Types of Opioid Harms in Canadian Hospitals: Comparing Canada and Australia
Bibliographic record
Abstract
Harms related to opioid use (whether prescribed or obtained illicitly) represent a growing cause of concern in developed countries, including Australia and Canada.This report examines the characteristics of opioid-related care visits to emergency departments (EDs) or hospital admissions and groups them into five distinct harm profiles. These profiles and their respective distributions illustrate how opioid-related harms differ across care settings in Canada. Opioid dependence and accidental poisoning were the more prominent types of harm seen in EDs, with a rate of 39.2 and 38.0 visits per 100,000 population, respectively. Within the in-patient population, rates of hospital stays were comparatively higher (26.8 per 100,000) for adverse drug reactions compared to other opioid-related harms. In addition to differing patterns in care settings, these harm groups differed on length of hospital stay, types of care received, other drugs involved and demographic variables such as age, gender and income.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".