Evaluation of a Pharmacist-Led Clinic in a Canadian Remand Facility
Bibliographic record
Abstract
The health of Canadians in correctional facilities is poor when compared with the general population. Pharmacists effectively manage chronic illness and minor ailments; pharmacist-led prescriber clinics are being introduced in the community to improve access to care. However, there are no data on this model in correctional facilities. This article aims to evaluate the role of a pharmacist-led prescriber clinic in a provincial remand facility in Alberta, Canada, via a retrospective chart review of a weekly pharmacist-led clinic in a remand center from January to May of 2023. Data were collected for number of patients, drug therapy problems addressed, types and acceptance of interventions, and follow-up plans. Pharmacists saw an average of 8.8 patients per clinic with 1.9 interventions per patient. Most patients (83%) presented with untreated symptoms or indication. For many, pharmacists' interventions resulted in care that fully resolved concerns in a manner acceptable to patients, and 13% of cases were referred to alternative prescribers. This review adds to current literature on pharmacist intervention capacity; however, it does not include clinical outcomes. Pharmacists with prescribing authority in a clinic setting provide patients effective medication support, opening possibilities of expanding pharmacist practice models for quality patient care and increasing access to timely care.
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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 | 0.003 | 0.002 |
| 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".