 Accounting for Methodological, Structural, and Parameter Uncertainty in Decision-Analytic ModelsJoke Bilcke, Philippe Beutels, Marc Brisson and Mark Jit Medical Decision Making, 2011, vol. 31, issue 4, 675-692 Abstract: Accounting for uncertainty is now a standard part of decision-analytic modeling and is recommended by many health technology agencies and published guidelines. However, the scope of such analyses is often limited, even though techniques have been developed for presenting the effects of methodological, structural, and parameter uncertainty on model results. To help bring these techniques into mainstream use, the authors present a step-by-step guide that offers an integrated approach to account for different kinds of uncertainty in the same model, along with a checklist for assessing the way in which uncertainty has been incorporated. The guide also addresses special situations such as when a source of uncertainty is difficult to parameterize, resources are limited for an ideal exploration of uncertainty, or evidence to inform the model is not available or not reliable. Methods for identifying the sources of uncertainty that influence results most are also described. Besides guiding analysts, the guide and checklist may be useful to decision makers who need to assess how well uncertainty has been accounted for in a decision-analytic model before using the results to make a decision. Keywords: model uncertainty; checklist; sensitivity analysis; identifying uncertainty; presenting uncertainty (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:31:y:2011:i:4:p:675-692 Access Statistics for this article More articles in Medical Decision Making |
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