British Columbia’s Safer Opioid Supply Policy and Opioid Outcomes
Bibliographic record
Abstract
Importance: In March 2020, British Columbia, Canada, became the first jurisdiction globally to launch a large-scale provincewide safer supply policy. The policy allowed individuals with opioid use disorder at high risk of overdose or poisoning to receive pharmaceutical-grade opioids prescribed by a physician or nurse practitioner, but to date, opioid-related outcomes after policy implementation have not been explored. Objective: To investigate the association of British Columbia's Safer Opioid Supply policy with opioid prescribing and opioid-related health outcomes. Design, Setting, and Participants: This cohort study used quarterly province-level data from quarter 1 of 2016 (January 1, 2016) to quarter 1 of 2022 (March 31, 2022), from British Columbia, where the Safer Opioid Supply policy was implemented, and Manitoba and Saskatchewan, where the policy was not implemented (comparison provinces). Exposure: Safer Opioid Supply policy implemented in British Columbia in March 2020. Main Outcomes and Measures: The main outcomes were rates of prescriptions, claimants, and prescribers of opioids targeted by the Safer Opioid Supply policy (hydromorphone, morphine, oxycodone, and fentanyl); opioid-related poisoning hospitalizations; and deaths from apparent opioid toxicity. Difference-in-differences analysis was used to compare changes in outcomes before and after policy implementation in British Columbia with those in the comparison provinces. Results: The Safer Opioid Supply policy was associated with statistically significant increases in rates of opioid prescriptions (2619.6 per 100 000 population; 95% CI, 1322.1-3917.0 per 100 000 population; P < .001) and claimants (176.4 per 100 000 population; 95% CI, 33.5-319.4 per 100 000 population; P = .02). There was no significant change in prescribers (15.7 per 100 000 population; 95% CI, -0.2 to 31.6 per 100 000 population; P = .053). However, the opioid-related poisoning hospitalization rate increased by 3.2 per 100 000 population (95% CI, 0.9-5.6 per 100 000 population; P = .01) after policy implementation. There were no statistically significant changes in deaths from apparent opioid toxicity (1.6 per 100 000 population; 95% CI, -1.3 to 4.5 per 100 000 population; P = .26). Conclusions and Relevance: Two years after its launch, the Safer Opioid Supply policy in British Columbia was associated with higher rates of safer supply opioid prescribing but also with a significant increase in opioid-related poisoning hospitalizations. These findings will help inform ongoing debates about this policy not only in British Columbia but also in other jurisdictions that are contemplating it.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".