Redefining health technology assessment in Canada: Diversification of products and contextualization of findings
Bibliographic record
Abstract
OBJECTIVES: While strategies for enhancing the dissemination and impact of Health Technology Assessment (HTA) are now being increasingly examined, the characteristics of HTA production have received less attention. METHODS: This study presents the results of a content analysis of the HTA documents (n = 187) produced by six Canadian agencies from 1995 to 2001, supplemented by interviews with chief executive officers and researchers (n = 40). The goal of this analysis was to characterize the agencies' portfolios and to analyze the challenges these agencies face in responding to the increased demand for HTA. RESULTS: On average, thirty HTA products were issued annually by the agencies. While the bulk of documents produced were full HTA reports (76 percent), two agencies showed significant diversification in their products. Three agencies in particular actively supported the publication of results in scientific journals. Three agencies showed evidence of adapting to different institutional environments by specializing in certain areas (drugs, health services). Overall, a significant portion of the agencies' HTAs contained data on costs (37 percent) and effectiveness (48 percent), whereas ethical and social issues were rarely addressed (17 percent). Most agencies addressed issues and outcomes that did not strictly fall under the typical definition of HTA but that increased the "contextualization" of their findings. CONCLUSIONS: Our discussion highlights four paradoxes and reflects further on challenges raised by the coordination of HTA within large countries and among European states. This study concludes that HTA is being redefined in Canada as HTA agencies offer a more contextualized informational basis, an approach that may prove more compatible with the increased demand for HTA.
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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 | 0.108 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.029 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".