Critical appraisal of costeffectiveness and cost-utility studies in health care

  • Soares M
  • Dumville J
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Abstract

Increasingly, cost-effectiveness and cost-utility analyses (broadly referred to as cost-effectiveness analyses [CEAs]) are used to inform resource allocation decisions in health care. National bodies, such as the UK National Institute of Health and Clinical Excellence (NICE), prefer CEAs to cost–benefit and cost-minimisation studies. CEAs assess value for money by relating the costs and consequences (effects) of 2 or more health technologies. Ascertaining value for money is important since healthcare sectors have fixed budgets. This means that a decision made in favour of one technology is associated with an opportunity cost in the form of the health technologies now forgone. In our previous Notebook, 1 we gave an overview of what economic evaluation involves and why such research is important. Like all forms of research evidence, CEAs need to be critically appraised for validity, clinical importance, and applicability before they are given a ''weight'' in decision-making processes. The aim of this Notebook is to guide readers through the stages of evaluating published CEAs. Broadly speaking, these studies take 2 forms: a single source of data collected in the context of primary research (ie, a randomised controlled trial [RCT]) or synthesis of data from multiple sources in a decision-analytic model. Decision-analytic models represent a simplified version of ''real world'' decision making. As with other research designs, appraisal of CEAs is facilitated by applying a series of tailored questions to the research study . The seminal guide to critical appraisal of economic evaluations was developed by Drummond et al. 2 In this Notebook, we draw on the Drummond checklist as well as the UK requirements for economic evaluation. 3 We present a series of questions under 4 main headings: defining and presenting the decision problem, measurement and data, analysis, and discussion (table). Broadly, this guide can be applied to CEAs done as part of primary research and modelling studies. More detailed information on each can be found elsewhere. 4 5

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Authors

  • Marta Soares

  • Jo C. Dumville

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