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Inconsistencies in TTO and VAS Values for EQ-5D Health States

Author

Listed:
  • Leida M. Lamers

    (Institute for Medical Technology Assessment (iMTA), Erasmus MC, PO Box 1738, 3000 DR Rotterdam, the Netherlands l.lamers@erasmusmc.nl)

  • Peep F. M. Stalmeier

    (Department of Radiation Oncology; Department of Medical Technology Assessment, Radboud University Nijmegen Medical Centre, the Netherlands)

  • Paul F. M. Krabbe

    (Department of Medical Technology Assessment, Radboud University Nijmegen Medical Centre, the Netherlands)

  • Jan J. V. Busschbach

    (Viersprong Institute for Studies on Personality Disorders, Halsteren, the Netherlands)

Abstract

Background. Most EQ-5D health states can be ordered logically. When people assign values to different health states, they may violate this logical order, which can be seen as inconsistencies. Objective. The aim of this study was to assess the effect of inconsistently valued EQ-5D health states on mean visual analog scale (VAS) and time trade-off (TTO) values. The authors also examined the effect of removing respondents with high numbers of inconsistent states on the estimation of tariffs, which is used to interpolate values to all possible EQ-5D states from the direct valuation of a subset of states. Method. Data from the Dutch EQ-5D valuation study were used. A representative sample of 309 Dutch adults valued 17 EQ-5D health states by VAS and TTO. A state was valued inconsistently when it had a higher value than at least 1 logically better state. Mean values of groups with various numbers of inconsistently valued states were compared. Results. Of the respondents, 65% had inconsistencies for VAS and 89% for TTO. The mean VAS values of consistent respondents tend to be lower. For TTO, those with inconsistencies gave lower values. Removing data of respondents with the highest number of inconsistently valued states for VAS (13%) and TTO (9%) did not result in statistically significant different coefficients in the estimated tariff using all data. Conclusion. The majority of respondents valued at least 1 state inconsistently. For both VAS and TTO, the presence of these inconsistencies did not affect the estimated tariffs

Suggested Citation

  • Leida M. Lamers & Peep F. M. Stalmeier & Paul F. M. Krabbe & Jan J. V. Busschbach, 2006. "Inconsistencies in TTO and VAS Values for EQ-5D Health States," Medical Decision Making, , vol. 26(2), pages 173-181, March.
    • Handle: RePEc:sae:medema:v:26:y:2006:i:2:p:173-181
    DOI: 10.1177/0272989X06286480
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    References listed on IDEAS

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    1. Bansback, Nick & Brazier, John & Tsuchiya, Aki & Anis, Aslam, 2012. "Using a discrete choice experiment to estimate health state utility values," Journal of Health Economics, Elsevier, vol. 31(1), pages 306-318.
    2. Eva Rodríguez Míguez & José María Abellán Perpiñán & José Carlos Álvarez Villamarín & José Manuel González Martínez & Antonio Rodríguez Sampayo, 2013. "Development of a new preference-based instrument to measure dependency," Working Papers 1301, Universidade de Vigo, Departamento de Economía Aplicada.
    3. Arthur E. Attema & Werner B. F. Brouwer, 2008. "Can we fix it? Yes we can! But what? A new test of procedural invariance in TTO‐measurement," Health Economics, John Wiley & Sons, Ltd., vol. 17(7), pages 877-885, July.
    4. Attema, Arthur E. & Brouwer, Werner B.F., 2009. "The correction of TTO-scores for utility curvature using a risk-free utility elicitation method," Journal of Health Economics, Elsevier, vol. 28(1), pages 234-243, January.
    5. Bromley, Hannah L. & Petrie, Dennis & Mann, G.Bruce & Nickson, Carolyn & Rea, Daniel & Roberts, Tracy E., 2019. "Valuing the health states associated with breast cancer screening programmes: A systematic review of economic measures," Social Science & Medicine, Elsevier, vol. 228(C), pages 142-154.
    6. Bansback, Nick & Brazier, John & Tsuchiya, Aki & Anis, Aslam, 2010. "Using a discrete choice experiment to estimate societal health state utility values," MPRA Paper 29933, University Library of Munich, Germany.
    7. Franz Ombler & Michael Albert & Paul Hansen, 2017. "The true significance of ‘high’ correlations between EQ-5D value sets," Working Papers 1704, University of Otago, Department of Economics, revised Mar 2017.
    8. Eve Wittenberg & Lisa Prosser, 2011. "Ordering errors, objections and invariance in utility survey responses," Applied Health Economics and Health Policy, Springer, vol. 9(4), pages 225-241, July.
    9. Zoltán Hermann & Márta Péntek & László Gulácsi & Irén Anna Kopcsóné Németh & Zsombor Zrubka, 2022. "Measuring the acceptability of EQ-5D-3L health states for different ages: a new adaptive survey methodology," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1243-1255, September.
    10. Franz Ombler & Michael Albert & Paul Hansen, 2018. "How Significant Are “High†Correlations Between EQ-5D Value Sets?," Medical Decision Making, , vol. 38(6), pages 635-645, August.
    11. Rodríguez-Míguez, E. & Abellán-Perpiñán, J.M. & Alvarez, X.C. & González, X.M. & Sampayo, A.R., 2016. "The DEP-6D, a new preference-based measure to assess health states of dependency," Social Science & Medicine, Elsevier, vol. 153(C), pages 210-219.
    12. Zhihao Yang & Jan van Busschbach & Reinier Timman & M F Janssen & Nan Luo, 2017. "Logical inconsistencies in time trade-off valuation of EQ-5D-5L health states: Whose fault is it?," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-10, September.
    13. Sharma, Rajiv & Stano, Miron, 2010. "Implications of an economic model of health states worse than dead," Journal of Health Economics, Elsevier, vol. 29(4), pages 536-540, July.
    14. Schneider, Paul, 2019. "Social tariffs and democratic choice – do population-based health state values reflect the will of the people?," SocArXiv 2qvjb, Center for Open Science.
    15. Hans-Helmut König & Oliver Günther & Matthias Angermeyer & Christiane Roick, 2009. "Utility Assessment in Patients with Mental Disorders," PharmacoEconomics, Springer, vol. 27(5), pages 405-419, May.
    16. Nancy J. Devlin & Koonal K. Shah & Brendan J. Mulhern & Krystallia Pantiri & Ben van Hout, 2019. "A new method for valuing health: directly eliciting personal utility functions," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(2), pages 257-270, March.

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