Statements like "quality of care is more highly valued than waiting time" can neither be supported nor refuted by comparisons of utility parameters from a traditional discrete choice experiment (DCE). Best-worst scaling can overcome this problem because it asks respondents to perform a different choice task. However, whilst the nature of the best-worst task is generally understood, there are a number of issues relating to the design and analysis of a best-worst choice experiment that require further exposition. This paper illustrates how to aggregate and analyse such data and using a quality of life pilot study demonstrates how richer insights can be drawn by the use of best-worst tasks.
|Translated title of the contribution||Best-Worst Scaling: What it can do for health care research and how to do it|
|Pages (from-to)||171 - 189|
|Number of pages||19|
|Journal||Journal of Health Economics|
|Publication status||Published - Jan 2007|