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Med Decis Making. 2011 Jul-Aug;31(4):675-92. doi: 10.1177/0272989X11409240. Epub 2011 Jun 8.

Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide.

Author information

Center for Health Economic Research and Modeling for Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (Vaxinfectio), Antwerp University, Antwerp, Belgium (JB, PB)
De´ partement de Me´ decine sociale et pre´ ventive, Universite´ Laval, Que´ bec, Canada (MB)
URESP, Centre de recherche FRSQ du CHA universitaire de Que´ bec, Que´ bec, Canada (MB)
Modelling and Economics Unit, Health Protection Agency, London, United Kingdom (MJ)


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.


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.

[Indexed for MEDLINE]

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