Assessing the impact of the introduction of generic methadone to the Ontario public drug formulary
Bibliographic record
Abstract
BACKGROUND: Two new generic methadone products-Jamp-methadone and Odan-methadone-were added to Ontario's public drug formulary in August 2022 and listed as interchangeable with the brand-name product, Methadose®. Concerns have been raised by people receiving methadone and their prescribers about potential risks of treatment destabilization as a result of switching between methadone-containing products. METHODS: We conducted a retrospective population-based time series analysis of weekly methadone claims in Ontario, Canada between January 5, 2017, and March 31, 2023. Using interventional autoregressive integrated moving average models, we assessed the impact of the formulary listing on product market-share, maximum dose dispensed, methadone discontinuation, and opioid toxicities. RESULTS: The market share of Methadose® declined from 99.7 % to 52.3 % between the listing of generic methadone and March 2023, whereas generic products increased from 0.27 % to 40.0 % (Jamp-methadone) and 0.0 % to 7.7 % (Odan-methadone). We observed a significant short-term increase in the percentage of individuals dispensed methadone doses ≥130 mg (+1.30 %; 95 % CI: 0.85 %, 1.76 %) following formulary listing; however the introduction of generic methadone did not result in a significant change in methadone discontinuation among those stabilized (p > 0.5) and not yet stabilized on treatment (p > 0.7) or opioid-related toxicity events (p > 0.1). CONCLUSION: Our findings did not indicate broad treatment destabilization or increased opioid-related toxicity among methadone recipients in the months following the introduction of generic products. Early notification of formulary changes, phased implementation of the policy, as well as information resources developed for patients and clinicians may have played a role in mitigating potential disruptions for this population.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".