Estimating the Fuzzy Trade-Offs Between Health Dimensions with Standard Time Trade-Off Data
- 657 Downloads
Optimizing health provision requires measuring health, best using societal preferences. Health-related quality of life is evaluated with multiple criteria (e.g. feeling pain or being depressed), and their importance must be quantified. In a time trade-off (TTO) elicitation method, worsening in various attributes is compared with shortening the duration of life—a task unlike everyday experience. Therefore, we claim the trade-off coefficients should be treated as fuzzy numbers to allow imprecision. Additionally, a typical TTO protocol allows only limited number of final outcomes, enforcing approximate answers. In our model, we assume the respondent terminates TTO when the implied utility falls within the 1-cut of the true fuzzy disutility (normal and rectangular, simplifying). We show how to estimate such disutilities with standard TTO data (existing datasets can be used) in the hierarchical Bayesian setting. We test our approach on data collected in Poland with EQ-5D-3L descriptive system. For example, the disutility of worsening mobility to level 2 or 3 results (on average) in a disutility with 1-cut equal to [0.076–0.089] or [0.398–0.483], respectively. Standard errors of interval bounds estimates amount to ca. 5%–15% of their values. We construct a fuzzy value set assigning fuzzy utilities to all 243 EQ-5D-3L health states. The fuzzy disutilities tend to be larger than the standard, crisp ones (e.g. the crisp parameters for mobility amount to 0.056 and 0.313, respectively), and the resulting fuzzy value set assigns lower values to utilities than the crisp one.
KeywordsPreference elicitation Utility Fuzzy numbers Time trade-off Imprecise preferences Multiple-criteria decision making
The research was financed by the funds obtained from National Science Centre, Poland, granted following the decision number DEC-2015/19/B/HS4/01729. We would like to thank Juan-Manuel Ramos Goñi for comments on the initial results presented during the EuroQol Group Meeting in Berlin, 2016.
- Dolan, P., Gudex, C., Kind, P., Williams, A.: The Measurement and Valuation of Health. First report on the main survey. Technical report, Centre for Health Economics, University of York (1995)Google Scholar
- Jakubczyk, M.: Impact of complementarity and heterogeneity on health related utility of life. Central Eur. J. Econ. Model. Econometrics 1, 139–156 (2009)Google Scholar
- Jakubczyk, M.: Using a fuzzy approach in multi-criteria decision making with multiple alternatives in health care. Multiple Criteria Decis. Making 10, 65–81 (2015)Google Scholar
- Jakubczyk, M., Kamiński, B., Lewandowski, M.: Eliciting Fuzzy Preferences Towards Health States with Discrete Choice Experiments (2017)Google Scholar
- Szende, A., Oppe, M., Devlin, N. (eds.): EQ-5D Value Sets: Inventory, Comparative Review and User Guide. Springer Netherlands (2007)Google Scholar