General practitioners’ experiences with, views of, and attitudes towards, general practice-based pharmacists: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: There is limited United Kingdom (UK) literature on general practice-based pharmacists' (PBPs') role evolution and few studies have explored general practitioners' (GPs') experiences on pharmacist integration into general practice. Therefore, this study aimed to investigate GPs' experiences with, views of, and attitudes towards PBPs in Northern Ireland (NI). METHODS: A paper-based self-administered questionnaire comprising four sections was mailed in 2019 to 329 general practices across NI and was completed by one GP in every practice who had most contact with the PBP. Descriptive analyses were used and responses to open-ended questions were analysed thematically. RESULTS: The response rate was 61.7% (203/329). There was at least one PBP per general practice. All GPs had face-to-face meetings with PBPs, with three-quarters (78.7%, n = 159) meeting with the PBP more than once a week. Approximately two-thirds of GPs (62.4%, n = 126) reported that PBPs were qualified as independent prescribers, and 76.2% of these (n = 96/126) indicated that prescribers were currently prescribing for patients. The majority of GPs reported that PBPs always/very often had the required clinical skills (83.6%, n = 162) and knowledge (87.0%, n = 167) to provide safe and effective care for patients. However, 31.1% (n = 61) stated that PBPs only sometimes had the confidence to make clinical decisions. The majority of GPs (> 85%) displayed largely positive attitudes towards collaboration with PBPs. Most GPs agreed/strongly agreed that PBPs will have a positive impact on patient outcomes (95.0%, n = 192) and can provide a better link between general practices and community pharmacists (96.1%, n = 194). However, 24.8% of GPs (n = 50) were unclear if the PBP role moved community pharmacists to the periphery of the primary care team. An evaluation of the free-text comments indicated that GPs were in favour of more PBP sessions and full-time posts. CONCLUSION: Most GPs had positive views of, and attitudes towards, PBPs. The findings may have implications for future developments in order to extend integration of PBPs within general practice, including the enhancement of training in clinical skills and decision-making. Exploring PBPs', community pharmacists' and patients' views of this role in general practice is required to corroborate study findings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".