Introducing the patient's perspective in hospital health technology assessment (<scp>HTA</scp>): the views of <scp>HTA</scp> producers, hospital managers and patients
Bibliographic record
Abstract
BACKGROUND: The recent establishment of health technology assessment (HTA) units in University hospitals in the Province of Quebec (Canada) provides a unique opportunity to foster increased participation of patients in decisions regarding health technologies and interventions at the local level. However, little is known about factors that influence whether the patient's perspective is taken into consideration when such decisions are made. OBJECTIVE: To explore the practices, perceptions and views of the various HTA stakeholders concerning patient involvement in HTA at the local level. METHOD: Data were collected using semi-structured interviews with 24 HTA producers and hospital managers and two focus groups with a total of 13 patient representatives. RESULTS: Patient representatives generally showed considerable interest in being involved in HTA. Our findings support the hypothesis that the patient perspective contributes to a more accurate and contextualized assessment of health technologies and produces HTA reports that are more useful for decision makers. They also suggest that participation throughout the assessment process could empower patients and improve their knowledge. Barriers to patient involvement in HTA at the local level are also discussed as well as potential strategies to overcome them. DISCUSSION AND CONCLUSION: This study contributes to knowledge that could guide interventions in favour of patient participation in HTA activities at the local level. Experimenting with different patient involvement strategies and assessing their impact is needed to provide evidence that will inform future interventions of this kind.
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 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 | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".