Fostering collective leadership to improve integrated primary care: lessons learned from the PriCARE program
Bibliographic record
Abstract
Case management (CM) is an intervention for improving integrated care for patients with complex care needs. The implementation of this complex intervention often raises opportunities for change and collective leadership has the potential to optimize the implementation. However, the application of collective leadership in real-world is not often described in the literature. This commentary highlights challenges faced during the implantation of a CM intervention in primary care for people with complex care needs, including stakeholders' buy-in and providers' willingness to change their practice, selection of the best person for the case manager position and staff turnover. Based on lessons learned from PriCARE research program, this paper encourages researchers to adopt collective leadership strategies for the implementation of complex interventions, including promoting a collaborative approach, fostering stakeholders' engagement in a trusting and fair environment, providing a high level of communication, and enhancing collective leadership attitudes and skills. The learnings from the PriCARE program may help guide researchers for implementing complex healthcare interventions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| 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".