‘A Better Way to Measure Choices’ Discrete Choice Experiment and Conjoint Analysis Studies in Nephrology: A Literature Review

Michael D. Clark,1 Robert Higgins,2 Anil Gumber,3 Domenico Moro,4 Dennis Leech,1 Ala Szczepura,5 Sunil Daga,2 Nick West2

1. Department of Economics, University of Warwick, Coventry UK
2. Nephrology Department, University Hospital, Walsgrave, Coventry UK
3. Centre for Health and Social Care Research, Faculty of Health andWellbeing, SHeffield Hallam University, Sheffield, UK
4. Third Sector Research Centre, University of Birmingham, Birmingham, UK
5. Warwick Medical School, University of Warwick, Coventry UK

Disclosure: No potential conflict of interest.
Citation: EMJ Neph. 2013;1:52-59.


Discrete choice experiments (DCE) and conjoint analysis (CA) are increasingly used to address health policy issues. This is because the DCE and CA approaches have theoretical foundations in the characteristics theory of demand, which assumes goods, services, or healthcare provision, can be valued in terms of their characteristics (or attributes). As a result, such analysis is grounded in economic theory, lending theoretical validity to this approach.With DCEs, respondents are also assumed to act in a utility-maximising manner and make choices contingent upon the levels of attributes in DCE scenarios. Therefore, choice data can be analysed using econometric methods compatible with random utility theory (RUT) or random regret minimisation (RRM) theory. This means they have additional foundations in economic theory. In contrast, analyses described as CAs are sometimes compatible with RUT or RRM, but by definition they do not have to be. In this paper we review the CA/DCE evidence relating to nephrology. The CA/DCE approach is then compared with other approaches used to provide either quality of life information or preference information relating to nephrology. We conclude by providing an assessment of the value of undertaking CA or DCE analysis in nephrology, comparing the application of CA/DCEs in nephrology with other methodological approaches.

Download (PDF, 160KB)

Leave a Reply