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Modeling Age Differences in Cost-Effectiveness Analysis: A Review of the Literature

Louise B. Russell, Ph.D., Rutgers University, and Jane E. Sisk, Ph.D., Mount Sinai School of Medicine

International Journal of Technology Assessment in Health Care
Autumn, 2000
Objectives: Cost-effectiveness analysts often present cost-effectiveness results by age to help inform decisions about the use of an intervention. Yet it is not known how well studies model the risks and costs associated with age. We reviewed published studies to examine their modeling of age differences.

Methods: Medline searches identified all cost-effectiveness analyses published between 1985 and 1997 that included adults 50 and older, were based on data for developed countries, and compared cost-effectiveness ratios for adults of different ages or for initiation of an intervention at different ages; 36 articles met these criteria. They were reviewed to determine the extent to which they incorporated age-specific data. Studies that justified using the same data for all ages were counted as having varied the data element by age.

Results: All studies varied life expectancy by age. Most also varied the incidence/prevalence of the target condition and the case fatality rate. Only 36% varied the effectiveness rate of the intervention by age. Costs were usually assumed constant: 42% of studies varied the cost of treating adverse effects and 17% varied the cost of treating the target condition. Whether a data element was varied or not did not appear to be related to the pattern of cost-effectiveness ratios by age.

Conclusions: Many studies have not modeled age differences in sufficient detail to ensure that differences in cost-effectiveness ratios by age are accurate and a sound basis for decisions. As cost-effectiveness analysis becomes more widespread, analysts should strive to incorporate more complete age-specific data.

Louise B. Russell and Jane E. Sisk. "Modeling age differences in cost-effectiveness analysis: A review of the literature." International Journal of Technology Assessment in Health Care. 16(4):1158-67, 2000 Autumn.



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