A re‐examination of the impact of reference pricing on anti‐hypertensive drug plan expenditures in British Columbia
Bibliographic record
Abstract
Reference pricing (RP) limits drug plan reimbursement of interchangeable medicines to a reference price, which is typically equal to the price of the lowest-cost interchangeable drug; any cost above that is borne by the patient. Much of the evidence of the effects of RP comes from 'before and after' studies of the RP scheme adopted by Pharmacare, the publicly funded drug plan for seniors and others in British Columbia, Canada. We critically assess the identifying assumption inherent in the before and after design - namely, that pre-RP trends accurately predict counterfactual outcomes - in the context of estimating the impact of RP on Pharmacare's expenditure on anti-hypertensive drugs for its senior beneficiaries. We use similar data from a public plan that has not introduced RP to estimate the effects on drug expenditures of patent expiration, secular changes in prescribing patterns and various other factors common to all Canadian public drug plans that could potentially confound the before and after estimates of the effect of RP on drug plan expenditures. We find that controlling for such factors reduces estimates of drug plan savings attributable to RP of the Calcium Channel Blockers by about half.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".