Family Physicians Collaborating for Health System Integration: A Scoping Review
Bibliographic record
Abstract
Context: Ontario Health Teams (OHTs) serve as a new model for integrative and accessible healthcare. Core to these teams are family physicians and their ability to collaborate with other family physicians and healthcare providers. Whereas the factors for intra-organizational collaboration have been well-studied, the approaches employed to strengthen inter-organizational collaboration between family physicians, between family physician and other healthcare organizations as an integrated care network, are less understood. Objective: To explore the structures and processes that support family physicians’ collaboration for integrated healthcare around globe. Design and Analysis: A scoping review was undertaken based on JBI methodology and Preferred Reporting Items for Systematic Review and Meta-Analysis for Scoping Review (PRISMA_ScR) checklist. With the help of a medical science librarian, a search for academic literature published between 2000-2021 was conducted across databases (MEDLINE, EMBASE, EBSCOhost). Additionally, a search for relevant grey literature was performed. A thematic analysis was conducted to identify the key findings of the selected studies. Setting: Primary care in collaboration with other care organizations in community. Population studied: Family physicians actively involved in inter-organizational collaborative partnerships. Findings: Beginning with 11,831 references, title/abstract screening and full text review identified 32 studies as eligible for this review. Three key structural components were identified as critical to family physicians’ successful participation in inter-organizational partnerships: 1) ensuring shared vision/values in place, 2) having strong, positive leadership by family physicians, and 3) having well-defined decision-making procedures. Also, three key processes were identified as important to family physicians working with partners from other healthcare sectors: 1) ensuring effective communication between family physicians and partners, 2) having a collective sense of motivation for change and collaboration, and 3) building relationships on trust and not on hierarchical command. Conclusion: Family physicians hold unique positions in healthcare, and this review is the first to synthesize the best evidence for building collaborations between family physicians and other healthcare sectors. These findings will inform future discussions of collaborative efforts that support health system integration.
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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 | 0.048 | 0.166 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.028 | 0.029 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".