Cohort profile: the provincial opioid agonist treatment cohort in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Opioid Agonist Treatment (OAT) is the most effective intervention for opioid use disorder (OUD), but retention has decreased due to increasingly potent drugs like fentanyl. This cohort can be used retrospectively to observe trends in service utilization, healthcare integration, healthcare costs and patient outcomes. It also facilitates the design of observational studies to mimic a prospective design. METHODS: This study used linked administrative data from ICES to create a cohort of 137,035 individuals who received at least one prescription of methadone or buprenorphine/naloxone between 2014 and 2022. Data were linked using de-identified personal health numbers. Variables included age, sex, rurality, income, homelessness, and mental health conditions. Regional differences in OAT use, retention, and mortality were analyzed. RESULTS: Of the cohort, 56.1% began OAT after 2014. Southern Ontario participants more often started on methadone (53.2%), while Northern Ontario patients favored buprenorphine/naloxone (62.7%). Northern patients were younger, more likely to be female, live in rural areas, and face homelessness. The death rate was higher in Southern Ontario (22.1%) than in Northern Ontario (13.2%). Retention declined over time, with 73.4% of patients remaining in treatment at the study's end. CONCLUSIONS: The findings highlight regional disparities in OAT delivery and emphasize the need for region-specific strategies, particularly in rural areas, to improve retention and reduce mortality.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".