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Applying conjoint analysis in economic evaluations: an application to menorrhagia

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  • Fernando San Miguel
  • Mandy Ryan
  • Emma McIntosh

Abstract

The increased demand for health care, coupled with limited resources, means that decisions have to be made concerning the allocation of scarce health care resources. This paper considers how conjoint analysis (CA) can be used to aid this decision making process. It is shown how the technique can be used to estimate marginal rates of substitution between attributes, willingness to pay (WTP) if cost is included as an attribute and overall utility scores for different ways of providing a service. The technique is applied to consider women's preferences for two surgical procedures in the treatment of menorrhagia: hysterectomy and conservative surgery. The results suggest conservative surgery is preferred to hysterectomy, as indicated by higher utility scores for the former and a marginal WTP of 7593 to have conservative surgery rather than hysterectomy. The internal validity of CA was also shown. It is concluded that CA is a potentially useful instrument for policy makers. However, numerous methodological issues need addressing before the technique becomes an established instrument within economic evaluations.

Suggested Citation

  • Fernando San Miguel & Mandy Ryan & Emma McIntosh, 2000. "Applying conjoint analysis in economic evaluations: an application to menorrhagia," Applied Economics, Taylor & Francis Journals, vol. 32(7), pages 823-833.
  • Handle: RePEc:taf:applec:v:32:y:2000:i:7:p:823-833
    DOI: 10.1080/000368400322165
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    References listed on IDEAS

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    1. Paul Kind, 1988. "The design and construction of quality of life measures," Working Papers 043chedp, Centre for Health Economics, University of York.
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    Cited by:

    1. Debby van Helvoort-Postulart & Benedict G. C. Dellaert & Trudy van der Weijden & Maarten F. von Meyenfeldt & Carmen D. Dirksen, 2009. "Discrete choice experiments for complex health-care decisions: does hierarchical information integration offer a solution?," Health Economics, John Wiley & Sons, Ltd., vol. 18(8), pages 903-920.
    2. Daniele Fabbri & Chiara Monfardini, 2008. "Style of practice and assortative mating: a recursive probit analysis of Caesarean section scheduling in Italy," Applied Economics, Taylor & Francis Journals, vol. 40(11), pages 1411-1423.
    3. Emily Lancsar & Elizabeth Savage, 2004. "Deriving welfare measures from discrete choice experiments: inconsistency between current methods and random utility and welfare theory," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 901-907.
    4. Patterson, Paul M. & Martinez, Samuel Cardona, 2004. "State and Origin Branding in Hispanic Food Markets," Journal of Food Distribution Research, Food Distribution Research Society, vol. 35(03), November.
    5. Patrizia Riganti & Anna Alberini & Alberto Longo, 2005. "Public Preferences for Land usesÂ’ changes - valuing urban regeneration projects at the Venice Arsenale," ERSA conference papers ersa05p756, European Regional Science Association.
    6. Harrison, R. Wes & Gillespie, Jeffrey M. & Fields, Deacue, 2005. "Analysis of Cardinal and Ordinal Assumptions in Conjoint Analysis," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 34(2), October.
    7. Poulos, Christine & Yang, Jui-Chen & Levin, Carol & Van Minh, Hoang & Giang, Kim Bao & Nguyen, Diep, 2011. "Mothers' preferences and willingness to pay for HPV vaccines in Vinh Long Province, Vietnam," Social Science & Medicine, Elsevier, vol. 73(2), pages 226-234, July.
    8. Lee, Jongsu & Cho, Youngsang, 2009. "Demand forecasting of diesel passenger car considering consumer preference and government regulation in South Korea," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 420-429, May.
    9. Scott, Anthony, 2002. "Identifying and analysing dominant preferences in discrete choice experiments: An application in health care," Journal of Economic Psychology, Elsevier, vol. 23(3), pages 383-398, June.
    10. Lim, Jennifer N.W. & Edlin, Richard, 2009. "Preferences of older patients and choice of treatment location in the UK: A binary choice experiment," Health Policy, Elsevier, vol. 91(3), pages 252-257, August.
    11. Giebel, Olaf & Breitschopf, Barbara, 2011. "The impact of policy elements on the financing costs of RE investment: The case of wind power in Germany," Working Papers "Sustainability and Innovation" S11/2011, Fraunhofer Institute for Systems and Innovation Research (ISI).
    12. Yeonbae Kim & Jeong-Dong Lee & Daeyoung Koh, 2005. "Effects of consumer preferences on the convergence of mobile telecommunications devices," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 817-826.
    13. Yusuke Sakata & Junyi Shen & Yoshizo Hashimoto, 2006. "The Influence of Environmental Deterioration and Network Improvement on Transport Modal Choice," Discussion Papers in Economics and Business 06-04, Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP).
    14. Stirling Bryan & Paul Dolan, 2004. "Discrete choice experiments in health economics," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 5(3), pages 199-202, September.

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