Opinions and preferences of British Columbia pharmacists and physicians on medication management services
Bibliographic record
Abstract
BACKGROUND: Medication management (MM) services are being provided by pharmacists across Canada in various forms, but pharmacist-physician collaboration is still not a routine practice in most jurisdictions. This survey aimed to gather pharmacists' and physicians' opinions and preferences for MM provision. METHODS: Two parallel, cross-sectional online surveys, including best-worst scaling tasks, were designed for pharmacists and physicians in British Columbia to capture and compare their preferences for a number of attributes of MM. RESULTS: Surveys were completed by 119 pharmacists and 146 physicians. Results indicate that pharmacists and physicians had similar opinions on many aspects of MM. Ninety-five percent of pharmacists and 69% of physicians believed that additional health services are needed to help patients optimize the use of their medications. However, the majority of each group felt that they were the most important health care professional in providing this service. Most pharmacists (79%) and some physicians (25%) thought that optimizing use of medications would result in both decreased costs and utilization to the health care system. Both pharmacists and physicians felt that the best attribute of an MM service would be if the services resulted in improved health and medication use for patients. Both groups were motivated by increased remuneration for MM; however, the relative strength of preference for this was higher among physicians. Interestingly, physicians valued improved medication adherence as a result of MM more highly than pharmacists did. DISCUSSION AND CONCLUSION: Most pharmacists and physicians agreed that improving patients' health and medication use would be the best attribute of MM and that there is a need for such services. However, physicians also had strong preferences for being remunerated for participating in MM provision.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".