial to improve outcomes, a program was developed between 2012 and 2021 to enhance primary care for COPD patients. METHODS: A process evaluation was undertaken to assess program development, implementation, mechanisms of impact, and context of COPD program. Qualitative thematic analysis of stakeholder interviews (n = 11) and a document review (n = 60; ~ 500 pages) of key clinic documents was conducted. RESULTS: We describe five phases of the COPD program's development (Survive; Reorganize and Stabilize; Assess and Respond; Build and Refine; and Sustain and Share), highlighting areas of innovation. Outreach and localizing resources improved access to the program. Acquiring secured physician compensation, capturing quality data, and improving patient and provider self-efficacy built the capacity of the system and stakeholders within it. Finally, relationships were forged through building an integrated facility, collaborative networking, and patient engagement. Key elements of program implementation included the resources (infrastructure, software, operational) required to ensure operation. CONCLUSION: Team-based care and service integration enhanced care capacity and the health network. Focused use of infrastructure and resources supported the people in the care system. Upholding a shared value of relationship is critical to deliver robust and sustainable rural healthcare. Quality improvement requires investment in rural community healthcare resources.
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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 | 0.029 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".