Implications of interprofessional primary care team characteristics for health services and patient health outcomes: A systematic review with narrative synthesis
Bibliographic record
Abstract
Interprofessional primary care (IPPC) teams are promoted as an alternative to single profession physician practices in primary care with focus on preventive care and chronic disease management. Characteristics of teams can have an impact on their performance. We synthesized quantitative, qualitative or mixed-methods evidence addressing the design of IPPC teams. We searched Ovid MEDLINE, Embase, CINAHL, and PAIS using search terms focused on IPPC teams. Studies were included if they discussed the influence of team structure, organization, financial arrangements, or policies and procedures, or either health care processes or outputs, health outcomes, or costs, and were conducted in Australia, Canada, the United Kingdom or New Zealand between 2003 and 2016. We screened 11,707 titles, 5366 abstracts, and selected 77 full text articles (38 qualitative, 31 quantitative and 8 mixed-methods). Literature focused on the implications of team characteristics on team processes, such as teamwork, collaboration, or satisfaction of patients or providers. Despite heterogeneity of contexts, some trends are observable: shared space, common vision and goals, clear definitions of roles, and leadership as important to good teamwork. The impacts of these on health care outputs or patient health are not clear. To move the state of knowledge beyond perception of what works well for IPPC teams, researchers should focus on quantitative causal inference about the linkages between team characteristics and patient health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".