Dimensions and intensity of inter-professional teamwork in primary care: evidence from five international jurisdictions
Bibliographic record
Abstract
Background: Inter-professional teamwork in primary care settings offers potential benefits for responding to the increasing complexity of patients' needs. While it is a central element in many reforms to primary care delivery, implementing inter-professional teamwork has proven to be more challenging than anticipated. Objective: The objective of this study was to better understand the dimensions and intensity of teamwork and the developmental process involved in creating fully integrated teams. Methods: Secondary analyses of qualitative and quantitative data from completed studies conducted in Australia, Canada and USA. Case studies and matrices were used, along with face-to-face group retreats, using a Collaborative Reflexive Deliberative Approach. Results: Four dimensions of teamwork were identified. The structural dimension relates to human resources and mechanisms implemented to create the foundations for teamwork. The operational dimension relates to the activities and programs conducted as part of the team's production of services. The relational dimension relates to the relationships and interactions occurring in the team. Finally, the functional dimension relates to definitions of roles and responsibilities aimed at coordinating the team's activities as well as to the shared vision, objectives and developmental activities aimed at ensuring the long-term cohesion of the team. There was a high degree of variation in the way the dimensions were addressed by reforms across the national contexts. Conclusion: The framework enables a clearer understanding of the incremental and iterative aspects that relate to higher achievement of teamwork. Future reforms of primary care need to address higher-level dimensions of teamwork to achieve its expected outcomes.
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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 | 0.025 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".