Breathing easier: removing maintenance inhalers from hospital wardstock for cost savings and waste reduction
Bibliographic record
Abstract
BACKGROUND: Maintenance inhalers are commonly used for long-term management of respiratory conditions. These multidose devices contain several weeks of medication, are expensive, and have significant global emissions impact. As these medications are not useful for managing acute symptoms, it was questioned whether keeping these inhalers in hospital wardstock locations may contribute to inhaler wastage. OBJECTIVE: To determine if removal of maintenance inhalers from wardstock would reduce the number of inhalers dispensed. METHODS: This was a prospective quality improvement study examining medication utilization data within the Fraser Health Authority. An inventory report was run to determine where maintenance inhalers were located to select hospital sites to target. Maintenance inhalers were removed from wardstock at chosen sites and utilization data from 6 months prior to removal were compared to 6 months post-removal. Outcomes reported were change in number of inhalers dispensed, change in number of inhalers dispensed per active-order-day, change in expenditure, and change in carbon emissions. Informal assessments on workload and access were made during the 6-month follow-up period. KEY FINDINGS: Within 6 months after maintenance inhalers were removed from wardstock at two hospitals, 119 fewer inhalers and 43 fewer dry powder inhaler capsules were dispensed, representing $4541 in savings and a reduction in carbon emissions equivalent to 6,770.5 km driven by a typical gasoline car-enough to drive across Canada from the Pacific to the Atlantic coast. No indications of delayed access or increased workload were reported. CONCLUSIONS: Routine reassessments of wardstock supply of maintenance inhalers or medications that are not acutely needed may be useful in alignment with formulary budget and planetary health.
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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 | 0.002 |
| 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 | 0.001 |
| 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".