Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods

Objectives In recent years, discrete choice experiments (DCEs) have become frequently used to generate utility values, but there are a diverse range of approaches to do this. The primary focus of this systematic review is to summarise the methods used for the design and analysis of DCEs when estimating utility values in both generic and condition-specific preference-based measures. Methods Published literature using DCEs to estimate utility values from preference-based instruments were identified from MEDLINE, Embase, Cochrane Library and CINAHL using PRISMA guidelines. To assess the different DCE methods, standardised information was extracted from the articles including the DCE design method, the number of choice sets, the number of DCE pairs per person, randomisation of questions, analysis method, logical consistency tests and techniques for anchoring utilities. The CREATE checklist was used to assess the quality of the studies. Results A total of 38 studies with samples from the general population, students and patients were included. Values for health states described using generic multi attribute instruments (MAUIs) (especially the EQ-5D) were the most commonly explored using DCEs. The studies showed considerable methodology and design diversity (number of alternatives, attributes, sample size, choice task presentation and analysis). Despite these differences, the quality of articles reporting the methods used for the DCE was generally high. Conclusion DCEs are an important approach to measure utility values for both generic and condition-specific instruments. However, a gold standard method cannot yet be recommended.