Probabilistic choice models in health-state valuation research: background, theories, assumptions and applications

Alexander M M Arons, Paul F M Krabbe

    Research output: Contribution to journalReview articleAcademicpeer-review

    20 Citations (Scopus)


    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.

    Original languageEnglish
    Pages (from-to)93-108
    Number of pages16
    JournalExpert review of pharmacoeconomics & outcomes research
    Issue number1
    Publication statusPublished - Feb-2013


    • Choice Behavior
    • Costs and Cost Analysis
    • Data Interpretation, Statistical
    • Disability Evaluation
    • Health Care Costs
    • Health Services Research
    • Health Status
    • Health Status Indicators
    • Humans
    • Models, Statistical
    • Outcome and Process Assessment (Health Care)
    • Patient Preference
    • Probability
    • Quality of Life
    • Recovery of Function
    • Treatment Outcome

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