Barriers and facilitators to safer supply pilot program implementation in Canada: a qualitative assessment of service provider perspectives
Bibliographic record
Abstract
BACKGROUND: In response to the ongoing drug toxicity crisis, driven by fentanyl and its analogues in the unregulated drug supply, Canada has funded several safer supply programs, which provide pharmaceutical-grade medications to reduce the reliance on toxic unregulated drug supply for people who use drugs. In this study, we examined barriers and facilitators that influenced the implementation of integrated safer supply pilot programs (ISSPP) across Canada. METHODS: Between March 2022 and May 2023, we conducted a qualitative study using semi-structured interviews with key informants from ten ISSPP located in three provinces across Canada. Data analysis and interpretation of findings were guided by the Consolidated Framework for Implementation Research (CFIR). Thematic analysis was used to code transcripts and identify themes. RESULTS: ISSPP varied greatly in the degree of ancillary and wraparound services provided. Additionally, differences existed across the ten programs in terms of eligibility criteria for enrolling clients and the availability of medication options. We found twelve constructs and three sub-constructs across four domains of CFIR that influenced the implementation of ISSPP. Implementation facilitators included low-barrier and client-centered delivery model, ongoing needs assessment through program monitoring and evaluation, integration of wraparound care, partnership with local services to coordinate client care, community buy-in, clinical protocols and standardized practices, and multidisciplinary care teams with motivated staff. Major barriers to ISSPP implementation were a volatile and toxic unregulated drug supply, complicated policy environments, unsustainable funding models, unsupportive regulatory environments, limited medication options, limited physical space, as well as staff shortage. CONCLUSIONS: Despite several internal implementation facilitators, ISSPP faced many external and policy-level implementation barriers. Future safer supply programs should be guided by evidence-based planning and implementation, drawing from successful experiences in harm reduction implementation. Implementation facilitators, in particular, evidence-based practice guidelines along with better monitoring of client outcomes can be leveraged to enhance quality of care, address client needs and preferences, and mitigate unintended 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".