Increasing take-home naloxone kit distribution to patients with substance use disorder before hospital discharge: a quality improvement project
Bibliographic record
Abstract
The ongoing drug toxicity crisis is a growing public health challenge in many countries across the world. Despite the WHO's recommendation of take-home naloxone (THN) kits as a cost-effective harm reduction strategy to prevent drug toxicity deaths, the Addiction Medicine Consult Team (AMCT) at Burnaby Hospital found that only 51% of their eligible patients were receiving a kit before discharge. In response, the AMCT created a quality improvement (QI) team with the aim of increasing their THN kit distribution rate on two hospital wards from 51% to over 80% within 10 months.Change ideas were implemented with the aim of targeting various components of the THN kit distribution process. Changes included adjusting THN kit inventory on wards, hosting education sessions for nurses, creating just-in-time training using nursing station whiteboards, streamlining the documentation process for nurses and standardising the ordering process for providers. The QI team collaborated with hospital interest holders including senior executives, nursing and pharmacy groups to facilitate change ideas. The project culminated with 4 months of sustained THN kit provision above 80%.The QI team is currently in talks with hospital operations to ensure that an effective documentation system will be integrated into the new electronic medical record system when the hospital transitions away from paper charting in 2025.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".