Patient Involvement in Health Technology Assessments: Lessons for EU Joint Clinical Assessments
Bibliographic record
Abstract
Patient involvement in health technology assessment (HTA) processes is increasingly recognized as pivotal for informed, equitable, and patient-relevant health care decision-making. With the implementation of Joint Scientific Consultations (JSCs) and Joint Clinical Assessments (JCAs) under Regulation (EU) 2021/2282, the European Union has a unique opportunity to design harmonized mechanisms that reflect best practices from established HTA systems. This article, drawing on the Acute Leukemia Advocates Network (ALAN)'s comparative analysis of HTA practices across seven countries (Canada, England, Scotland, France, Germany, Spain, and Italy), examines how current patient involvement processes can inform the JCA framework. It identifies opportunities to replicate effective practices and proposes strategies to embed patient voices meaningfully into the JCA process. By prioritizing robust and inclusive patient involvement, the EU can establish a global benchmark for impactful and consistent HTA processes. By leveraging lessons from international HTA systems and prioritizing clear frameworks, early involvement, and capacity building, the EU can set a global standard for meaningful patient participation in HTA processes. ALAN is an independent global network of patient organizations dedicated to improving outcomes for patients with acute leukemia.
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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 | 0.083 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads 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".