High-Cost Drug Policies in Canadian Children’s Hospitals: An Exploratory Study
Bibliographic record
Abstract
OBJECTIVE: Over the past decade a number of effective but costly drugs have entered the therapeutic arena. Ethical and logistical challenges associated with including children in research and policy have produced variability in public policy on funding pediatric drugs, with inconsistent coverage across Canada. The purpose of this study was to explore the processes for funding high-cost pediatric drugs in Canadian children's hospitals. METHODS: We conducted a cross-sectional, text-based survey of all 19 chairs of Canadian departments of pediatrics about the funding and accessibility of high-cost drugs. Thematic qualitative analysis was performed to organize, sort, and code verbatim written responses and follow-up correspondence. RESULTS: Responses were received from all 19 Canadian departments of pediatrics surveyed (100% response rate). Three major themes emerged about pediatric high-cost drug policies: inconsistency between funding processes, variability in funding sources, and frustration with the current system. In aggregate, a clear concern emerged that current funding options were heterogenous and inadequate to meet patient needs. CONCLUSIONS: There was widespread consensus from respondents that current options for funding pediatric high-cost drugs were inadequate and that there was need for urgent action to address this problem. Policy changes are needed to sustain and improve access to high-cost drugs for Canadian children. We propose 3 solutions, including the creation of a national framework for funding high-cost pediatric drugs, increased incorporation of pediatric considerations in drug research and development, and a multidisciplinary drug summit on pediatric therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".