Trends in injectable buprenorphine prescribing in Canada: A descriptive analysis in five Canadian Provinces
Bibliographic record
Abstract
BACKGROUND: Injectable extended-release buprenorphine (BUP-ER) (Sublocade®) is a newer form of opioid agonist therapy (OAT) administered monthly. It was listed on formularies across Canada in February 2020, expanding the options for OAT across the country. This study describes rates of injectable BUP-ER uptake in five provinces to compare access to this novel medication across Canada. METHODS: We conducted a retrospective time-series analysis among individuals who received injectable BUP-ER in British Columbia, Alberta, Saskatchewan, Manitoba, and Ontario from February 1, 2020, to March 31, 2022. The primary outcome was the population-adjusted rate of injectable BUP-ER in each province, with secondary analyses exploring rates by urban/rural location, and the number of prescribers of injectable BUP-ER per 100,000 population. RESULTS: In total, 6528 individuals were treated with injectable BUP-ER, with the majority in British Columbia (29.0 %) and Ontario (47.0 %). By March 2022, the rate of BUP-ER use was highest in British Columbia (16.6 per 100,000), and lowest in Ontario (9.1 per 100,000). The rate of BUP-ER use was higher in rural areas (15.5 per 100,000) compared to urban centres (10.6 per 100,000), and British Columbia had the highest rate of prescribers per 100,000 population (5.9) compared to Ontario (2.2), Alberta (2.3), Saskatchewan (3.4) and Manitoba (3.5) by the end of Q1-2022. CONCLUSION: Uptake of BUP-ER varied geographically since being approved by Health Canada. More rapid uptake in rural areas is reassuring and suggests that this form of OAT may be supporting treatment access to those with barriers to more traditional treatment formulations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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, 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".