An institutional ethnographic analysis of public and patient engagement activities at a national health technology assessment agency
Bibliographic record
Abstract
OBJECTIVE: The practice of public and patient engagement (PPE) in health technology assessment (HTA) has spread worldwide, yet gaps in knowledge remain. We carried out an institutional ethnography of the Canadian Agency for Drugs and Technologies in Health (CADTH) public and patient involvement in HTA. METHODS: The research took place over 15 months and included observational work in the institutional settings, text review, and interviews with individuals working for or involved with the agency. RESULTS: We found that despite demonstrated commitment to PPE, organizational history, governance structure, and practices were impediments to a unified approach to PPE. Unclear role descriptions for committee members and differences in philosophy and priority given to PPE across the organization presented challenges to effective participation. The high degree of value given to evidence-based principles at times conflicted with meaningful integration of patient input. A lack of clear goals and processes, roles, and differential treatment of evidence in PPE served to minimize the importance of patient experiences and to displace their validity. An acknowledgment of conflicts between multiple epistemic traditions at work within HTA activities may strengthen organizational approaches to PPE. CONCLUSION: HTA organizations can learn from this study by reflecting on the challenges described and the recommendations offered to address them. We suggest solidifying CADTH's commitment to PPE with clear agency-wide roles and direction, values, and outcomes, a comprehensive framework, and policy and procedures. An acknowledgment of diverse epistemic traditions, as well as leadership and expertise in PPE, will strengthen CADTH's PPE activities and sustain its leadership position in the HTA field.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".