Patient Feedback on Pharmacist Prescribing for Minor Ailments in a Canadian Province
Bibliographic record
Abstract
Background: Pharmacists have been given authority in many Canadian provinces to go beyond simply recommending over-the-counter medicines to patients with minor ailments. In Saskatchewan, they can prescribe medicines normally under the sole control of physicians for 17 conditions. An evaluation program is underway to assess the value of the program. Methods: Adults were recruited over a one-year period and were eligible for inclusion if prescribed an agent for an applicable condition. Pharmacists from 40 pharmacies participated in identifying people who received the service. Of patients agreeing to participate, a link to an online survey was provided. The survey included items on clinical improvement, care options, and patient confidence in knowing when to seek a physician for a minor ailment. Results: Forty-eight people were involved in prescribing encounters, with the majority seeking help for themselves. All but one saw their symptoms improve subsequent to pharmacist assistance, most often to a significant extent. Satisfaction with the service was high. Convenience and trust in pharmacists were primary reasons for choosing the service over medical care (rather than an issue potentially more worrisome such as not having a family physician). Had this service not been in place, 30.6% of those asking for help would have gone to a medical clinic or emergency room. Seventy-five percent were (at least) very confident in knowing when to seek a physician (rather than a pharmacist) for such conditions. Conclusion: Information on the clinical outcomes of pharmacist-led minor ailment care is starting to accrue in Saskatchewan. While the numbers are extremely low to date, what has become available suggests the service is of value to the citizens of the province, it is chosen for appropriate reasons, and is of an acceptable standard of care. Conflict of Interest We declare no conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received), employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties. However, the authors are pharmacists licensed within the province and bring this perspective to this evaluation of a pharmacy-based program. Type: Original Research
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".