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Record W4318777696 · doi:10.46542/pe.2023.231.100108

Pharmacist prescribing training models in the United Kingdom, Australia, and Canada: Snapshot survey

2023· article· en· W4318777696 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePharmacy Education · 2023
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPharmacistPharmacyCurriculumMedicineGovernment (linguistics)Medical educationNursingFamily medicinePsychologyPedagogy

Abstract

fetched live from OpenAlex

Background: This study sought to identify the differences between training models for pharmacist prescribing across three countries according to the funding, model of prescribing the pharmacist will practice after training, training course framework, method of delivery, assessment, continuing professional development, and barriers and facilitators to enrolment. Methods: An online quantitative/qualitative snapshot survey was sent to academics of pharmacist prescribing courses and Deans of different pharmacy schools in the UK (n=49), Australia (n=12), and Canada (n=10). A narrative analysis was undertaken. Results: Seventeen pharmacy schools responded (24% response rate). The UK provides postgraduate training courses funded by the government. Canada incorporates prescribing competencies into entry-t- practice courses. Australia does not provide courses yet. Conclusion: Pharmacist prescribing is still under-utilised in many countries. Standardisation would reduce variation and improve uptake in countries implementing pharmacist prescribing roles. However, there is currently no international unified system or curriculum for pharmacists' prescribing courses.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.589
GPT teacher head0.550
Teacher spread0.039 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it