Service utilization patterns and characteristics among clients of integrated supervised consumption sites in Toronto, Canada
Bibliographic record
Abstract
INTRODUCTION: Supervised consumption services (SCS), intended to reduce morbidity and mortality among people who inject drugs, have been implemented in a variety of delivery models. We describe and compare access to and uptake of co-located and external services among clients accessing harm reduction-embedded (HR-embedded) and community health center-embedded (CHC-embedded) SCS models. METHODS: Cross-sectional baseline data were collected between November 2018 and March 2020 as part of a cohort of people who inject drugs in Toronto, Canada designed to evaluate one HR-embedded and two CHC-embedded SCS. This analysis was restricted to clients who reported accessing these SCS more than once in the previous 6 months. Participants were classified as HR-embedded or CHC-embedded SCS clients based on self-reported usage patterns. Client characteristics, as well as access to onsite services and referral and uptake of external services, were compared by SCS model. RESULTS: Among 469 SCS clients, 305 (65.0%) primarily used HR-embedded SCS and 164 (35.0%) primarily used CHC-embedded SCS. Compared to clients accessing CHC-embedded SCS, clients accessing HR-embedded SCS were somewhat younger (37.6 vs. 41.4, p < 0.001), more likely to report fentanyl as their primary injected drug (62.6% vs. 42.7%, p < 0.001), and visited SCS more often (49.5% vs. 25.6% ≥ daily, p < 0.001). HR-embedded SCS clients were more likely to access harm reduction services onsite compared to CHC-embedded SCS clients (94.8% vs. 89.6%, p = 0.04), while CHC-embedded SCS clients were more likely to access non-harm reduction services onsite (57.3% vs. 26.6%, p < 0.001). For external services, HR-embedded SCS clients were more likely to receive a referral (p = 0.03) but less likely to report referral uptake (p = 0.009). CONCLUSIONS: Clients accessing HR-embedded and CHC-embedded SCS were largely demographically similar but had different drug and SCS use patterns, with CHC-embedded SCS clients using the site less frequently. While clients of CHC-embedded SCS reported greater access to ancillary health services onsite, external service use remained moderate overall, underscoring the importance of co-location and support for clients with system navigation. Importantly, lack of capacity in services across the system may impact ability of staff to make referrals and/or the ability of clients to take up a referral.
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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) | 0.000 | 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 | 0.000 |
| 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".