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Weighing Clinical Evidence Using Patient Preferences: An Application of Probabilistic Multi-Criteria Decision Analysis

Author

Listed:
  • Henk Broekhuizen

    (University of Twente)

  • Maarten J. IJzerman

    (University of Twente)

  • A. Brett Hauber

    (RTI Health Solutions)

  • Catharina G. M. Groothuis-Oudshoorn

    (University of Twente)

Abstract

The need for patient engagement has been recognized by regulatory agencies, but there is no consensus about how to operationalize this. One approach is the formal elicitation and use of patient preferences for weighing clinical outcomes. The aim of this study was to demonstrate how patient preferences can be used to weigh clinical outcomes when both preferences and clinical outcomes are uncertain by applying a probabilistic value-based multi-criteria decision analysis (MCDA) method. Probability distributions were used to model random variation and parameter uncertainty in preferences, and parameter uncertainty in clinical outcomes. The posterior value distributions and rank probabilities for each treatment were obtained using Monte-Carlo simulations. The probability of achieving the first rank is the probability that a treatment represents the highest value to patients. We illustrated our methodology for a simplified case on six HIV treatments. Preferences were modeled with normal distributions and clinical outcomes were modeled with beta distributions. The treatment value distributions showed the rank order of treatments according to patients and illustrate the remaining decision uncertainty. This study demonstrated how patient preference data can be used to weigh clinical evidence using MCDA. The model takes into account uncertainty in preferences and clinical outcomes. The model can support decision makers during the aggregation step of the MCDA process and provides a first step toward preference-based personalized medicine, yet requires further testing regarding its appropriate use in real-world settings.

Suggested Citation

  • Henk Broekhuizen & Maarten J. IJzerman & A. Brett Hauber & Catharina G. M. Groothuis-Oudshoorn, 2017. "Weighing Clinical Evidence Using Patient Preferences: An Application of Probabilistic Multi-Criteria Decision Analysis," PharmacoEconomics, Springer, vol. 35(3), pages 259-269, March.
  • Handle: RePEc:spr:pharme:v:35:y:2017:i:3:d:10.1007_s40273-016-0467-z
    DOI: 10.1007/s40273-016-0467-z
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    References listed on IDEAS

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    1. P. Thokala & A. Duenas, 2012. "Multiple Criteria Decision Analysis for Health Technology Assessment," Post-Print hal-00800398, HAL.
    2. repec:ehl:wpaper:12761 is not listed on IDEAS
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    Cited by:

    1. Mónica D. Oliveira & Inês Mataloto & Panos Kanavos, 2019. "Multi-criteria decision analysis for health technology assessment: addressing methodological challenges to improve the state of the art," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 891-918, August.

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