Introducing patient perspective in health technology assessment at the local level
Bibliographic record
Abstract
BACKGROUND: Recognizing the importance of increased patient participation in healthcare decisions leads decision makers to consider effective ways to incorporate patient perspectives in Health Technology Assessment (HTA) processes. The implementation of local health HTA units in university hospitals in Quebec provides a unique opportunity to foster an increased participation of patients in decisions regarding health technologies and clinical interventions. This project explores strategies that could be effective in involving patients in HTA activities at the local level. To do so, three objectives are pursued: 1) To synthesise international knowledge and experiences on patient and public involvement in HTA activities; 2) To explore the perceptions of stakeholders (administrators, clinical managers, healthcare professionals, HTA producers, and patients) regarding strategies for involving patients in various HTA activities; and 3) To produce a consensual strategic framework that could guide interventions for involving patients in HTA activities at the local level. METHODS: A systematic review of the literature will be conducted to synthesise international knowledge and experiments regarding the implication of patients and public in HTA. Then, focus groups will be carried out with representatives of various stakeholder groups in order to explore their perceptions regarding patient participation in HTA. Based on findings from the systematic review and the focus groups, a framework to support patient participation in HTA activities will be proposed. It will then be validated during a deliberative meeting with the research team, composed of scientists and decision makers, and representatives from different groups involved in HTA in Quebec. This deliberative meeting will aim at identifying the type and the degree of participation as well as the adequate timing for involving patients in local HTA activities. DISCUSSION: Given the actual state of evidence, integrating patient perspective in HTA activities has the potential to improve the quality of healthcare services. This study provides an opportunity to bridge the gap between HTA producers and its ultimate end-user: the patient. It will provide guidance to support local HTA units in Quebec and elsewhere in their decisions regarding patient participation. The framework developed could be applied to design and implement strategies for involving patients in HTA activities.
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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 | 0.122 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".