Performing cost-effectiveness analysis by integrating randomized trial data with a comprehensive decision model: application to treatment of acute ischemic stroke.
A recent national panel on cost-effectiveness in health and medicine has recommended that cost-effectiveness analysis (CEA) of randomized controlled trials (RCTs) should reflect the effect of treatments on long-term outcomes. Because the follow-up period of RCTs tends to be relatively short, long-term implications of treatments must be assessed using other sources. We used a comprehensive simulation model of the natural history of stroke to estimate long-term outcomes after a hypothetical RCT of an acute stroke treatment. The RCT generates estimates of short-term quality-adjusted survival and cost and also the pattern of disability at the conclusion of follow-up. The simulation model incorporates the effect of disability on long-term outcomes, thus supporting a comprehensive CEA. Treatments that produce relatively modest improvements in the pattern of outcomes after ischemic stroke are likely to be cost-effective. This conclusion was robust to modifying the assumptions underlying the analysis. More effective treatments in the acute phase immediately following stroke would generate significant public health benefits, even if these treatments have a high price and result in relatively small reductions in disability. Simulation-based modeling can provide the critical link between a treatment's short-term effects and its long-term implications and can thus support comprehensive CEA.
Duke Scholars
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- United States
- Treatment Outcome
- Survival Analysis
- Sensitivity and Specificity
- Risk Factors
- Randomized Controlled Trials as Topic
- Quality-Adjusted Life Years
- Outcome Assessment, Health Care
- Monte Carlo Method
- Models, Economic
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- United States
- Treatment Outcome
- Survival Analysis
- Sensitivity and Specificity
- Risk Factors
- Randomized Controlled Trials as Topic
- Quality-Adjusted Life Years
- Outcome Assessment, Health Care
- Monte Carlo Method
- Models, Economic