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Using stated preference discrete choice modelling to inform health care decision-making: A pilot study of breast screening participation

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  • Karen Gerard
  • Marian Shanahan
  • Jordan Louviere

Abstract

This study was an important start to explore the feasibility of applying stated preference discrete choice modelling (SPDCM) for use in developing breast screening participation enhancement strategies. It needs to be followed by further research to establish model validity and authoritative results. In the meantime a random effects binary probit choice model was estimated using a main effects with selected 2-way interaction design and a convenience sample of Australian breast cancer screening participants. A response rate of 48% was obtained. Clear preferences for different service configurations were revealed and used to demonstrate how potential strategies to enhance future participation rates of women placed on routine recall could be identified. As anticipated accuracy of screening was the most important attribute of the service to influence the probability of uptake but others were screening time, travel time, information about screening benefits and the desire for privacy lending support to the view that benefit assessment goes beyond health factors. In summary, the SPDCM approach can be regarded as a judicious approach for helping decision-makers improve screening participation.

Suggested Citation

  • Karen Gerard & Marian Shanahan & Jordan Louviere, 2003. "Using stated preference discrete choice modelling to inform health care decision-making: A pilot study of breast screening participation," Applied Economics, Taylor & Francis Journals, vol. 35(9), pages 1073-1085.
  • Handle: RePEc:taf:applec:v:35:y:2003:i:9:p:1073-1085
    DOI: 10.1080/0003684032000081348
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    References listed on IDEAS

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    Cited by:

    1. Axel Mühlbacher & F. Reed Johnson, 2016. "Choice Experiments to Quantify Preferences for Health and Healthcare: State of the Practice," Applied Health Economics and Health Policy, Springer, vol. 14(3), pages 253-266, June.
    2. Darla Hatton MacDonald & Mark Morrison & Mary Barnes, 2010. "Willingness to Pay and Willingness to Accept Compensation for Changes in Urban Water Customer Service Standards," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(12), pages 3145-3158, September.
    3. Zhang, Yue & Berman, Oded & Verter, Vedat, 2009. "Incorporating congestion in preventive healthcare facility network design," European Journal of Operational Research, Elsevier, vol. 198(3), pages 922-935, November.
    4. Mehdi Ammi & Christine Peyron, 2016. "Heterogeneity in general practitioners’ preferences for quality improvement programs: a choice experiment and policy simulation in France," Health Economics Review, Springer, vol. 6(1), pages 1-11, December.
    5. Navneet Vidyarthi & Onur Kuzgunkaya, 2015. "The impact of directed choice on the design of preventive healthcare facility network under congestion," Health Care Management Science, Springer, vol. 18(4), pages 459-474, December.
    6. Fogliatto, Flavio S. & da Silveira, Giovani J.C., 2008. "Mass customization: A method for market segmentation and choice menu design," International Journal of Production Economics, Elsevier, vol. 111(2), pages 606-622, February.
    7. Richard Abreu Lourenco & Marion Haas & Jane Hall & Rosalie Viney, 2017. "Valuing Meta-Health Effects for Use in Economic Evaluations to Inform Reimbursement Decisions: A Review of the Evidence," PharmacoEconomics, Springer, vol. 35(3), pages 347-362, March.

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