Evolution of health technology assessment: best practices of the pan-Canadian Oncology Drug Review
Bibliographic record
Abstract
BACKGROUND: In 2007, Canada chose to develop a separate and distinct path for oncology drug health technology assessment (HTA). In 2013, the decision was made to transfer the pan-Canadian Oncology Drug Review (pCODR) to the Canadian Agency for Drugs and Technologies in Health (CADTH), to align the pCODR and CADTH Common Drug Review processes while building on the best practices of both. The objective of this research was to conduct an examination of the best practices established by the pCODR. METHODS: A qualitative research approach was taken to assess the policies, processes, and practices of the pCODR, based on internationally accepted best practice "principles" in HTA, with a particular focus on stakeholder engagement. Publicly available information regarding the approach of the pCODR was used to gauge the agency's performance against these principles. In addition, stakeholder observations and real-world experiences were gathered through key informant interviews to be inclusive of perspectives from patient advocacy groups, provincial and/or cancer agency decision-makers, community and academic oncologists, industry, expert committee members, and health economists. RESULTS: This analysis indicated that, through the pCODR, oncology stakeholders have had a voice in and have come to trust the quality and relevance of oncology HTA as a vital tool to ensure the best decisions for Canadians with cancer and their health care system. It could be expected that adoption of the principles and processes of the pCODR would bring a similar level of engagement and trust to other HTA organizations in Canada and elsewhere. CONCLUSION: The results of this research led to recommendations for improvement and potential extrapolation of these best practices to other HTA organizations worldwide, along with suggestions for continued evolution of the pCODR in conjunction with its integration into the CADTH. It is clear that the transition of the pCODR to CADTH provides an opportunity for practices initiated by the pCODR to become the standard for these newly amalgamated HTA agencies in 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 | 0.361 | 0.415 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.023 | 0.027 |
| Science and technology studies | 0.017 | 0.034 |
| Scholarly communication | 0.041 | 0.013 |
| Open science | 0.010 | 0.016 |
| Research integrity | 0.007 | 0.016 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".