Output correlations in probabilistic models with multiple alternatives

Klemen Naveršnik ()

The European Journal of Health Economics, 2015, vol. 16, issue 2, 133-139

Abstract: A comprehensive cost-effectiveness decision model will often go beyond a one-to-one comparison and will include a number of competing alternatives. Only a simultaneous assessment of all relevant treatment alternatives avoids comparing average cost-effectiveness ratios and allows a truly incremental analysis. Two issues arise if the analysis is probabilistic, namely, the occurrence of output correlations and difficulty in presenting the results. I have examined the role of output correlations using a screening model with eight alternatives and have shown that specifically cost–cost and quality-adjusted life years (QALY)–QALY correlations between alternatives have a major impact on decision uncertainty, as measured by the probability of the cost-effectiveness and expected value of perfect information. In particular, the latter strongly depends on between-alternative output correlations. This analysis shows that both the expected value of perfect information plots and acceptability curves/frontiers are sensitive to output correlations and thus appropriate for presentation of multiple alternatives. To avoid confusing statistical significance and economic importance I propose that acceptability curves be augmented by incremental net-benefit density plots at a given willingness to pay threshold. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Output correlations; Multiple alternatives; Uncertainty analysis; Probabilistic model; C5; I1 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10198-013-0558-0

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