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Choosing Among Living-Donor and Cadaveric Livers

Author

Listed:
  • Oguzhan Alagoz

    (Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706)

  • Lisa M. Maillart

    (Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261)

  • Andrew J. Schaefer

    (Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261)

  • Mark S. Roberts

    (Section of Decision Sciences and Clinical Systems Modeling, Division of General Internal Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213)

Abstract

The only therapy for a patient with end-stage liver disease (ESLD) is liver transplantation, which is performed by using either a cadaveric liver from a deceased donor or a portion of a living-donor's liver. This study addresses the following decision problem for an ESLD patient with an available living donor. Should she have a transplantation now or wait? If she decides to have the transplantation now, should she use her living-donor liver or a cadaveric liver for transplantation? We formulate this problem as a discrete-time, infinite-horizon Markov decision process model and solve it using clinical data. Because living donors are typically related to the recipient, we incorporate a disutility associated with using the living-donor liver as opposed to using a cadaveric liver. We perform a structural analysis of the model, including a set of intuitive conditions that ensure the existence of structured policies such as an at-most-three-region (AM3R) optimal policy. Our computational experiments confirm that the optimal policy is typically of AM3R type.

Suggested Citation

  • Oguzhan Alagoz & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2007. "Choosing Among Living-Donor and Cadaveric Livers," Management Science, INFORMS, vol. 53(11), pages 1702-1715, November.
  • Handle: RePEc:inm:ormnsc:v:53:y:2007:i:11:p:1702-1715
    DOI: 10.1287/mnsc.1070.0726
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    References listed on IDEAS

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    11. Oguzhan Alagoz & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2004. "The Optimal Timing of Living-Donor Liver Transplantation," Management Science, INFORMS, vol. 50(10), pages 1420-1430, October.
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    Cited by:

    1. Burhaneddin Sandıkçı & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2013. "Alleviating the Patient's Price of Privacy Through a Partially Observable Waiting List," Management Science, INFORMS, vol. 59(8), pages 1836-1854, August.
    2. Nikhil N. Dhakate & Rohit Joshi, 2020. "Analysing Process of Organ Donation and Transplantation Services in India at Hospital Level: SAP-LAP Model," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(4), pages 323-339, December.
    3. Mason, J.E. & Denton, B.T. & Shah, N.D. & Smith, S.A., 2014. "Optimizing the simultaneous management of blood pressure and cholesterol for type 2 diabetes patients," European Journal of Operational Research, Elsevier, vol. 233(3), pages 727-738.
    4. Oguzhan Alagoz & Heather Hsu & Andrew J. Schaefer & Mark S. Roberts, 2010. "Markov Decision Processes: A Tool for Sequential Decision Making under Uncertainty," Medical Decision Making, , vol. 30(4), pages 474-483, July.
    5. Burhaneddin Sandıkçı & Lisa M. Maillart & Andrew J. Schaefer & Oguzhan Alagoz & Mark S. Roberts, 2008. "Estimating the Patient's Price of Privacy in Liver Transplantation," Operations Research, INFORMS, vol. 56(6), pages 1393-1410, December.
    6. Ozge Ceren Ersoy & Diwakar Gupta & Timothy Pruett, 2021. "A critical look at the U.S. deceased‐donor organ procurement and utilization system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 3-29, February.
    7. Zeynep Erkin & Matthew D. Bailey & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2010. "Eliciting Patients' Revealed Preferences: An Inverse Markov Decision Process Approach," Decision Analysis, INFORMS, vol. 7(4), pages 358-365, December.
    8. Jinghua Shi & Oguzhan Alagoz & Fatih Erenay & Qiang Su, 2014. "A survey of optimization models on cancer chemotherapy treatment planning," Annals of Operations Research, Springer, vol. 221(1), pages 331-356, October.
    9. Sen Lin & Bo Li & Antonio Arreola-Risa & Yiwei Huang, 2023. "Optimizing a single-product production-inventory system under constant absolute risk aversion," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 510-537, October.
    10. Mustafa Akan & Oguzhan Alagoz & Baris Ata & Fatih Safa Erenay & Adnan Said, 2012. "A Broader View of Designing the Liver Allocation System," Operations Research, INFORMS, vol. 60(4), pages 757-770, August.
    11. Miao He & Lei Zhao & Warren Powell, 2010. "Optimal control of dosage decisions in controlled ovarian hyperstimulation," Annals of Operations Research, Springer, vol. 178(1), pages 223-245, July.
    12. Klein, Michael G. & Verter, Vedat & Moses, Brian G., 2020. "Designing a rural network of dialysis facilities," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1088-1100.
    13. Murat Kurt & Mark S. Roberts & Andrew J. Schaefer & M. Utku Ünver, 2011. "Valuing Prearranged Paired Kidney Exchanges: A Stochastic Game Approach," Boston College Working Papers in Economics 785, Boston College Department of Economics, revised 14 Oct 2011.

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