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Eliciting Benefit–Risk Preferences and Probability-Weighted Utility Using Choice-Format Conjoint Analysis

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  • George Van Houtven
  • F. Reed Johnson
  • Vikram Kilambi
  • A. Brett Hauber

Abstract

This study applies conjoint analysis to estimate health-related benefit-risk tradeoffs in a non-expected-utility framework. We demonstrate how this method can be used to test for and estimate nonlinear weighting of adverse-event probabilities and we explore the implications of nonlinear weighting on maximum acceptable risk (MAR) measures of risk tolerance. We obtained preference data from 570 Crohn’s disease patients using a web-enabled conjoint survey. Respondents were presented with choice tasks involving treatment options that involve different efficacy benefits and different mortality risks for 3 possible side effects. Using conditional logit maximum likelihood estimation, we estimate preference parameters using 3 models that allow for nonlinear preference weighting of risks—a categorical model, a simple-weighting model, and a rank dependent utility (RDU) model. For the second 2 models we specify and jointly estimate 1- and 2-parameter probability weighting functions. Although the 2-parameter functions are more flexible, estimation of the 1-parameter functions generally performed better. Despite well-known conceptual limitations, the simple-weighting model allows us to estimate weighting function parameters that vary across 3 risk types, and we find some evidence of statistically significant differences across risks. The parameter estimates from RDU model with the single-parameter weighting function provide the most robust estimates of MAR. For an improvement in Crohn’s symptom severity from moderate and mild, we estimate maximum 10-year mortality risk tolerances ranging from 2.6% to 7.1%. Our results provide further the evidence that quantitative benefit-risk analysis used to evaluate medical interventions should account explicitly for the nonlinear probability weighting of preferences.

Suggested Citation

  • George Van Houtven & F. Reed Johnson & Vikram Kilambi & A. Brett Hauber, 2011. "Eliciting Benefit–Risk Preferences and Probability-Weighted Utility Using Choice-Format Conjoint Analysis," Medical Decision Making, , vol. 31(3), pages 469-480, May.
    • Handle: RePEc:sae:medema:v:31:y:2011:i:3:p:469-480
    DOI: 10.1177/0272989X10386116
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    References listed on IDEAS

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    Cited by:

    1. Juan Marcos Gonzalez & Marco Boeri, 2021. "The Impact of the Risk Functional Form Assumptions on Maximum Acceptable Risk Measures," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(6), pages 827-836, November.
    2. Angelyn Otteson Fairchild & Shelby D. Reed & Juan Marcos Gonzalez, 2023. "Method for Calculating the Simultaneous Maximum Acceptable Risk Threshold (SMART) from Discrete-Choice Experiment Benefit-Risk Studies," Medical Decision Making, , vol. 43(2), pages 227-238, February.
    3. F. Reed Johnson, 2023. "Comment on: Taking the Shortcut: Simplifying Heuristics in Discrete Choice Experiments," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 16(4), pages 289-292, July.

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