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ESTIMATING HEALTH STATE UTILITY VALUES FROM DISCRETE CHOICE EXPERIMENTS—A QALY SPACE MODEL APPROACH
Author(s) -
Gu Yuanyuan,
Norman Richard,
Viney Rosalie
Publication year - 2014
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.3066
Subject(s) - state space , econometrics , quality adjusted life year , cost–utility analysis , discrete choice , medicine , space (punctuation) , statistics , economics , mathematics , computer science , cost effectiveness , operating system
Using discrete choice experiments (DCEs) to estimate health state utility values has become an important alternative to the conventional methods of Time Trade‐Off and Standard Gamble. Studies using DCEs have typically used the conditional logit to estimate the underlying utility function. The conditional logit is known for several limitations. In this paper, we propose two types of models based on the mixed logit: one using preference space and the other using quality‐adjusted life year (QALY) space, a concept adapted from the willingness‐to‐pay literature. These methods are applied to a dataset collected using the EQ‐5D. The results showcase the advantages of using QALY space and demonstrate that the preferred QALY space model provides lower estimates of the utility values than the conditional logit, with the divergence increasing with worsening health states. Copyright © 2014 John Wiley & Sons, Ltd.