Timeliness of Health Technology Assessments and Price Negotiations for Oncology Drugs in Canada
Bibliographic record
Abstract
Purpose: To evaluate whether time targets for Canadian Agency for Drugs and Technologies in Health (CADTH) reimbursement reviews and pan-Canadian Pharmaceutical Alliance (pCPA) price negotiations are being achieved for oncology drugs. Materials and Methods: Recommendations, dates of submission and publication, and indications for oncology medicines issued between January 2014 and December 2023 were recorded from CADTH’s reimbursement reports webpage. The date any negotiation began and the date it was completed (successfully or not), or when a decision was made not to pursue negotiation was extracted from the pCPA’s webpage. The duration of each CADTH review and pCPA negotiation was calculated, together with time between CADTH’s recommendation and start of the pCPA negotiation or a decision not to negotiate. Percentages of reviews completed within CADTH’s target and of times taken by the pCPA to decide whether to negotiate and by its price negotiations completed within the relevant targets were calculated. Results: CADTH achieved its 270-days target in 88.2% to 100% of reviews issued between 2015 and 2019 but only in 65.9% to 73.1% of reviews issued in the last three years of the decade. CADTH’s “typical timeline” of 180 days was achieved in under 40% of reviews issued in 2015 and not attained in any review in 2021, 2022 or 2023. The pCPA’s target of 60 days for deciding whether to negotiate was achieved for all recommendations issued in 2014 but dropped below 40% for the last seven years of the decade; its target of 130 days for negotiations was achieved for over 85% of the recommendations in 2014 but decreased to only 14.3% in 2016 and then gradually increased to 61.5% in 2023. Conclusion: CADTH’s “typical timeline” and the pCPA’s targets were not met sufficiently to be meaningful. Their processes take too long for cancer drugs. Plain Language Summary: Canadian patients and providers are often frustrated and concerned about the timeliness of the country’s health technology assessment (HTA) and price negotiation processes, especially for cancer drugs. HTAs are carried out to evaluate the benefit of a medicine in comparison with its cost to see whether the drug is of sufficient value to add it to the benefit lists of government drug plans. HTAs are performed by the Canadian Agency for Drugs and Technologies in Health (CADTH) for all of Canada, except the province of Quebec, and price negotiations with drug developers are carried out by the pan-Canadian Pharmaceutical Alliance (pCPA) on behalf of all government drug plans. We used data from the websites of CADTH and the pCPA on HTA reviews of cancer drugs issued between January 2014 and December 2023 and price negotiations for these drugs to assess whether CADTH and the pCPA complied with their stated target times for completing their processes. We found that CADTH’s reviews and the pCPA’s price negotiations failed to meet their targets for cancer drugs in the past 10 years and that the timeliness of their performance has, in most cases, deteriorated. HTA and price negotiation processes for cancer drugs take too long in Canada. Keywords: oncology drugs, health technology assessment, drug prices, Canada
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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 | 0.045 | 0.264 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".