Community pharmacists' perceptions of their collaborative working relationships with physicians for drug therapy management: An exploratory study
Bibliographic record
Abstract
Purpose. To determine community pharmacists' perceptions of their collaborative working relationships (CWRs) with physicians and of factors that contributed to or hindered collaborative drug therapy management (C-DTM). Methods. Ten semi-structured interviews were conducted with medical building pharmacists in Toronto who varied in gender and years of practice experience in Canada. Interpretive content analysis was performed. Results. Pharmacists desired a role in C-DTM to reduce the number of drug therapy problems; however, collaboration was uncommon. Pharmacists' best CWRs were at low, mid, and high levels. Attributes ascribed to CWRs were trust, working together, communication, sharing decisions and patient information, and patient referral. Factors that contributed to or hindered the development of CWRs at the practice and system levels were described. Conclusions. C-DTM is infrequent and does not occur to the extent that participants perceived was necessary to improve prescribing and patient outcomes. McDonough and Doucette's CWR Model (2001) should include third-party (i.e. receptionist) and systemic factors as influences on pharmacist-physician CWRs.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".