An international comparative policy analysis of opioid use disorder treatment in primary care across nine high-income jurisdictions
Bibliographic record
Abstract
BACKGROUND: Opioid use disorder (OUD) and opioid-related harms are current health priorities in many high-income countries such as Canada. Opioid agonist therapy (OAT) is an effective evidence-based treatment for OUD, but access is often limited. AIMS: To describe and compare OUD treatment policies across nine international jurisdictions, and to understand how they are situated within their primary care and health systems. METHODS: Using policy documents, we collected data on health systems, drug use epidemiology, drug policies, and OUD treatment from Australia, Canada, France, Germany, Ireland, Portugal, Sweden, Switzerland, and Taiwan. We used the health system dynamics framework and adapted definitions of low- and high-threshold treatment to describe and compare OUD treatment policies, and to understand how they may be shaped by their health systems context. RESULTS: Broad similarities across jurisdictions included the OAT pharmacological agents used and the need for supervised dosing; however, preferred OAT, treatment settings, primary care and specialist physicians' roles, and funding varied. Most jurisdictions had elements of lower-threshold treatment access, such as the availability of treatment through primary care and multiple OAT options, but the higher-threshold criteria of supervised dosing. CONCLUSIONS: From the Canadian perspective, there are opportunities to improve accessibility of OUD care by drawing on how different jurisdictions incorporate multidisciplinary care, regulate OAT medications, remunerate healthcare professionals, and provide funding for services.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".