"Trial" prescriptions to reduce drug wastage: results from Canadian programs and a community demonstration project.
Bibliographic record
Abstract
OBJECTIVE: To determine the acceptability of a program to avoid drug wastage through "trial" prescriptions. STUDY DESIGN: Cross-sectional survey, followed by a 9-month demonstration project. METHODS: Consultants to trial prescription programs operated by 2 public- and 3 private-sector drug plans in Canada were surveyed. All of the trial prescription programs were voluntary. The demonstration project involved 215 English-speaking adults who filled a "new" prescription for an angiotensin-converting enzyme inhibitor, beta-blocker, or calcium channel blocker (CCB) in 1 of 16 Peterborough, Ontario pharmacies. Patients received a 7-day supply of medication and a reminder card on which the dispensing pharmacist recorded the mutually agreed date and time the patient would be contacted to assess the results of the "trial." Patients who tolerated the medication received the balance of their original prescription. RESULTS: Most patients (86%) who were offered trials in the demonstration project accepted them, and most (82%) who accepted them found them helpful. The proportion of patients who received the balance varied by program, ranging from 47.1% to 86.6%. The dollar value of the wastage avoided through trial prescriptions varied by drug class. This was driven largely by differences in the unit cost of the medications, but also to a lesser extent by larger prescriptions for CCBs. CONCLUSIONS: Trial prescriptions were acceptable to patients and, if focused on specific medications, could reduce the direct cost of drug wastage. More work is needed to define the conditions under which trial prescription programs are feasible for pharmacists and drug plans.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".