Literature DB >> 23402450

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

Alexander M M Arons1, Paul F M Krabbe.   

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.

Mesh:

Year:  2013        PMID: 23402450     DOI: 10.1586/erp.12.85

Source DB:  PubMed          Journal:  Expert Rev Pharmacoecon Outcomes Res        ISSN: 1473-7167            Impact factor:   2.217


  9 in total

1.  The better than dead method: feasibility and interpretation of a valuation study.

Authors:  R A van Hoorn; A R T Donders; M Oppe; P F M Stalmeier
Journal:  Pharmacoeconomics       Date:  2014-08       Impact factor: 4.981

2.  Understanding drug preferences, different perspectives.

Authors:  Peter G M Mol; Arna H Arnardottir; Sabine M J Straus; Pieter A de Graeff; Flora M Haaijer-Ruskamp; Elise H Quik; Paul F M Krabbe; Petra Denig
Journal:  Br J Clin Pharmacol       Date:  2015-06       Impact factor: 4.335

3.  Eye tracking to explore attendance in health-state descriptions.

Authors:  Anna Selivanova; Paul F M Krabbe
Journal:  PLoS One       Date:  2018-01-05       Impact factor: 3.240

4.  Head-to-head comparison of health-state values derived by a probabilistic choice model and scores on a visual analogue scale.

Authors:  Paul F M Krabbe; Elly A Stolk; Nancy J Devlin; Feng Xie; Elise H Quik; A Simon Pickard
Journal:  Eur J Health Econ       Date:  2016-11-02

5.  Head-to-Head Comparison of EQ-5D-3L and EQ-5D-5L Health Values.

Authors:  Anna Selivanova; Erik Buskens; Paul F M Krabbe
Journal:  Pharmacoeconomics       Date:  2018-06       Impact factor: 4.981

6.  Quantification of health by scaling similarity judgments.

Authors:  Alexander M M Arons; Paul F M Krabbe
Journal:  PLoS One       Date:  2014-02-21       Impact factor: 3.240

7.  A generalized measurement model to quantify health: the multi-attribute preference response model.

Authors:  Paul F M Krabbe
Journal:  PLoS One       Date:  2013-11-21       Impact factor: 3.240

8.  Multinational evidence of the applicability and robustness of discrete choice modeling for deriving EQ-5D-5L health-state values.

Authors:  Paul F M Krabbe; Nancy J Devlin; Elly A Stolk; Koonal K Shah; Mark Oppe; Ben van Hout; Elise H Quik; A Simon Pickard; Feng Xie
Journal:  Med Care       Date:  2014-11       Impact factor: 2.983

9.  A two-step procedure to generate utilities for the Infant health-related Quality of life Instrument (IQI).

Authors:  Paul F M Krabbe; Ruslan Jabrayilov; Patrick Detzel; Livia Dainelli; Karin M Vermeulen; Antoinette D I van Asselt
Journal:  PLoS One       Date:  2020-04-03       Impact factor: 3.240

  9 in total

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