Abstract #300315

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JSM 2003 Abstract #300315
Activity Number: 72
Type: Invited
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Health Policy Statistics
Abstract - #300315
Title: New Developments for Statistical Inference in Cost-Effectiveness Analysis
Author(s): Joseph C. Gardiner*+
Companies: Michigan State University
Address: Department of Epidemiology, East Lansing, MI, 48823-5383,
Keywords: Markov model ; inverse weighting ; random effects ; censoring ; longitudinal data
Abstract:

Cost-effectiveness analysis (CEA) is a useful tool in the effort to prioritize expenditure on competing health care programs. Central to economic evaluation is the analysis of health care costs. These analyses face several challenges. Cost data can exhibit appreciable variation across subgroups. The distribution of costs is usually skewed in the right tail, or the presence of a large proportion of observations in the sample with zero values for cost gives its distribution a spike at zero. Since costs accrue through resource use over time, the amount of the resource and the time at which it is used will vary across individuals, and the total costs in some individuals might not be completely ascertained yielding right-censored costs. We develop regression models to analyze health care costs and outcomes jointly, addressing issues of heteroscedasticity, skewness, right-censoring in cost data, and incorporating explanatory variables (treatments, demographics) that might influence both costs and health outcomes. We describe estimation of measures widely used in CEA such as net present value, cost-effectiveness ratios, net-health benefit, and quality-adjusted survival years.

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