Contextual levers for team-based primary care: lessons from reform interventions in five jurisdictions in three countries
Bibliographic record
Abstract
Background: Most Western nations have sought primary care (PC) reform due to the rising costs of health care and the need to manage long-term health conditions. A common reform-the introduction of inter-professional teams into traditional PC settings-has been difficult to implement despite financial investment and enthusiasm. Objective: To synthesize findings across five jurisdictions in three countries to identify common contextual factors influencing the successful implementation of teamwork within PC practices. Methods: An international consortium of researchers met via teleconference and regular face-to-face meetings using a Collaborative Reflexive Deliberative Approach to re-analyse and synthesize their published and unpublished data and their own work experience. Studies were evaluated through reflection and facilitated discussion to identify factors associated with successful teamwork implementation. Matrices were used to summarize interpretations from the studies. Results: Seven common levers influence a jurisdiction's ability to implement PC teams. Team-based PC was promoted when funding extended beyond fee-for-service, where care delivery did not require direct physician involvement and where governance was inclusive of non-physician disciplines. Other external drivers included: the health professional organizations' attitude towards team-oriented PC, the degree of external accountability required of practices, and the extent of their links with the community and medical neighbourhood. Programs involving outreach facilitation, leadership training and financial support for team activities had some effect. Conclusion: The combination of physician dominance and physician aligned fee-for-service payment structures provide a profound barrier to implement team-oriented PC. Policy makers should carefully consider the influence of these and our other identified drivers when implementing team-oriented PC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".