The Rationale and Design of Public Involvement in Health Technology Assessment: A Systems Thinking Approach
Bibliographic record
Abstract
Governments worldwide utilise an evaluation methodology named Health Technology Assessment (HTA) to decide which medical treatments they will fund. HTA evaluates the safety and (cost-) effectiveness, and broader implications of introducing new interventions into a given healthcare system. Involving the public in HTA is considered an appropriate way to collect information on the social and ethical implications of new medical interventions. This thesis examines why and how the public should be involved in HTA processes and healthcare funding policymaking. Its objective is to propose directions on how to improve public involvement in HTA based on an understanding of stakeholders’ perspectives. The thesis uses a theoretical framework based on two Systems Thinking approaches: Complex Adaptive Systems and Soft Systems Methodology. The thesis is composed of four studies. First, there is a survey of members of the public to examine public involvement in policy decisions. Then, there is a theoretical piece on how to define which types of public might take part in HTA. Finally, there is a Canadian case study comprising two studies. The first study features interviews with HTA stakeholders to understand their views about public involvement processes, and the second study features focus groups with members of the public to ascertain their views on being involved in HTA. The reasons for involving the public in policy are clarified; engagement processes are used to increase trust and transparency in decision making as part of governance strategies. A taxonomy for defining and differentiating the public from other types of stakeholders in HTA is proposed, along with the reasons and goals for engaging with each group. Examining HTA as a system shows that the HTA process and its outcomes are influenced by stakeholders’ worldviews and values both at a personal and group level. Members of the public report being suspicious of the interests driving HTA stakeholders and see public input as a counterbalance to those interests. Members of the public also suggest the use of a mixed-methods approach to public involvement to provide information to HTA processes and meet the public’s democratic aspirations to take part in government decisions. This research shows that the challenges related to increasing and improving public involvement in HTA do not pertain exclusively to methodological problems such as a lack of standards for the design and evaluation of such processes. The main challenge is the differences in worldviews of those involved in HTA and those not directly involved. However, if all stakeholders’ worldviews are explicitly considered, conflicts can be managed with provisional agreements that enable policy decisions to move forward. The inclusion of members of the public adds a set of values that may be different from the values of actors already involved in HTA and thus may warrant significant changes to current HTA processes. This body of work indicates that establishing formal procedures to foster discussion between stakeholders was seen a useful by those directly or indirectly involved in HTA as it allows them to understand a range of viewpoints and access potential solutions to challenges in this 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 | 0.117 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.009 | 0.062 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".