Developing recommendations and actions for integrated services delivery through primary health care teams in Canada: a deliberative dialogue approach for a national knowledge translation event
Bibliographic record
Abstract
Primary health care teams are a key strategy in providing integrated care, particularly for patients with multiple chronic conditions. Despite a strong commitment to improving primary health care through team-based care globally, challenges to its implementation remain. A comparative policy analysis was conducted in four Canadian provinces (British Columbia, Alberta, Ontario, and Quebec) to examine the policies and structures supporting service integration for patients with two or more chronic conditions through primary health care teams. Results are reported on Phase 3 of the project, including a national knowledge translation event to refine recommendations and develop actions for implementing recommendations related to team-based primary health care in policy and practice. Our virtual knowledge translation event took place in June 2022; with 25 participants including policymakers, decision-makers, providers, patients and researchers. Eight key recommendations were discussed and revised with feedback and strategies for implementation developed. Five themes were identified from the discussions: 1) composition of the team and access; 2) communication and electronic health records; 3) remuneration; 4) patient engagement; and performance measurement. Recommendations for policy and practice are outlined and compared to existing Canadian and international literature.
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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 | 0.141 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.039 | 0.016 |
| Scholarly communication | 0.025 | 0.008 |
| Open science | 0.012 | 0.021 |
| Research integrity | 0.021 | 0.030 |
| Insufficient payload (model declined to judge) | 0.008 | 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".