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Title
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Generating, presenting, and interpreting cost-effectiveness results in the context of uncertainty : a tutorial for deeper knowledge and better practice
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Author
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Abstract
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| This tutorial aims to help make the best available methods for generating and presenting cost-effectiveness results with uncertainty common practice. We believe there is a need for such type of tutorial because some erroneous practices persist (e.g., identifying the cost-effective intervention as the one with the highest probability to be cost-effective), while some of the more advanced methods are hardly used (e.g., the net loss statistic 'NL', expected net loss curves and frontier). The tutorial explains with simple examples the pros and cons of using ICER, incremental net benefit and NL to identify the cost-effective intervention, both with and without uncertainty accounted for probabilistically. A flowchart provides practical guidance on when and how to use ICER, incremental net benefit or NL. Different ways to express and present uncertainty in the results are described, including confidence and credible intervals, the probability that a strategy is cost-effective (as usually shown with cost-effectiveness acceptability curves (CEACs)) and the expected value of perfect information (EVPI). The tutorial clarifies and illustrates why EVPI is the only measure accounting fully for decision uncertainty, and why NL curves and the NL frontier may be preferred over CEACs and other plots for presenting cost-effectiveness results in the context of uncertainty. The easy calculations and a worked-out real-life example will help users to thoroughly understand and correctly interpret key cost-effectiveness results. Examples with mathematical calculations, interpretation, plots and R code are provided. |
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Language
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English
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Source (journal)
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Medical decision making. - Philadelphia, Pa, 1981, currens
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Publication
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Thousand oaks
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Sage publications inc
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2022
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ISSN
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0272-989X
[print]
1552-681X
[online]
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DOI
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10.1177/0272989X211045070
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Volume/pages
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42
:4
(2022)
, p. 421-435
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ISI
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000708613300001
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Pubmed ID
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34651515
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Full text (Publisher's DOI)
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Full text (open access)
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