Ethical and Social Values for Paediatric Health Technology Assessment and Drug Policy
Bibliographic record
Abstract
BACKGROUND: Public policy approaches to funding paediatric medicines in advanced health systems remain understudied. In particular, the ethical and social values dimensions of health technology assessment (HTA) and drug coverage decisions for children have received almost no attention in research or policy. METHODS: To elicit and understand the social values that influence decision-making for public funding of paediatric drugs, we undertook a series of in-depth, semi-structured interviews with a stratified purposive sample (n = 22) of stakeholders involved with or affected by drug funding decisions for children at the provincial (Ontario) and national levels in Canada. Constructivist grounded theory methodology guided data collection and thematic analysis. RESULTS: Our study provides empirical evidence about the unique ethical and social values dimensions of HTA for children, and describes a novel social values typology for paediatric drug policy decision-making. Three principal categories of values emerged from stakeholder reflections on HTA and drug policy-making for children: procedural values, structural values, and sociocultural values. Key findings include the importance of attention to the procedural legitimacy of HTA for children, with emphasis on the inclusion of child health voices in processes of technology appraisal and policy uptake; a role for HTA institutions to consider the equity impacts of technologies, both in setting review priorities and in assessing the value of technologies for public coverage; and the potential benefits of a distinct national framework to guide drug policy for children. CONCLUSION: Current approaches to HTA are not well designed for the realities of child health and illness, nor the societal priorities regarding children that our study identified. This research generates new knowledge to inform decision-making on paediatric drugs by HTA institutions and government payers in Canada and other publicly-funded health systems, through insights into the relevant social values for child drug funding decisions from varied stakeholder groups.
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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 | 0.083 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.122 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".