Patient and public involvement in health technology assessment: update of a systematic review of international experiences
Bibliographic record
Abstract
OBJECTIVE: To summarize current evidence on patient and public involvement (PPI) in health technology assessment (HTA) in order to synthesize the barriers and facilitators, and to propose a framework to assess its impact. METHODS: We conducted an update of a systematic review published in 2011 considering the recent scientific literature (qualitative, quantitative, and mixed-methods studies). We searched papers published between March 2009 (end of the initial search) and December 2019 in five databases using specific search strategies. We identified other publications through citation tracking and contacting authors of previous related studies. Reviewers independently selected relevant studies based on prespecified inclusion and exclusion criteria. We extracted information using a pre-established grid. RESULTS: We identified a total of 7872 publications from the main search strategy. Ultimately, thirty-one distinct new studies met the inclusion criteria, whereas seventeen studies were included in the previous systematic review. PPI is realized through two main strategies: (i) patients and public members participate directly in decision-making processes (participation) and (ii) patients or public perspectives are solicited to inform decisions (consultation or indirect participation). This review synthesizes the barriers and facilitators to PPI in HTA, and a framework to assess its impact is proposed. CONCLUSION: The number of studies on patients or public involvement in HTA has dramatically increased in recent years. Findings from this updated systematic review show that PPI is done mostly through consultation and that direct involvement is less frequent. Several barriers to PPI in HTA exist, notably the lack of information to patients and public about HTA and the lack of guidance and policies to support PPI in HTA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".