PP86 Impact Of Health Technology Assessment On Drug Price Negotiations: Canada
Bibliographic record
Abstract
Introduction: Subsequent to review by Canada's two central health technology assessment (HTA) agencies, confidential drug prices are negotiated by the pan-Canadian Pharmaceutical Alliance (pCPA) on behalf of public drug plans. This analysis is the first to examine characteristics of drugs considered for negotiation, and the duration of negotiations, from inception in 2011 to August 2017. The objectives were to identify how HTA recommendations impacted price negotiations, and in particular the role of health economics in the process. Methods: The dataset contained 208 drug indications from the pCPA archives: those with a decision to negotiate (n=155) or a decision not to negotiate (n=53). Data were abstracted from the publicly-maintained websites of the respective agencies; descriptive statistics were conducted. Results: There was close but imperfect alignment between the HTA agency listing recommendation and the pCPA's decision to negotiate. The incremental cost-effectiveness ratio (ICER) of negotiated drugs (as estimated by HTA agencies) approached CAD 200,000/QALY (i.e. USD 157,000) for oncology drugs, but was closer to CAD 100,000/QALY (i.e. USD 78,000) for non-oncology drugs, revealing that negotiations would require a substantial discount to achieve conventionally ‘acceptable’ value-for-money. ICERs were influential to non-oncology drug recommendations (and were increasingly used to set pCPA negotiation targets) but did not appear to influence oncology drug HTA recommendations. The time period required to initiate negotiations was dramatically shorter for oncology versus non-oncology drugs (53 versus 263 days), and also differed markedly between therapeutic areas. The time period for pCPA activities was surprisingly similar for drugs recommended without a price condition and for those conditional on a price reduction. Conclusions: These findings revealed an implicit prioritization pattern at the pCPA, as well as the evolving role of health economics in Canada's two-stage reimbursement process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.146 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".