Team-based comanagement of diabetes in rural primary care.
Bibliographic record
Abstract
OBJECTIVE: To explore clinical indicators among patients with diabetes in southern Alberta and assess changes over time, and to compare patients with diabetes attending a reference clinic (RC), which had adapted its service model to address the specific needs of the patient population, with patients with diabetes attending comparison clinics (CCs) in the same region. DESIGN: Analysis of longitudinal data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). SETTING: Rural southern Alberta. PARTICIPANTS: A community-based family medicine clinic and the 6 other CPCSSN clinics in the same region at the time of the study. MAIN OUTCOME MEASURES: levels, and blood pressure, as well as service use and measurement frequency. Rate of change per year was modeled longitudinally for each of the outcomes. RESULTS: < .001). CONCLUSION: This study describes a team-based comanagement organizational model and might provide useful commentary about organizational effectiveness in primary care. Although improvement in health outcomes cannot be directly attributed to any specific change in clinic organization, some statistically and likely clinically significant benefit was found associated with the service model of the RC in a relatively medically and socially challenged patient population and in a conservative evaluative design.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".