Obesity services planning framework for interprofessional primary care organizations
Bibliographic record
Abstract
Aim We report on a formative project to develop an organization-level planning framework for obesity prevention and management services. BACKGROUND: It is common when developing new services to first develop a logic model outlining expected outcomes and key processes. This can be onerous for single primary care organizations, especially for complex conditions like obesity. METHODS: The initial draft was developed by the research team, based on results from provider and patient focus groups in one large Family Health Team (FHT) in Ontario. This draft was reviewed and activities prioritized by 20 FHTs using a moderated electronic consensus process. A national panel then reviewed the draft. Findings Providers identified five main target groups: pregnancy to 2, 3-12, 13-18, 18+ years at health risk, and 18+ with complex care needs. Desired outcomes were identified and activities were prioritized under categories: raising awareness (eg, providing information and resources on weight-health), identification and initial management (eg, wellness care), follow-up management (eg, group programs), expanded services (eg, availability of team services), and practice initiatives (eg, interprofessional education). Overall, there was strong support for raising awareness by providing information on the weight-health connection and on community services. There was also strong support for growth assessment in pediatric care. In adults, there was strong support for wellness care/health check visits and episodic care to identify people for interventions, for group programs, and for additional provider education. CONCLUSIONS: Joint development by different teams proved useful for consensus on outcomes and for ensuring relevancy across practices. While priorities will vary depending on local context, the basic descriptions of care processes were endorsed by reviewers. Key next steps are to trial the use of the framework and for further implementation studies to find optimally effective approaches for obesity prevention and management across the lifespan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".