title: Probabilistic choice models in health-state valuation research: background, theories, assumptions and applications.
abstract: Interest is rising in measuring subjective health outcomes, such as treatment outcomes that are not directly quantifiable (functional disability, symptoms, complaints, side effects and health-related quality of life). Health economists in particular have applied probabilistic choice models in the area of health evaluation. They increasingly use discrete choice models based on random utility theory to derive values for healthcare goods or services. Recent attempts have been made to use discrete choice models as an alternative method to derive values for health states. In this article, various probabilistic choice models are described according to their underlying theory. A historical overview traces their development and applications in diverse fields. The discussion highlights some theoretical and technical aspects of the choice models and their similarity and dissimilarity. The objective of the article is to elucidate the position of each model and their applications for health-state valuation.
authors: Department for Health Evidence, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands. s.arons@ebh.umcn.nl
authors: Alexander M M
authors: AM
authors: Arons
authors: Paul F M
authors: PF
authors: Krabbe
mesh_terms: D002755:Choice Behavior; D003365:Costs and Cost Analysis; D003627:Data Interpretation, Statistical; D004185:Disability Evaluation; D017048:Health Care Costs; D006302:Health Services Research / Q000191:economics / Q000706:statistics & numerical data*; D006304:Health Status; D006305:Health Status Indicators; D006801:Humans; D015233:Models, Statistical; D010043:Outcome and Process Assessment, Health Care / Q000191:economics / Q000706:statistics & numerical data*; D057240:Patient Preference; D011336:Probability; D011788:Quality of Life; D020127:Recovery of Function; D016896:Treatment Outcome