Evaluating pharmacist prescribing for minor ailments
Bibliographic record
Abstract
OBJECTIVES: Saskatchewan is the second Canadian province to allow pharmacists to prescribe medications for minor ailments and the only province that remunerates for this activity. The aim of this project was to determine whether patients prescribed such treatment by a pharmacist symptomatically improve within a set time frame. METHODS: Pharmacists were asked to hand a study-invitation card to anyone for whom they prescribed a medication for a minor ailment during the 1-year study period. Consenting participants contacted the study researchers directly and were subsequently instructed to complete an online questionnaire at the appropriate follow-up time. KEY FINDINGS: Ninety pharmacies in Saskatchewan participated, accruing 125 participants. Cold sores were the most common minor ailment (34.4%), followed by insect bites (20%) and seasonal allergies (19.2%). Trust in pharmacists and convenience were the most common reasons for choosing a pharmacist over a physician, and 27.2% would have chosen a physician or emergency department if the minor ailment service were not available. The condition significantly/completely improved in 80.8%; only 4% experienced bothersome side effects. Satisfaction with the pharmacist and service was strong; only 5.6% felt a physician would have been more thorough. CONCLUSIONS: Participants were very satisfied with their symptomatic improvement and with the service in general, albeit for a small number of conditions. Participants reported getting better, and side effects were not a concern. These results are encouraging for pharmacists; however, a comparison of physician care with pharmacist care and unsupported self-care is required to truly know the benefit of pharmacist prescribing.
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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 | 0.004 | 0.017 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".