Stakeholders' views and experiences of pharmacist prescribing: a systematic review
Bibliographic record
Abstract
AIMS: The aims of this systematic review were to: (1) critically appraise, synthesize and present the available evidence on the views and experiences of stakeholders on pharmacist prescribing and; (2) present the perceived facilitators and barriers for its global implementation. METHODS: Medline, CINAHL, International Pharmaceutical Abstracts, PsychArticles and Google Scholar databases were searched. Study selection, quality assessment and data extraction were conducted independently by two reviewers. A narrative approach to data synthesis was undertaken due to heterogeneity, the nature of study types and outcome measures. RESULTS: Sixty-five studies were identified, mostly from the UK (n = 34), followed by Australia (n = 13), Canada (n = 6) and USA (n = 5). Twenty-seven studies reported pharmacists' perspectives, with fewer studies focusing on patients' (n = 12), doctors' (n = 6), the general public's (n = 4), nurses' (n = 1), policymakers' (n = 1) and multiple stakeholders' (n = 14) perspectives. Most reported positive experiences and views, regardless of stage of implementation. The main benefits described were: ease of patient access to healthcare services, improved patient outcomes, better use of pharmacists' skills and knowledge, improved pharmacist job satisfaction, and reduced physician workload. Any lack of support for pharmacist prescribing was largely in relation to: accountability for prescribing, limited pharmacist diagnosis skills, lack of access to patient clinical records, and issues concerning organizational and financial support. CONCLUSION: There is an accumulation of global evidence of the positive views and experiences of diverse stakeholder groups and their perceptions of facilitators and barriers to pharmacist prescribing. There are, however, organizational issues to be tackled which may otherwise impede the implementation and sustainability of pharmacist prescribing.
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 | 0.035 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".