The challenge of promoting integration: conceptualization, implementation, and assessment of a pilot care delivery model for patients with type 2 diabetes.
Bibliographic record
Abstract
BACKGROUND: The Côte-des-Neiges diabetes pilot project strove to conceptualize, implement, and assess an integrated health care system for Type 2 diabetes. Using a disease management and population-based approach, a multidisciplinary team sought to (1). organize health care in an integrative framework, (2). promote behavior changes in patients to foster self-care, (3). introduce tools to allow family physicians to modify their practices, and (4). encourage local community action to support patients and providers. METHODS: Information from a needs assessment helped guide the development of the care model, which was implemented over a 1-year period. A preliminary assessment was undertaken using qualitative methods. Data were collected through in-depth interviews, focus groups, participant observation, and document analysis. RESULTS: (1). Physicians and patients appreciated having access to a multidisciplinary team and related services, and personalized communication was preferred to computerized links. (2). Patients also perceived the benefit of individualized assessment and self-care educational sessions allowing them to participate in their illness management. (3). A diabetes care flow sheet altered the management strategies of physicians. (4). Limited time prevented full development of networking efforts to promote community mobilization. CONCLUSIONS: Approaches to chronic diseases such as diabetes require integrative health care strategies to support patients and providers in their community. In spite of time constraints, patients perceived the value of education with increasing involvement in their illness, physicians reported changes in their practice, and steps were initiated to mobilize community 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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 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".