Comparing the contribution of prescribed opioids to opioid-related hospitalizations across Canada: A multi-jurisdictional cross-sectional study
Bibliographic record
Abstract
BACKGROUND: The Canadian opioid crisis is a complex, multifaceted problem involving prescribed, diverted and illicitly manufactured opioids. This study sought to characterize the contribution of prescribed opioids to opioid-related hospitalizations in Canada. METHODS: We conducted a cross-sectional study of all individuals who were admitted to hospital for opioid toxicity in British Columbia (BC), Manitoba and Ontario between April 2015 and March 2016. We used prescription claims to ascertain active prescription opioid use at time of hospital admission. In secondary analyses, we defined recent opioid prescriptions as those that were dispensed in the 30 and 180 days up to and including admission, and the prevalence of active co-prescription of benzodiazepines with opioids at time of overdose. RESULTS: We identified 2599 instances of opioid toxicity over the study period. In BC, 34.1% of hospital visits for overdose occurred in people with an active opioid prescription, compared to 52.2% (47 of 90) in Manitoba and 52.8% (804 of 1524) in Ontario. However, active opioid prescriptions prior to overdose varied significantly by age and sex. Co-prescription of opioids and benzodiazepines prior to overdose ranged from 17.1% in BC to 35.6% in Manitoba. CONCLUSIONS: There remains an important ongoing contribution of prescribed opioids to overdoses across Canada, but non-prescribed opioids play a growing role, particularly in BC. These findings underscore the importance of more judicious opioid prescribing, harm reduction programs, and improved access to addiction care for people with an opioid use disorder.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".