Practice Change Challenges and Priorities: A National Survey of Practising Pharmacists
Bibliographic record
Abstract
Background: Vision and action plans have been created to address the future of pharmacy and help pharmacists progress into expanded roles in order to provide more patient-centred care. To assess the thoughts and perceptions of pharmacists in these new roles, a survey was conducted among practising pharmacists in Canada. Methods: A Web-based survey, developed as part of the Canadian Pharmacists Association's Moving Forward initiative, was open to all practising pharmacists in September and October of 2007. This survey educated pharmacists on potential future roles and sought to gain feedback on the human resource challenges and priorities that might result from the proposed practice changes. Results: From the 1003 respondents, it was found that the majority of pharmacist time is spent on dispensing duties. However, over 60% of pharmacists felt that it was time to begin taking on new responsibilities and over 70% of pharmacists want to be performing expanded clinical duties within 5 years. Discussion: It is encouraging to see that most pharmacists are open to new expanded clinical roles in the near future. Despite the challenges identified, such as the need for additional training, increases in workload and stress and expected poor physician acceptance, it was felt that changes would result in improved patient health outcomes and better personal job satisfaction. Conclusion: Pharmacists have responded positively to the proposed vision for the future of pharmacy and are eager to move away from the traditional dispensing role to an expanded clinical role that more fully utilizes their unique skills and knowledge.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".