A rapid monitoring plan following a shift in coverage from brand name to biosimilar drugs for rheumatoid arthritis in British Columbia
Bibliographic record
Abstract
PURPOSE: To describe a rapid monitoring plan to assess the impacts of a shift in drug coverage for biosimilar drugs in British Columbia following the introduction of a new policy on 27 May 2019. The Biosimilars Initiative requires users of originator infliximab or etanercept to switch to biosimilar versions of those drugs to maintain coverage. We propose a signal-detection method to provide near-real-time information to policymakers on the impacts of the policy change. METHODS: The exposure will be the Biosimilars Initiative, a policy affecting patients using originator infliximab (Remicade) and etanercept (Enbrel) for approved rheumatologic or dermatologic indications. Two policy cohorts and six historical control cohorts of patients using originator infliximab or etanercept will be assembled using linked and de-identified data from the British Columbia Ministry of Health. Patients will be identified during the 6-month period before the policy anniversary. Outcomes will include medication refills and switching, hospital admissions, emergency department visits, and physician visits. Summary outcome measures, such as cumulative incidence or average quantity as applicable, will be examined daily and reported monthly for 1 year. Outcomes in the policy cohorts will be compared with historical controls using likelihood ratios. RESULTS: The results of this rapid monitoring plan will be based on analyses involving approximately 9000 patients: four infliximab cohorts of approximately 430 patients and four etanercept cohorts of approximately 1800 patients. CONCLUSIONS: Rapid monitoring results will inform ongoing policy decisions related to the Biosimilars Initiative, in terms of impacts on both patient health and health services utilization.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".