‘It's showed me the skills that he has’: pharmacists' and mentors' views on pharmacist supplementary prescribing
Bibliographic record
Abstract
OBJECTIVES: Supplementary prescribing has seen pharmacists assume greater responsibility for prescribing in collaboration with doctors. This study explored the context and experiences, in relation to the practice of supplementary prescribing, of pharmacists and physicians (who acted as their training mentors) at least 12 months after pharmacists had qualified as supplementary prescribers. METHODS: The setting was primary and secondary healthcare sectors in Northern Ireland. Pharmacists and mentors who had participated in a pre-training study were invited to take part. All pharmacists (n = 47) were invited to participate in focus groups, while mentors (n = 35) were asked to participate in face-to-face semi-structured interviews. The research took place between May 2005 and September 2007. All discussions and interviews were audiotaped, transcribed and analysed using constant comparison. KEY FINDINGS: Nine pharmacist focus groups were convened (number per group ranging from three to six; total n = 40) and 31 semi-structured interviews with mentors were conducted. The six main themes that emerged were optimal practice setting, professional progression for prescribing pharmacists, outcomes for prescribing pharmacists, mentors and patients, relationships, barriers to implementation and the future of pharmacist prescribing. Where practised, pharmacist prescribing had been accepted, worked best for chronic disease management, was perceived to have reduced doctors' workload and improved continuity of care for patients. However, three-quarters of pharmacists qualified to practise as supplementary prescribers were not actively prescribing, largely due to logistical and organisational barriers rather than inter-professional tensions. Independent prescribing was seen as contentious by mentors, particularly because of the diagnostic element. CONCLUSIONS: Supplementary prescribing has been successful where it has been implemented but a number of barriers remain which are preventing the wider acceptance of this practice innovation.
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".