Sustainability pharmacy assistants in large urban hospital system
Bibliographic record
Abstract
OBJECTIVES: The financial feasibility and practical viability of implementing a Sustainability Pharmacy Assistant Position (SPAP) program were assessed in this study. Human resources operating independently of the site were utilized by this innovative strategy to process medication returns for redistribution. METHODS: The cost-effectiveness of employing SPAPs solely responsible for processing medication returns for redistribution was assessed in a 3-month pilot service at two hospital sites. Funding was sourced from unfilled positions, and the SPAP's tasks and schedule were coordinated with site staff. Data on medication returns and workflow were collected and analysed as well as labor costs and expenses to evaluate cost savings and operational impact. The results of the pilot were extrapolated to yield an estimate of the impacts of an expanded SPAP program for 12 hospitals in the area. KEY FINDINGS: The pilot service revealed net savings from SPAPs at two hospitals of $19 951. Extrapolating the net savings to two SPAPs working for a full year and servicing 12 Fraser Health hospitals, the return on investment was $6.51 per dollar invested for the first year. SPAPs are highly cost-effective and address previous problems with site-based resource issues. The SPAP was smoothly integrated into each site's workflow, with no disruptions or complaints from staff, allowing them to focus on their primary duties. CONCLUSIONS: Costs are effectively reduced, and operational efficiency is enhanced by the SPAPs through the processing of medication returns for redistribution. Given these positive outcomes, plans are in place to expand the program to additional sites, and similar initiatives are recommended for other healthcare systems. Financial savings are yielded by this approach, along with environmental benefits through the reduction of medication waste and incineration.
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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 | 0.001 | 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 | 0.001 |
| 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".