Comprehensive substance use services within primary care settings: The Safer Opioid Supply program at London InterCommunity Health Centre
Bibliographic record
Abstract
SETTING: This paper describes the Safer Opioid Supply (SOS) program, a public health intervention in London, Ontario, in response to the toxic unregulated drug supply which is driving the overdose crisis in Canada. INTERVENTION: The London InterCommunity Health Centre (LIHC) SOS program provides comprehensive harm reduction and primary health care services to individuals at risk of overdose from the toxic drug supply. Clients are prescribed high-dose pharmaceutical opioids as replacement for unregulated toxic substances within a low-barrier primary care clinic, with wraparound interdisciplinary social services, embedded in the Ontario Community Health Centre model of care. The program serves people dependent on street-acquired fentanyl who are experiencing medical issues due to their substance use, and who are experiencing challenges accessing other forms of healthcare. OUTCOMES: A qualitative analysis of interviews and focus groups conducted in 2022-2023 with staff (n=5) and clients (n=20) was used to explore impacts of the SOS program. Four outcomes are discussed: safer supply as crucial to engage clients in primary care; safer supply as one component of comprehensive care; the use of a harm reduction approach; and challenges with limited medication options and program capacity. IMPLICATIONS: Positive health and social outcomes demonstrate the utility of embedding comprehensive substance use services within a primary health care model to address health and social complexity among people who use drugs amid the continuing toxic drug crisis. Responding to an increasingly volatile unregulated supply of drugs, having limited medication options, and providing comprehensive care without long-term funding remain ongoing challenges.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".