Performing cost-effectiveness analysis by integrating randomized trial data with a comprehensive decision model: Application to treatment of acute ischemic stroke

Gregory P. Samsa, Richard A. Reutter, Giovanni Parmigiani, Marek Ancukiewicz, Paul Abrahamse, Joseph Lipscomb, David B. Matchar

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)259-271
Number of pages13
JournalJournal of Clinical Epidemiology
Volume52
Issue number3
DOIs
StatePublished - Mar 1999
Externally publishedYes

Keywords

  • Cost-effectiveness analysis
  • Simulation modeling
  • Stroke treatment

ASJC Scopus subject areas

  • Medicine(all)
  • Public Health, Environmental and Occupational Health
  • Epidemiology

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