Supervised Tablet Injectable Opioid Agonist Therapy (TiOAT): A Strategy to Address Safer Supply for Individuals With an Opioid Use Disorder?
Bibliographic record
Abstract
North America is in the midst of an overdose crisis, with up to 130 Americans dying daily from a preventable drug overdose. Opioids account for 70% of overdose deaths. Despite government efforts to improve access to opioid use disorder (OUD) treatment and the implementation of various harm reduction initiatives, overdose mortality remains unacceptably high. Although effective treatments exist for OUD (eg, opioid agonist therapies like buprenorphine/naloxone and methadone), many individuals do not achieve stabilization with these medications. Tablet injectable opioid agonist therapy (TiOAT) is an initiative being piloted in British Columbia to provide witnessed access to a safer opioid supply for individuals with treatment-refractory OUD. The program offers participants a safer opioid supply through physician-prescribed pharmaceutical-grade hydromorphone tablets. TiOAT is suitable for individuals with severe OUD who are actively injecting opioids and are refractory to conventional OUD treatment. As such, a scale-up of the TiOAT program may be a feasible alternative to address persistent opioid-related deaths in North America, while minimizing potential harms associated with unwitnessed safer supply opioid prescribing (eg, diversion and overdose). Although a comprehensive evaluation of TiOAT is of critical importance (including an assessment of the program's adverse events), completion of the evaluation should not preclude scale-up of the program in the interim as a strategy to reduce opioid-related harms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".