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Patient and Public Preferences for Treatment Attributes in Parkinson’s Disease

Author

Listed:
  • Marieke G. M. Weernink

    (University of Twente)

  • Janine A. Til

    (University of Twente)

  • Catharina G. M. Groothuis-Oudshoorn

    (University of Twente)

  • Maarten J. IJzerman

    (University of Twente)

Abstract

Background Patient and public preferences for therapeutic outcomes or medical technologies are often elicited, and discordance between the two is frequently reported. Objective Our main objective was to compare patient and public preferences for treatment attributes in Parkinson’s disease (PD). Methods A representative sample from Dutch PD patients and the general public were invited to complete a best–worst scaling case 2 experiment consisting of six health-related outcomes and one attribute describing the specific treatment (brain surgery, pump, oral medication). Data were analyzed using mixed logit models, and attribute impact was estimated and compared between populations (and population subgroups). Results Both the public (N = 276) and patient (N = 198) populations considered treatment modality the most important attribute, although patients assigned higher relative importance. Both groups assigned high disutility to pump infusion and brain surgery and preferred drug treatment. Most health outcomes were valued equally by patients and the public, with the exception of reducing dizziness (more important to the public) and improving slow movement (more important to patients). Discussion Although these data do not support definite conclusions on whether patients are less likely to undergo invasive treatments, the (predicted) choice probability of undergoing brain surgery or having pump infusion technology would be low based on the (un)desirability of the attribute levels. Patients with PD might have adapted to their condition and are not willing to undergo advanced treatments in order to receive health improvements. Both public and patient preferences entail information that is potentially relevant for decision makers, and patient preferences can inform decision makers about the likelihood of adaptation to a specific condition.

Suggested Citation

  • Marieke G. M. Weernink & Janine A. Til & Catharina G. M. Groothuis-Oudshoorn & Maarten J. IJzerman, 2017. "Patient and Public Preferences for Treatment Attributes in Parkinson’s Disease," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 10(6), pages 763-772, December.
    • Handle: RePEc:spr:patien:v:10:y:2017:i:6:d:10.1007_s40271-017-0247-7
    DOI: 10.1007/s40271-017-0247-7
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    References listed on IDEAS

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    1. Banta, David, 2003. "The development of health technology assessment," Health Policy, Elsevier, vol. 63(2), pages 121-132, February.
    2. Lancsar, Emily & Louviere, Jordan & Flynn, Terry, 2007. "Several methods to investigate relative attribute impact in stated preference experiments," Social Science & Medicine, Elsevier, vol. 64(8), pages 1738-1753, April.
    3. G. Ardine De Wit & Jan J.V. Busschbach & Frank Th. De Charro, 2000. "Sensitivity and perspective in the valuation of health status: whose values count?," Health Economics, John Wiley & Sons, Ltd., vol. 9(2), pages 109-126, March.
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    3. Wiebke Mohr & Anika Rädke & Adel Afi & Franka Mühlichen & Moritz Platen & Annelie Scharf & Bernhard Michalowsky & Wolfgang Hoffmann, 2022. "Development of a Quantitative Preference Instrument for Person-Centered Dementia Care—Stage 2: Insights from a Formative Qualitative Study to Design and Pretest a Dementia-Friendly Analytic Hierarchy ," IJERPH, MDPI, vol. 19(14), pages 1-21, July.

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