JSM 2004 - Toronto

Abstract #301279

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Activity Number: 263
Type: Topic Contributed
Date/Time: Tuesday, August 10, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #301279
Title: Use of Cost-effectiveness Elasticity to Address the Problem of Small Denominators in Cost-effectiveness Analysis
Author(s): Ya-Chen T. Shih*+ and Scott B. Cantor and Peter Muller
Companies: University of Texas M. D. Anderson Cancer Center and University of Texas M.D. Anderson Cancer Center and University of Texas M. D. Anderson Cancer Center
Address: Dept of Biostatistics & Applied Mathematics , Houston, TX, 77030,
Keywords: cost-effectiveness analysis ; Bayesian cost-effectiveness analysis ; cost-effectiveness elasticity ; incremental cost-effectiveness ratio ; small denominators
Abstract:

The conventional CEA summarizes results in an incremental cost-effectiveness ratio (ICER) and compares it with a specific threshold to determine whether a new intervention is cost-effective. The ICER measures the absolute difference in costs against the absolute difference in effectiveness; it does not differentiate small denominators caused by poor clinical benefit (bad intervention) from those due to treating conditions with a limited lifespan to show clinical improvement (bad disease). Therefore, decisions based on ICER may be biased against the latter type of interventions. We propose a relative CE measure called the CE-elasticity to address this issue. We used the Bayesian approach to analyze a simulated data with the same incremental effectiveness for diseases with very short, short, and moderate life expectancy; the estimated posterior mean CE-elasticity for these diseases was 0.47, 2.68, and 5.45, respectively. The probability that the new intervention had an elasticity larger than 2 is 0.63, 0.50, and 0.48, respectively. Results showed that the new CE measure differentiate bad interventions from bad diseases in CEA and thus may minimize biased decision-making.

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