“Before medically advised” hospital discharge and the risk of subsequent drug overdose: A case‐crossover analysis
Bibliographic record
Abstract
BACKGROUND: Patient-initiated or "before medically advised" (BMA) hospital discharge is more common among people who use drugs. Transitions of care can be destabilizing and might increase the risk of subsequent illicit drug overdose. OBJECTIVES: This study sought to evaluate whether BMA discharge is associated with an increased risk of subsequent drug overdose (primary objective) and whether physician-advised discharge is associated with an increased risk of subsequent drug overdose (secondary objective). METHODS: We performed a case-crossover analysis of population-based linked administrative health data for individuals experiencing an overdose between 2016 and 2019 in British Columbia, Canada. Using conditional logistic regression, we compared the likelihood of hospital discharge in the 28 days before overdose (the "pre-overdose interval") to the likelihood of hospital discharge in two self-matched 28-day control intervals ending 26 and 52 weeks before overdose. RESULTS: Over the 3.5-year study interval, 235 of 27,584 (0.9%) pre-overdose intervals and 189 of 55,168 (0.3%) control intervals included a BMA discharge, suggesting that BMA discharge was associated with a twofold increase in the risk of subsequent drug overdose (adjusted odds ratio [aOR], 2.08; 95% confidence interval [95% CI], 1.68-2.58; p < 0.001). Physician-advised hospital discharge was also a risk factor for subsequent overdose, occurring in 1350 of 27,584 (4.9%) pre-overdose intervals and 1625 of 55,168 (2.9%) control intervals (aOR, 1.39; 95% CI, 1.27-1.52; p < 0.001). CONCLUSIONS: Both BMA and physician-advised hospital discharge are independently associated with transient increases in the risk of subsequent illicit drug overdose. Better in-hospital treatment of substance use disorder and novel means of post-discharge outreach should be deployed to reduce this risk.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".