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Patients’ preferences: a discrete-choice experiment for treatment of non-small-cell lung cancer

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  • Axel Mühlbacher
  • Susanne Bethge

Abstract

Preference measurement showed “progression-free survival” and “tumor-associated symptoms” had a significant influence on the treatment decision. Subgroup analysis revealed that the importance of “progression-free survival” increases with increased therapy experience. Based on the presented results therapies can be designed, assessed and chosen on the basis of patient-oriented findings. As such, more effective and efficient care of patients can be achieved and benefits increased. Copyright The Author(s) 2015

Suggested Citation

  • Axel Mühlbacher & Susanne Bethge, 2015. "Patients’ preferences: a discrete-choice experiment for treatment of non-small-cell lung cancer," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(6), pages 657-670, July.
    • Handle: RePEc:spr:eujhec:v:16:y:2015:i:6:p:657-670
    DOI: 10.1007/s10198-014-0622-4
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    References listed on IDEAS

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    1. Emily Lancsar & Jordan Louviere, 2008. "Conducting Discrete Choice Experiments to Inform Healthcare Decision Making," PharmacoEconomics, Springer, vol. 26(8), pages 661-677, August.
    2. Esther W. de Bekker‐Grob & Mandy Ryan & Karen Gerard, 2012. "Discrete choice experiments in health economics: a review of the literature," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 145-172, February.
    3. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "GLLAMM Manual," U.C. Berkeley Division of Biostatistics Working Paper Series 1160, Berkeley Electronic Press.
    4. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    5. Mandy Ryan & Karen Gerard & Gillian Currie, 2012. "Using Discrete Choice Experiments in Health Economics," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 41, Edward Elgar Publishing.
    6. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
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    Cited by:

    1. Plaxcedes Chiwire & Charlotte Beaudart & Silvia M. Evers & Hassan Mahomed & Mickaël Hiligsmann, 2022. "Enhancing Public Participation in Public Health Offerings: Patient Preferences for Facilities in the Western Cape Province Using a Discrete Choice Experiment," IJERPH, MDPI, vol. 19(1), pages 1-26, January.
    2. Afschin Gandjour, 2018. "Patient preferences: a Trojan horse for evidence-based medicine?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(1), pages 167-172, January.
    3. Vikas Soekhai & Esther W. Bekker-Grob & Alan R. Ellis & Caroline M. Vass, 2019. "Discrete Choice Experiments in Health Economics: Past, Present and Future," PharmacoEconomics, Springer, vol. 37(2), pages 201-226, February.

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    More about this item

    Keywords

    Discrete-choice experiment; Non-small-cell lung cancer; Patient preferences; Patient-relevant treatment attributes; I10; I15; D700;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development

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