Using Conjoint Analysis to Evaluate Health State Preferences

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Quality of life dimensions are important considerations when patients evaluate pharmaceutical products with respect to personal benefits. Traditionally, standard gamble, time trade-off, and rating scale techniques are used to obtain preference (utility) estimates for various quality of life dimensions. This study examines three objectives to determine the feasibility of using conjoint analysis to elicit patient preferences for a particular health state. For the first objective, patients with multiple myeloma were asked to select quality of life conditions for 18 hypothetical patients with cancer and to indicate which conditions were the easiest and hardest to live with. Second, patients were asked to rate several cancer-related and general symptoms using visual analog scales. Third, comparisons were made between the two techniques to determine similarity and validity. Results revealed that conjoint analysis is useful for health-related quality of life research, and that conjoint analysis results compare favorably with values obtained from visual analog scales.

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  1. 1.

    Nunnally JC. Psychometric Theory. 2nd ed. New York: McGraw-Hill; 1978.

  2. 2.

    Von Neumann J, Mergenstem O. Theory of Games and Economic Behavior. 2nd ed. Princeton, NJ: University Press; 1947.

  3. 3.

    Keeney RL, Raiffa H. Decisions with Multiple Objectives. New York, NY: Cambridge University Press; 1993:131–139.

  4. 4.

    Luce RD, Tukey JW. Simultaneous conjoint measurement: A new type of fundamental measurement. J Mathematical Psychol. 1964;1:1–27.

  5. 5.

    Torrance GW, Feeny DH, Furlong WJ, Barr RD, Zhang Y, Wang Q. Multiattribute utility function for a comprehensive health status classification system. Med Cure. 1996;34(7):702–722.

  6. 6.

    Addington-Hall JM. MacDonald LD, Anderson HR. Can the Spitzer quality of life index help to reduce prognostic uncertainty in terminal care? Br J Cancer. 1990;62:695–699.

  7. 7.

    Spitzer WO, Dobson AJ, Hall J, Chesterman E, Levi J, Shephard R, Battista Renaldo N, Catchlove BR. Measuring the quality of life of cancer patients. J Chron Dis. 1981;34:585–597.

  8. 8.

    Coates A, Thomson D, McLeod GRM, Hersey P, Gill PG, Olver IN, Kefford R, Lowenthal RM, Beadle G, Walpole E. Prognostic value of quality of life scores in a trial of chemotherapy with or without interferon in patients with metastatic malignant melanoma. European J Cancer. 1993;29A(12):1731–1734.

  9. 9.

    Wilson IB, Cleary PC. Linking clinical variables with health-related quality of life: A conceptual mode) of patient outcomes. JAMA. 1995;273(1): 59–65.

  10. 10.

    The EuroQol Group. EuroQol—A new facility for the measurement of health-related quality of life. Health Policy. 1990;16:199–208.

  11. 11.

    Uyl-de Groot CA, Rutten FFH, Bonsel GJ. Measurement and valuation of quality of life in economic appraisal of cancer treatment. Eur J Cancer. 1994; 30A:111–117.

  12. 12.

    Niezgoda HE, Pater JL. A validation study of the domains of the core EORTC quality of life questionnaire. Quality Life Res. 1993;2:319–325.

  13. 13.

    Brazier J, Jones N. Kind P. Testing the validity of the F.uroqol and comparing it with the SF-36 Health Survey questionnaire. Qual Life Res. 1993:2:169–180.

  14. 14.

    Ahles TA. Ruckdeschel JC, Blanchard EB. Caner-related pain-11. Assessment with visual analogue scales. J Psychosom Res. 1984;28:121–124.

  15. 15.

    Price DD, Bush HM, Long S, et al. A comparison of pain measurement characteristics of mechanical visual analogue and simple numerical rating scales. Pain. 1994;56:217–226.

  16. 16.

    Guyatt GH, Townsend M, Berman LB, Keller JL. A comparison of likert and visual analogue scales for measuring change in funtion. J Chronic Dis. 1987; Vol 40(12):1129–1133.

  17. 17.

    Drummond MF, Stoddart GL. Torrance GW. Methods for the Economic Evaluation of Health Care Programmes. Oxford: Oxford Medical Publications, Oxford University Press; 1992.

  18. 18.

    Thurstone LL. Attitudes can be measured. Am J Sociol. 1928;33:529–554.

  19. 19.

    Gensch DH, Recker WW. The multinomial, multiat-tribute logit choice model. J Marketing Res. 1979; Vol XVI: 124–132.

  20. 20.

    Szeinbach SL, Barnes JH. Garner DD. Building brand equity in the pharmaceutical industry through value-added services: an application of maximum difference conjoint analysis using best-worst scaling. J Business Res. 1997;40:226–236.

  21. 21.

    Horowitz JL, Louviere JJ. Testing predicted choices against observations in probabilistic discrete-choice models. Marketing Sci. 1993;12(3):270–279.

  22. 22.

    Lynch JG. Uniqueness issues in the decompositional modeling of multiattribute overall evaluations: an information integration perspective. J Marketing Res. 1985;22:1–19.

  23. 23.

    Louviere JJ, Finn A, Timmermans H. Retailing research. In McGraw-Hill Handbook of Marketing Research. New York: McGraw-Hill Book Company; 1992.

  24. 24.

    Louviere JJ, Swait J, Anderson D. Best-worst conjoint: theory, methods and comparisons with choicebased conjoint and reported marketplace choices. Working Paper. University of Florida, 1995.

  25. 25.

    Ware JE. Sherboume CD. The MOS 36-item Short-Form Health Survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30:473–483.

  26. 26.

    McHorney CA, Ware JE Jr, Raczek AE. The MOS 36-item Short-Form Health Survey (SF-36):II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care. 1993;31:247–263.

  27. 27.

    Jack W. Pharmaceutical differentiation through quality of life measurement: a case study. J Pharm Mark Man. 1991:6:65–85.

  28. 28.

    Melzack R. The McGill pain questionniare; major properties and scoring methods. Pain. 1975; 1227–1299.

  29. 29.

    Ahles TA, Ruckdeschel JC, Blanchard EB. Caner-relted pain-II. Assessment with visual analogue scales. J Psychosom Res. 1984:28:121–124.

  30. 30.

    Cresswell SM. English PJ, Roberts JT. Marsh MM. Pain relief and quality-of-life assessment following intravenous and oral clodronate in hormone-escaped metastatic prostate cancer. Br J Urol. 1995;76:360–365.

  31. 31.

    Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica. 1979;47(2): 263–291.

  32. 32.

    Krupnick AJ. Cropper M. The effect of information on health risk valuations. J Risk Uncertainty. 1992; 5:29–48.

  33. 33.

    Viscusi W. Kip WM. Huber J. Pricing environmental health risks: A survey assessment of risk-risk and risk-dollar trade-offs for chronic bronchitis. J Environmental Econ Manage. 1991;21:32–51.

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Author information

Correspondence to Sheryl L. Szeinbach PhD, RPh.

Additional information

Pesented at the DIA Symposium “Quality of Life Evaluation.” April 6–8. 1998, Hilton Head, South Carolina.

Support for this study was provided by a grant from Novartis.

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Szeinbach, S.L., Barnes, J.H., McGhan, W.F. et al. Using Conjoint Analysis to Evaluate Health State Preferences. Ther Innov Regul Sci 33, 849–858 (1999).

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Key Words

  • Health state preferences
  • Conjoint analysis
  • Visual analog scaling
  • Quality of life multiple myeloma