A scoping review of research on the prescribing practice of Canadian pharmacists
Bibliographic record
Abstract
BACKGROUND: Pharmacists in Canada have been prescribing since 2007. This review aims to explore the volume, array and nature of research activity on Canadian pharmacist prescribing and to identify gaps in the existing literature. METHODS: We conducted a scoping review to examine the literature on prescribing by pharmacists in Canada according to methodological trends, research areas and key findings. We searched for peer-reviewed research articles and abstracts in the Ovid MEDLINE, Ovid EMBASE and International Pharmaceutical Abstracts databases without any date limitations. A standardized form was used to extract information. RESULTS: We identified 156 articles; of these, 26 articles and 12 abstracts met inclusion criteria. One-half of the research studies (20) used quantitative methods, including surveys, trials and experimental designs; 11 studies used qualitative methods and 7 used other methods. Research on pharmacist prescribing demonstrated an improvement in patient outcomes (13 studies), varied stakeholder perceptions (10 studies) and factors that influence this practice change (11 studies). Pharmacist prescribing was adopted when pharmacists practised patient-centred care. Stakeholders held contrasting perceptions of pharmacist prescribing. DISCUSSION: Canadian research has demonstrated the benefit of pharmacist prescribing on patient outcomes, which is not present in the international literature. Future research may consider a meta-analysis addressing the impact on patient health. Gaps in research include comparisons between provinces, effects on physicians' services, overall patient safety and access to health care systems and economic implications for society. CONCLUSION: A growing body of research on pharmacist prescribing has captured the early impact of prescribing on patient outcomes, perceptions of practice and practice change. Opportunities exist for pan-Canadian research that examines the system impact.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.036 | 0.056 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".