Health Technology Assessment Process for Oncology Drugs: Impact of CADTH Changes on Public Payer Reimbursement Recommendations
Bibliographic record
Abstract
Public reimbursement systems face the challenge of balancing provision of needed treatments and the reality of limited resources. Canada has a complex system for drug approval and public reimbursement, with jurisdiction divided between the federal government and the provinces/territories. A pivotal role is that of health technology assessment (HTA), which relies primarily on health economic principles to analyze the value of drugs on a population health basis and make recommendations about public reimbursement. The Canadian Agency for Drugs and Technologies in Health (CADTH) provides recommendations to all provinces but Quebec. This article provides an overview of Canada's approval and public reimbursement pathway, including the role of HTA and the economic principles on which it relies. Starting in late 2020, CADTH reduced the cost per quality-adjusted life year (QALY) threshold, the metric relied upon in making recommendations to public payers. An analysis of all 56 oncology drug final recommendations issued from January 2020 to January 2022 was conducted and confirms this reduction in the cost per QALY threshold. As a result of this threshold reduction, recommendations to the provinces include, in a number of cases, substantially greater price reductions. The potential implications for successful price negotiation with the pan-Canadian Pharmaceutical Alliance (pCPA), the public negotiating body for the provinces, are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".