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Deciding kidney-offer admissibility dependent on patients’ lifetime failure rate

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  • Bendersky, Michael
  • David, Israel

Abstract

We use developments in full-information optimal stopping to decide kidney-offer admissibility depending on the patient’s age in treatment, on his/her estimated lifetime probabilistic profile and his/her prospects on the waiting list. We allow for a broad family of lifetime distributions – the Gamma – thus enabling flexible modeling of patients survival under dialysis. We fully automate an appropriate recursive solution in a spreadsheet application. It yields the optimal critical times for acceptance of offers of different qualities, and the ensuing expected value-to-go as a function of time. The model may serve both the organizer of a donation program for planning purposes, and the particular surgeon in making the critical decision at the proper time. It may further serve the potential individual recipient, practicing present-day patient-choice. Numerical results and their discussion are included.

Suggested Citation

  • Bendersky, Michael & David, Israel, 2016. "Deciding kidney-offer admissibility dependent on patients’ lifetime failure rate," European Journal of Operational Research, Elsevier, vol. 251(2), pages 686-693.
    • Handle: RePEc:eee:ejores:v:251:y:2016:i:2:p:686-693
    DOI: 10.1016/j.ejor.2015.12.009
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    References listed on IDEAS

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    Cited by:

    1. Amir Elalouf & Ariel Rosenfeld & Ofir Rockach, 2023. "The Extended David-Yechiali Rule for Kidney Allocation," Mathematics, MDPI, vol. 11(2), pages 1-16, January.
    2. Yael Deutsch & Israel David, 2020. "Benchmark policies for utility-carrying queues with impatience," Queueing Systems: Theory and Applications, Springer, vol. 95(1), pages 97-120, June.
    3. Perlman, Yael & Elalouf, Amir & Yechiali, Uri, 2018. "Dynamic allocation of stochastically-arriving flexible resources to random streams of objects with application to kidney cross-transplantation," European Journal of Operational Research, Elsevier, vol. 265(1), pages 169-177.
    4. Oztekin, Asil & Al-Ebbini, Lina & Sevkli, Zulal & Delen, Dursun, 2018. "A decision analytic approach to predicting quality of life for lung transplant recipients: A hybrid genetic algorithms-based methodology," European Journal of Operational Research, Elsevier, vol. 266(2), pages 639-651.

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