Examining inequities in access to opioid agonist treatment (OAT) take-home doses (THD): A Canadian OAT guideline synthesis and systematic review
Bibliographic record
Abstract
BACKGROUND: Daily supervised Opioid Agonist Treatment (OAT) medication has been identified as a barrier to treatment retention. Canadian OAT guidelines outline take-home dose (THD) criteria, yet, OAT prescribers use their clinical judgement to decide whether an individual is 'clinically stable' to receive THD. There is limited information regarding whether these decisions may result in inequitable access to THD, including in the context of updated COVID-19 guidance. The current Canadian OAT THD guideline synthesis and systematic review aimed to address this knowledge gap. METHODS: This systematic review included a two-pronged approach. First, we searched available academic literature in Embase, Medline, and PsychINFO up until October 12th, 2022, to identify studies that compared characteristics of individuals on OAT who had and had not been granted access to THD to explore potential inequities in access. Next, we identified all Canadian national and provincial OAT guidelines through a semi-structured grey literature search (conducted between September-October 2022) and extracted all THD 'stability' and allowances/timeline criteria to compare against characteristics identified in the literature search. Data from both review arms were synthesized and narratively presented. RESULTS: A total of n = 56 guidelines and n = 7 academic studies were included. The systematic review identified a number of patient characteristics such as age, sex, race/ethnicity, marital status, housing, employment, neighborhood income, drug use, mental health, health service utilization, as well as treatment duration that were associated with differential access to THD. The Canadian OAT THD guideline synthesis identified many of these same characteristics as 'stability' criteria, underscoring the potential for Canadian OAT guidelines to result in inequitable access to THD. CONCLUSIONS: This two-pronged literature review demonstrated that current guidelines likely contribute to inequitable OAT THD access due primarily to inconsistent 'stability' criteria across guidelines. More research is needed to understand differential OAT THD access with a focus on prescriber decision-making and evaluating associated treatment and safety outcomes. The development of a client-centered, equity-focused, and evidence-informed decision making framework that incorporates more clear definitions of 'stability' criteria and indications for prescriber discretion is warranted.
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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 | 0.036 | 0.147 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.025 | 0.032 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".