title: The Impact of Different DCE-Based Approaches When Anchoring Utility Scores.
abstract: Discrete choice experiments (DCEs) have been proposed as a method to estimate utility weights for health states within utility instruments. However, the most appropriate method to anchor the utility values on the full health to dead quality-adjusted life year (QALY) scale remains uncertain. We test four approaches to anchoring in which dead is valued at zero and full health at one.
  
  
  
  We use data from two DCEs valuing EQ-5D-3L and EQ-5D-5L health states, which presented pairs of health profiles with an associated duration, and a dead option. The approaches to anchoring the results on the required scale were (1) using only preferences between non-dead health profiles; (2) including the dead data, treating it as a health profile with zero duration; (3) explicitly modelling both duration and dead; and (4) using the preferences regarding the dead health state as an external anchor subsequent to the estimation of approach 1.
  
  
  
  All approaches lead to differences in the scale of utility decrements, but not the ranking of EQ-5D health states. The models differ in their ability to predict preferences around dead health states, and the characteristics of the value sets in terms of their range and the proportion of states valued as worse than dead.
  
  
  
  Appropriate anchoring of DCEs with or without complementary time trade-off (TTO) data remains unresolved, and the method chosen will impact on health resource allocation decision making employing the value sets.
authors.affiliation: School of Public Health, Curtin University, Perth, Australia. Richard.Norman@curtin.edu.au.
authors.forename: Richard
authors.initials: R
authors.lastname: Norman
authors.affiliation: Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney, Sydney, Australia.
authors.forename: Brendan
authors.initials: B
authors.lastname: Mulhern
authors.affiliation: Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney, Sydney, Australia.
authors.forename: Rosalie
authors.initials: R
authors.lastname: Viney
mesh_terms: D002755:Choice Behavior; D003657:Decision Making; D006304:Health Status; D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D057240:Patient Preference; D019057:Quality-Adjusted Life Years; D040841:Resource Allocation