Prescribed safer opioid supply: A scoping review of the evidence
Bibliographic record
Abstract
BACKGROUND: Safer opioid supply programs provide prescription pharmaceutical opioids, often with supportive services, to people at high risk of experiencing harms related to substance use. However, questions regarding the effectiveness and safety of this practice remain. We conducted a scoping review of literature describing client outcomes from formal opioid supply programs providing prescriptions for pharmaceutical opioids, and the perceptions of involved clients/providers. METHODS: We performed a scoping review of peer-reviewed studies and grey literature published between January 1, 2012, to September 12, 2023. We included articles reporting either safer opioid supply client outcomes or clients/providers perspectives. Extracted data included study objectives, substance use patterns, client outcomes, client/provider perspectives, and estimates of effectiveness and/or harm. RESULTS: Our search yielded 1,597 articles. Following removal of duplicates and application of exclusion criteria, 24 publications comprising 17 peer-reviewed and seven grey literature publications were included in our study. We generated eight themes summarizing topics in the available literature: opioid-related toxicities, infectious complications, other clinical outcomes, client-reported outcomes, program access barriers, diversion, program retention, and costs to the healthcare system. Specific findings included low rates of opioid toxicities, improved physical and mental health, and improved quality of life among clients. A lack of access to adequate opioid doses and the limited range of opioid options offered within safer opioid supply programs was described by clients and providers as a potential reason for diversion and a barrier to program access. CONCLUSIONS: Generally, evidence suggests that safer opioid supply programs are beneficial to clients through measurable outcomes. However, the available literature has important limitations, including limited inferences about the effectiveness, safety, and potential for diversion within safer opioid supply programs. Further research is needed to support the ongoing evaluation of safer opioid supply programs as one component of a multifactorial response to escalating rates of substance-related harms.
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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 | 0.024 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.031 | 0.028 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".