Exploring Uncertainty in Cost-Effectiveness Analysis
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This paper describes the key principles of why an assessment of uncertainty and its consequences are critical for the types of decisions that a body such as the UK National Institute for Health and Clinical Excellence (NICE) has to make. In doing so, it poses the question of whether formal methods may be useful to NICE and its advisory committees in making such assessments. Broadly, these include the following: (i) should probabilistic sensitivity analysis continue to be recommended as a means to characterize parameter uncertainty; (ii) which methods should be used to represent other sources of uncertainty; (iii) when can computationally expensive models be justified and is computation expense a sufficient justification for failing to express uncertainty; (iv) which summary measures of uncertainty should be used to present the results to decision makers; and (v) should formal methods be recommended to inform the assessment of the need for evidence and the consequences of an uncertain decision for the UK NHS?
KeywordsProbabilistic Sensitivity Analysis Decision Uncertainty Positive Guidance Uncertain Decision Expensive Model
This paper was initially prepared as a briefing paper for NICE as part of the process of updating the Institute’s 2004 Guide to the Methods of Technology Appraisal. The work was funded by NICE through its Decision Support Unit (DSU), which is based at the universities of Sheffield, Leicester, York, Leeds and at the London School of Hygiene and Tropical Medicine.
The author has no conflicts of interest that are directly related to the contents of this article.
The author thanks members of the DSU who commented on the briefing document that forms the basis of this paper as well as Iain Chalmers, Alex Sutton, Alan Brennan, Louise Longworth and Carole Longson, who provided helpful comments on earlier drafts of this paper. All errors and omissions are the responsibility of the author.
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