Reframing conceptualizations of opioid use disorder treatment in primary care
Bibliographic record
Abstract
<h3>CONTEXT:</h3> Opioid use disorder (OUD) and drug-related harms are health priorities requiring urgent policy responses. In countries like Canada and Australia, which have been experiencing high rates of opioid-related harms, there have been many calls to increase involvement of and improve OUD care in primary care. <h3>OBJECTIVE:</h3> To understand the factors that influence how OUD treatment is delivered through primary care in Canada and Australia and to identify current barriers and opportunities to improve OUD care in primary care. <h3>STUDY DESIGN & ANALYSIS:</h3> In our qualitative policy analysis, we used Starfield’s 4Cs conceptualization of primary care functions (first contact, comprehensiveness, continuity, coordination) to examine how and why current primary care systems may be suited towards, or pose challenges to providing OUD care, and to identify health system opportunities to address these challenges. <h3>SETTING/DATASET:</h3> We conducted 14 semi-structured interviews with 16 key informants with insights into opioid use policy in Canada and Australia. These included people with lived/living experience of drug use, clinicians, researchers, government health department staff, and individuals from non-government organizations focusing on drug use. <h3>RESULTS:</h3> Primary care was identified to be an ideal setting for OUD care due to its potential as the first point of contact in the health system; the opportunity to offer other health and social services to people with OUD; and the ability to coordinate with other care providers (e.g. specialists, social workers), thus providing care continuity. However, challenges include the prevailing model of OUD treatment, where addictions care is not viewed as part of comprehensive primary care, and the lack of resources and support for broader chronic disease management in primary care. Additionally, the highly regulated OUD policy landscape has manifested as a ‘regulatory cascade’ in which restrictive oversight of OUD treatment passes from regulators to health providers to people receiving treatment, normalizing the overly restrictive nature and inaccessibility of OUD care. <h3>CONCLUSIONS:</h3> The regulatory and sociocultural context of opioid use has led to treatment models involving primary care with priorities that conflict with the priorities and wellbeing of many people with OUD. This work presents an opportunity to re-think primary care delivery (including and beyond OUD care) from the perspective of people living at the margins.
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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) | 0.000 | 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".