Abstract
Most people consider health (quality and duration of life) as important but since we rarely choose between health states, our preferences are often not well-formed; moreover, the quality of life is frequently defined using imprecise terms (e.g. moderate difficulties doing usual activities). Therefore, we propose to model preferences towards health states (precisely: disutilities of worsening health dimensions in the EQ-5D-5L descriptive system) as fuzzy: each worsening is assigned an interval instead of a crisp number. We elicit such preferences with discrete choice experiment (DCE) data, using a maximum likelihood approach and bootstrapping to assess the estimation error. For example, the disutility of moderate difficulties doing usual activities was estimated as lying in the interval (0.018; 0.206). Pain/discomfort and anxiety/depression are associated with greatest upper bounds of disutilities and largest fuzziness (longest ranges). Our approach dispenses with one of the non-intuitive features of the standard approach to DCE, where even a clearly dominated alternative has a positive probability of being chosen; in our model, if the disutility ranges do not overlap, the worse alternative will never be chosen. Also, our model is more consistent regarding the constant proportional trade-off condition: the probability of a given health state being chosen in a pair will not change if durations are scaled proportionally; something that is not true in the standard DCE model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
The general idea is presented. The original formulas and notation are slightly changed.
- 2.
In a degenerate case \(L(Q)=H(Q)\), the membership function jumps discontinuously from 1 to 0.
- 3.
This model is originally meant for decisions under uncertainty, but we can confine attention to sure alternatives, because they constitute a subset of all alternatives.
References
Attema, A.E., Brouwer, W.B.: On the (not so) constant proportional trade-off in TTO. Qual. Life Res. 19, 489–497 (2010)
Attema, A.E., Versteegh, M.M., Oppe, M., Brouwer, W.B., Stolk, E.A.: Lead time TTO: leading to better health state valuations? Health Econ. 22, 376–392 (2013)
Bansback, N., Brazier, J., Tsuchiya, A., Anis, A.: Using a discrete choice experiment to estimate health state utility values. J. Health Econ. 31, 306–318 (2012)
Bezanson, J., Edelman, A., Karpinski, S., Shah, V.B.: Julia: a fresh approach to numerical computing (2014). arXiv 1411.1607
Bleichrodt, H., Johannesson, M.: The validity of QALYs: an experimental test of constant proportional tradeoff and utility independence. Med. Decis. Mak. 17, 21–32 (1997)
Bleichrodt, H., Quiggin, J.: Characterizing QALYs under a general rank dependent utility model. J. Risk Uncertain. 15, 151–165 (1997)
Bleichrodt, H., Wakker, P., Johannesson, M.: Characterizing QALYs by risk neutrality. J. Risk Uncertain. 15, 107–114 (1997)
Brooks, R., De Charro, F.: EuroQol: the current state of play. Health Policy 37, 53–72 (1996)
Devlin, N., Tsuchiya, A., Buckingham, K., Tilling, C.: A uniform time trade off method for states better and worse than dead: feasibility study of the ‘lead time’ approach. Health Econ. 20, 348–361 (2011)
Dolan, P., Gudex, C., Kind, P., Williams, A.: The time trade-off method: results from a general population study. Health Econom. 5, 141–154 (1996)
Drummond, M.F., Scupher, M.J., Torrance, G.W., O’Brien, B.J., Stoddart, G.L.: Methods for the Economic Evaluation of Health Care Programmes. Oxford University Press (2005)
Elrod, T., Chrzan, K.: The value of extent-of-preference information in choice-based conjoint analysis. In: Gustafsson, A., Herrmann, A., Huber, F. (eds.) Conjoint Measurement, pp. 209–223. Springer, Methods and Applications (2000)
Fechner, G.: Elemente der Psychophysik (2 Vols) (1860). Breitkopf and Hartel. Vol. 1 trans, by Adler, H.E. (1966)
Feng, Y., Devlin, N., Shah, K., Mulhern, B., van Hout, B.: New methods for modelling EQ-5D-5L value sets: an application to English data. Health Economics & Decision Science (HEDS) Discussion Paper Series, University of Sheffield (2016)
Fishburn, P.C.: Intransitive indifference in preference theory: a survey. Oper. Res. 18(2), 207–228 (1970)
Fishburn, P.C.: Interval graphs and interval orders. Discret. math. 55(2), 135–149 (1985)
Gil-Aluja, J.: Elements for a Theory of Decision in Uncertainty. Springer Science+Business Media Dordrecht (1999)
Gil-Aluja, J.: Fuzzy Sets in the Management of Uncertainty. Springer, Berlin Heidelberg (2004)
Gil-Aluja, J.: Investment in Uncertainty, vol. 21. Springer Science & Business Media
Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D., Bonsel, G., Badia, X.: Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of life research: an international journal of quality of life aspects of treatment, care and rehabilitation 20, 1727–1736 (2011)
Jakubczyk, M., Kamiński, B.: Fuzzy approach to decision analysis with multiple criteria and uncertainty in health technology assessment. Ann. Oper. Res. (2015). https://doi.org/10.1007/s10479-015-1910-9
Jakubczyk, M., Golicki, D.: Estimating the impact of EQ-5D dimensions as fuzzy numbers with hierarchical Bayesian modelling of regular TTO data. In: EuroQol Plenary Meeting (2016)
Kondratenko, G.V., Kondratenko, Y.P., Romanov, D.O.: Fuzzy Models for Capacitive Vehicle Routing Problem in Uncertainty. In: Proceedings of 17th International DAAAM Symposium “Intelligent Manufacturing and Automation: Focus on Mechatronics & Robotics”, pp. 205–206 (2006)
Kontek, K., Lewandowski, M.: Range-dependent utility. Manag. Sci. (forthcoming) (2016)
Luce, R.D.: Semiorders and a theory of utility discrimination. Econometrica, 178–191 (1956)
Luce, R.D.: A probabilistic theory of utility. Econometrica, 193–224 (1958)
Miyamoto, J.M., Wakker , P.P., Bleichrodt, H., Peters, H.J.M.: The Zero-Condition: a simplifying assumption in QALY measurement and multiattribute Utility. Manag. Sci. 44 (1998)
Rowen, D., Brazier, J., van Hout, B.: A comparison of methods for converting DCE values onto the full health-dead QALY scale. Med. Decis. Mak. 35, 328–340 (2015)
Weber, E.: De tactu. Koehler, Leipzig (1834)
Weinstein, M.C., Torrance, G., McGuire, A.: QALYs: the basics. Value Health 12, S5–S9 (2009)
Whitehead, S.J., Ali, S.: Health outcomes in economic evaluation: the QALY and utilities. British Medical Bulletin 96, 5–21 (2010)
Zadeh, L.: Fuzzy Sets. Inf. Control 8, 338–353 (1965)
Acknowledgements
The research was financed by the funds obtained from National Science Centre, Poland, granted following the decision number DEC-2015/19/B/HS4/01729.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Jakubczyk, M., Kamiński, B., Lewandowski, M. (2018). Eliciting Fuzzy Preferences Towards Health States with Discrete Choice Experiments. In: Berger-Vachon, C., Gil Lafuente, A., Kacprzyk, J., Kondratenko, Y., Merigó, J., Morabito, C. (eds) Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Studies in Systems, Decision and Control, vol 125. Springer, Cham. https://doi.org/10.1007/978-3-319-69989-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-69989-9_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69988-2
Online ISBN: 978-3-319-69989-9
eBook Packages: EngineeringEngineering (R0)