title: Incorporation of uncertainty in health economic modelling studies.
abstract: In a recent leading article in PharmacoEconomics, Nuijten described some methods for incorporating uncertainty into health economic models and for utilising the information on uncertainty regarding the cost effectiveness of a therapy in resource allocation decision-making. His proposals are found to suffer from serious flaws in statistical and health economic reasoning.Nuijten's suggestions for incorporating uncertainty: (a) wrongly interpret the p-value as the probability that the null hypothesis is true; (b) represent this probability wrongly by truncating the input distribution; and (c) in the specific example of an antiparkinsonian drug uses a completely inappropriate p-value of 0.05 when the null hypothesis would, in reality, be emphatically disproved by the data.His suggestions regarding minimum important differences in cost effectiveness: (a) introduce areas of indifference that suggest inappropriate reliance on cost minimisation while failing to recognise that decisions should be based on expected costs versus benefits; and (b) offer no guidance on how the probabilities associated with these areas could be used in decision-making. Furthermore, Nuijten's model for Parkinson's disease is over-simplified to the point of providing a bad example of modelling practice, which may mislead the readers of PharmacoEconomics. The rationale for this paper is to ensure that readers do not apply inappropriate analyses as a result of following the proposals contained in Nuijten's paper. In addition to a detailed critique of Nuijten's proposals, we provide brief summaries of the currently accepted best practice in cost-effectiveness decision-making under uncertainty.
authors.affiliation: Centre for Bayesian Statistics in Health Economics, Department of Probability and Statistics, University of Sheffield, Sheffield, UK.
authors.forename: Anthony
authors.initials: A
authors.lastname: O'Hagan
authors.forename: Christopher
authors.initials: C
authors.lastname: McCabe
authors.forename: Ron
authors.initials: R
authors.lastname: Akehurst
authors.forename: Alan
authors.initials: A
authors.lastname: Brennan
authors.forename: Andrew
authors.initials: A
authors.lastname: Briggs
authors.forename: Karl
authors.initials: K
authors.lastname: Claxton
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Fenwick
authors.forename: Dennis
authors.initials: D
authors.lastname: Fryback
authors.forename: Mark
authors.initials: M
authors.lastname: Sculpher
authors.forename: David
authors.initials: D
authors.lastname: Spiegelhalter
authors.forename: Andrew
authors.initials: A
authors.lastname: Willan
mesh_terms: D000978:Antiparkinson Agents / Q000627:therapeutic use; D003362:Cost-Benefit Analysis / Q000379:methods / Q000592:standards; D003657:Decision Making; D017850:Economics, Pharmaceutical / Q000706:statistics & numerical data; D006801:Humans; D008390:Markov Chains; D018803:Models, Economic; D010300:Parkinson Disease / Q000188:drug therapy / Q000191:economics; D035501:Uncertainty
chemical_list: D000978:Antiparkinson Agents