Stakeholder engagement in health technology assessment: a scoping review protocol
Bibliographic record
Abstract
Introduction Stakeholder engagement in the multidisciplinary process of Health Technology Assessment (HTA) ensures consideration of different perspectives and relevant issues during the HTA process. Despite being considered good practice to engage stakeholders in HTA, there is a lack of standardised methods and limited guidance on how to incorporate stakeholder engagement in the HTA process. This scoping review aims to identify the current practices for stakeholder engagement in HTA internationally. Methods JBI methodology for scoping reviews will be followed and the final review will be reported in accordance with PRISMA-ScR checklist. This scoping review will include both peer review published literature as well as grey literature. This will include guidance documents and webpages describing stakeholder engagement processes in HTA, as well as qualitative, quantitative, and mixed method peer review publications describing and evaluating stakeholder engagement. The search strategy will be developed by a medical librarian using two concepts: “stakeholder engagement” and “health technology assessment”. Two researchers will independently screen, select, and chart data from the identified documents. The quantitative data will be described descriptively while the qualitative data will be analysed using a basic content analysis and reported narratively. Conclusion This scoping review will identify current practices for stakeholder engagement in the HTA process internationally. The review findings will be used to inform updates to the national guideline for stakeholder engagement for HTA in Ireland and can also be used to develop future guidance.
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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 | 0.208 | 0.201 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.131 | 0.040 |
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".