Patient and citizen participation at the organizational level in health technology assessment: an exploratory study in five jurisdictions
Bibliographic record
Abstract
OBJECTIVE: While patient participation in individual health technology assessments (HTAs) has been frequently described in the literature, patient and citizen participation at the organizational level is less described and may be less understood and practiced in HTA bodies. We aimed to better understand its use by describing current practice. METHOD: To elicit descriptive case studies and insights we conducted semi-structured interviews and open-ended questionnaires with HTA body staff and patients and citizens participating at the organizational level in Belgium, France, Quebec, Scotland, and Wales. RESULTS: We identified examples of organizational participation in managerial aspects: governance, defining patient involvement processes, evaluation processes and methods, and capacity building. Mechanisms included consultation, collaboration, and membership of standing (permanent) groups. These were sometimes combined. Participants were usually from umbrella patient organizations and patient associations, as well as individual patients and citizens. DISCUSSION: Although the concept, participation at the organizational level, is not well-established, we observed a trend toward growth in each jurisdiction. Some goals were shared for this participation, but HTA bodies focused more on instrumental goals, especially improving participation in HTAs, while patients and citizens were more likely to offer democratic and developmental goals beyond improving participation processes. CONCLUSION: Our findings provide rationales for organizational-level participation from the perspectives of HTA bodies and patients. The case studies provide insights into how to involve participants and who may be seen as legitimate participants. These findings may be useful to HTA bodies, the patient sector, and communities when devising an organizational-level participation framework.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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 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".