Organizational Restructuring of Regional Pharmacy Services to Enable a New Pharmacy Practice Model
Bibliographic record
Abstract
Models of pharmacy practice are currently the focus of considerable attention within the North American pharmacy profession. In Canada, through the “Blueprint for Pharmacy” initiative, a vision and implementation plan for pharmacy practice in Canada have been established and endorsed by all pharmacy organizations. Three key objectives of the Blueprint are to incorporate technology, to enhance training and utilization of pharmacists and technicians, and to enhance accountability to patients. If pharmacists are to assume greater responsibility and accountability for management of medication therapy, they will need to spend more time performing direct patient care and less time performing technical drug distribution activities. These plans for the profession of pharmacy, when viewed in aggregate, call for transformative change (whereby the culture of pharmacy is changed), rather than transitional change (whereby only a process is changed). However, there is debate in the literature regarding the best approach for initiating and sustaining transformational change initiatives within organizations. This article describes the process followed and lessons learned during a Blueprint-associated transformative change initiative: organizational restructuring and implementation of a new pharmacy practice model within a large health authority.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".