Collaborative practice in a global health context: Common themes from developed and developing countries
Bibliographic record
Abstract
This paper reports on a study commissioned by the World Health Organization (WHO) to explore common themes of collaborative practice. The WHO requested global clarification of (1) the nature of collaborative practice, (2) its perceived importance, and (3) strategies for systematizing collaborative practice throughout national health systems. While there are many interpretations of collaborative practice around the world, there was a need to ascertain common underlying themes that illustrate good practice in both developed and developing countries to inform an international Framework for Action. A multiple case study design was used to examine collaborative practice in primary health care and commonalities across countries. Staff at each of WHO's six regional offices invited key informants in one or two primary health care organizations where collaborative practice was the model of care to complete case studies. Ten case studies were received from ten different countries, representing all six WHO regions. The results are described according to the study's three areas of focus: describing collaborative practice globally, the shared importance of collaborative practice, and systematizing collaborative practice. Collaborative practice requires a strong political framework that encourages interprofessional education and teamworking. Shared governance models and enabling legislation are required. At a practical level, interprofessional health care teams function most efficiently with shared clinical pathways and a common patient record.
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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 | 0.036 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.018 | 0.029 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.027 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".