Role of patient and public participation in health technology assessment and coverage decisions
Bibliographic record
Abstract
Health technology assessment (HTA) has become an integral part of decision-making on the coverage of new health technologies in most health systems in the developed world. In recent years, pressure to involve patients and members of the public in HTA has grown. In this article, we summarize findings from peer-reviewed and 'gray' literature, and discussions with key informants to determine potential roles for patients and the public in HTA and coverage decision-making. We also summarize existing roles for both groups in jurisdictions. Although there appears to be a general view that involvement of patients and the public is highly desirable, research offering insights into the effectiveness of different approaches to accomplish this is scarce. Nonetheless, many of the HTA agencies in developed countries have established some mechanism for seeking input from patients or the public in their processes.
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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 | 0.026 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".