Methadone Access for Opioid Use Disorder During the COVID-19 Pandemic Within the United States and Canada
Bibliographic record
Abstract
Importance: Methadone access may be uniquely vulnerable to disruption during COVID-19, and even short delays in access are associated with decreased medication initiation and increased illicit opioid use and overdose death. Relative to Canada, US methadone provision is more restricted and limited to specialized opioid treatment programs. Objective: To compare timely access to methadone initiation in the US and Canada during COVID-19. Design, Setting, and Participants: This cross-sectional study was conducted from May to June 2020. Participating clinics provided methadone for opioid use disorder in 14 US states and territories and 3 Canadian provinces with the highest opioid overdose death rates. Statistical analysis was performed from July 2020 to January 2021. Exposures: Nation and type of health insurance (US Medicaid and US self-pay vs Canadian provincial). Main Outcomes and Measures: Proportion of clinics accepting new patients and days to first appointment. Results: Among 268 of 298 US clinics contacted as a patient with Medicaid (90%), 271 of 301 US clinics contacted as a self-pay patient (90%), and 237 of 288 Canadian clinics contacted as a patient with provincial insurance (82%), new patients were accepted for methadone at 231 clinics (86%) during US Medicaid contacts, 230 clinics (85%) during US self-pay contacts, and at 210 clinics (89%) during Canadian contacts. Among clinics not accepting new patients, at least 44% of 27 clinics reported that the COVID-19 pandemic was the reason. The mean wait for first appointment was greater among US Medicaid contacts (3.5 days [95% CI, 2.9-4.2 days]) and US self-pay contacts (4.1 days [95% CI, 3.4-4.8 days]) than Canadian contacts (1.9 days [95% CI, 1.7-2.1 days]) (P < .001). Open-access model (walk-in hours for new patients without an appointment) utilization was reported by 57 Medicaid (30%), 57 self-pay (30%), and 115 Canadian (59%) contacts offering an appointment. Conclusions and Relevance: In this cross-sectional study of 2 nations, more than 1 in 10 methadone clinics were not accepting new patients. Canadian clinics offered more timely methadone access than US opioid treatment programs. These results suggest that the methadone access shortage was exacerbated by COVID-19 and that changes to the US opioid treatment program model are needed to improve the timeliness of access. Increased open-access model adoption may increase timely access.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".