Evaluation of General Practice Pharmacists: Study Protocol to Assess Interprofessional Collaboration and Team Effectiveness
Bibliographic record
Abstract
The inclusion of pharmacists into general practices has expanded in Australia. However, there is a paucity of research examining interprofessional collaboration and team effectiveness after including a pharmacist into the general practice team in primary or community care. This is a protocol for a cross-national comparative mixed-methods study to (i) investigate interprofessional collaboration and team effectiveness within the general practice team after employing pharmacists in general practices in the Australian Capital Territory (ACT) and (ii) to compare interprofessional collaboration and team effectiveness of pharmacists in general practice across Australia with international sites. The first objective will be addressed through a multiphase sequential explanatory mixed-method design, using surveys and semi-structured interviews. The study will recruit general practice pharmacists, general practitioners, and other health professionals from eight general practices in the ACT. Quantitative and qualitative results will be merged during interpretation to provide complementary perspectives of interprofessional collaboration. Secondly, a quantitative descriptive design will compare findings on interprofessional collaboration (professional interactions, relationship initiation, exchange characteristics, and commitment to collaboration) and team effectiveness of general practice pharmacists in Australia with international sites from Canada and the United Kingdom. The results of the study will be used to provide recommendations on how to best implement the role of general practice pharmacists across Australia.
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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 | 0.074 | 0.054 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 0.012 |
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".