Involving patients in HTA activities at local level: a study protocol based on the collaboration between researchers and knowledge users
Bibliographic record
Abstract
BACKGROUND: The literature recognizes a need for greater patient involvement in health technology assessment (HTA), but few studies have been reported, especially at the local level. Following the decentralisation of HTA in Quebec, Canada, the last few years have seen the creation of HTA units in many Quebec university hospital centres. These units represent a unique opportunity for increased patient involvement in HTA at the local level. Our project will engage patients in an assessment being carried out by a local HTA team to assess alternatives to isolation and restraint for hospitalized or institutionalized adults. Our objectives are to: 1) validate a reference framework for exploring the relevance and applicability of various models of patient involvement in HTA, 2) implement strategies that involve patients (including close relatives and representatives) at different stages of the HTA process, 3) evaluate intervention processes, and 4) explore the impact of these interventions on a) the applicability and acceptability of recommendations arising from the assessment, b) patient satisfaction, and c) the sustainability of this approach in HTA. METHODS: For Objective 1, we will conduct individual interviews with various stakeholders affected by the use of alternatives to isolation and restraint for hospitalized or institutionalized adults. For Objective 2, we will implement three specific strategies for patient involvement in HTA: a) direct participation in the HTA process, b) consultation of patients or their close relatives through data collection, and c) patient involvement in the dissemination of HTA results. For Objectives 3 and 4, we will evaluate the intervention processes and the impact of patient involvement strategies on the recommendations arising from the HTA and the understanding of the ethical and social implications of the HTA. DISCUSSION: This project is likely to influence future HTA practices because it directly targets knowledge users' need for strategies that increase patient involvement in HTA. By documenting the processes and outcomes of these involvement strategies, the project will contribute to the knowledge base related to patient involvement in HTA.
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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 | 0.237 | 0.149 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.033 | 0.015 |
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".