IDEAS home Printed from https://ideas.repec.org/a/spr/patien/v10y2017i6d10.1007_s40271-017-0247-7.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40271-017-0247-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40271-017-0247-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aizaki, Hideo & Fogarty, James, 2019. "An R package and tutorial for case 2 best–worst scaling," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    2. 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.
    3. Wiebke Mohr & Anika Rädke & Adel Afi & Franka Mühlichen & Moritz Platen & Bernhard Michalowsky & Wolfgang Hoffmann, 2022. "Development of a Quantitative Instrument to Elicit Patient Preferences for Person-Centered Dementia Care Stage 1: A Formative Qualitative Study to Identify Patient Relevant Criteria for Experimental D," IJERPH, MDPI, vol. 19(13), pages 1-27, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Álvarez, Begoña & Rodríguez-Míguez, Eva, 2011. "Patients' self-interested preferences: Empirical evidence from a priority setting experiment," Social Science & Medicine, Elsevier, vol. 72(8), pages 1317-1324, April.
    2. Charles Cunningham & Ken Deal & Yvonne Chen, 2010. "Adaptive Choice-Based Conjoint Analysis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 257-273, December.
    3. Ting Li & Robert J. Kauffman & Eric van Heck & Peter Vervest & Benedict G. C. Dellaert, 2014. "Consumer Informedness and Firm Information Strategy," Information Systems Research, INFORMS, vol. 25(2), pages 345-363, June.
    4. Pfarr, Christian & Schmid, Andreas, 2013. "The political economics of social health insurance: the tricky case of individuals’ preferences," MPRA Paper 44534, University Library of Munich, Germany.
    5. Wang, Yi & Rattanavipapong, Waranya & Teerawattananon, Yot, 2021. "Using health technology assessment to set priority, inform target product profiles, and design clinical study for health innovation," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    6. Andrea N. Natsky & Andrew Vakulin & Ching Li Chai-Coetzer & R. Doug McEvoy & Robert J. Adams & Billingsley Kaambwa, 2022. "Preferred Attributes of Care Pathways for Obstructive Sleep Apnoea from the Perspective of Diagnosed Patients and High-Risk Individuals: A Discrete Choice Experiment," Applied Health Economics and Health Policy, Springer, vol. 20(4), pages 597-607, July.
    7. Stephanie Knox & Rosalie Viney & Deborah Street & Marion Haas & Denzil Fiebig & Edith Weisberg & Deborah Bateson, 2012. "What’s Good and Bad About Contraceptive Products?," PharmacoEconomics, Springer, vol. 30(12), pages 1187-1202, December.
    8. Emelie Heintz & Marieke Krol & Lars-Åke Levin, 2013. "The Impact of Patients’ Subjective Life Expectancy on Time Tradeoff Valuations," Medical Decision Making, , vol. 33(2), pages 261-270, February.
    9. Anna Nicolet & Antoinette D I van Asselt & Karin M Vermeulen & Paul F M Krabbe, 2020. "Value judgment of new medical treatments: Societal and patient perspectives to inform priority setting in The Netherlands," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-18, July.
    10. Richard Norman & Jane Hall & Deborah Street & Rosalie Viney, 2013. "Efficiency And Equity: A Stated Preference Approach," Health Economics, John Wiley & Sons, Ltd., vol. 22(5), pages 568-581, May.
    11. Han Bleichrodt & Jose Maria Abellan-Perpiñan & Jose Luis Pinto-Prades & Ildefonso Mendez-Martinez, 2007. "Resolving Inconsistencies in Utility Measurement Under Risk: Tests of Generalizations of Expected Utility," Management Science, INFORMS, vol. 53(3), pages 469-482, March.
    12. Velasco Garrido, Marcial & Gerhardus, Ansgar & Røttingen, John-Arne & Busse, Reinhard, 2010. "Developing Health Technology Assessment to address health care system needs," Health Policy, Elsevier, vol. 94(3), pages 196-202, March.
    13. Han Bleichrodt & José-Luis Pinto-Prades, 2004. "The Validity of QALYs Under Non-Expected Utility," Working Papers 113, Barcelona School of Economics.
    14. Feucht, Yvonne & Zander, Katrin, 2017. "Consumers’ attitudes on carbon footprint labelling. Results of the SUSDIET project," Thünen Working Paper 266396, Johann Heinrich von Thünen-Institut (vTI), Federal Research Institute for Rural Areas, Forestry and Fisheries.
    15. Thébaut, Clémence, 2013. "Dealing with moral dilemma raised by adaptive preferences in health technology assessment: The example of growth hormones and bilateral cochlear implants," Social Science & Medicine, Elsevier, vol. 99(C), pages 102-109.
    16. Jiang, Shan & Gu, Yuanyuan & Yang, Fan & Wu, Tao & Wang, Hui & Cutler, Henry & Zhang, Lufa, 2020. "Tertiary hospitals or community clinics? An enquiry into the factors affecting patients' choice for healthcare facilities in urban China," China Economic Review, Elsevier, vol. 63(C).
    17. Richard Norman & Gisselle Gallego, 2008. "Equity weights for economic evaluation: An Australian Discrete Choice Experiment, CHERE Working Paper 2008/5," Working Papers 2008/5, CHERE, University of Technology, Sydney.
    18. Shehely Parvin & Paul Wang & Jashim Uddin, 2016. "Using best-worst scaling method to examine consumers’ value preferences: A multidimensional perspective," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1199110-119, December.
    19. Cyr, Pascale Renée & Jain, Vageesh & Chalkidou, Kalipso & Ottersen, Trygve & Gopinathan, Unni, 2021. "Evaluations of public health interventions produced by health technology assessment agencies: A mapping review and analysis by type and evidence content," Health Policy, Elsevier, vol. 125(8), pages 1054-1064.
    20. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:patien:v:10:y:2017:i:6:d:10.1007_s40271-017-0247-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.