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The Optimal Timing of Living-Donor Liver Transplantation


  • Oguzhan Alagoz

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

  • Lisa M. Maillart

    () (Weatherhead School of Management, Case Western Reserve University, Cleveland, Ohio 44106)

  • Andrew J. Schaefer

    () (Departments of Industrial Engineering and Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15261)

  • Mark S. Roberts

    () (Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213)


Living donors are a significant and increasing source of livers for transplantation, mainly because of the insufficient supply of cadaveric organs. We consider the problem of optimally timing a living-donor liver transplant to maximize the patient's total reward, such as quality-adjusted life expectancy. We formulate a Markov decision process (MDP) model in which the state of the process is described by patient health. We derive structural properties of the MDP model, including a set of intuitive conditions that ensure the existence of a control-limit optimal policy. We use clinical data in our computational experiments, which show that the optimal policy is typically of control-limit type.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:10:p:1420-1430

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    References listed on IDEAS

    1. Chen, Mingchih & Feldman, Richard M., 1997. "Optimal replacement policies with minimal repair and age-dependent costs," European Journal of Operational Research, Elsevier, vol. 98(1), pages 75-84, April.
    2. Howard, David H., 2002. "Why do transplant surgeons turn down organs?: A model of the accept/reject decision," Journal of Health Economics, Elsevier, vol. 21(6), pages 957-969, November.
    3. Howard J. Weiss, 1979. "The Computation of Optimal Control Limits for a Queue with Batch Services," Management Science, INFORMS, vol. 25(4), pages 320-328, April.
    4. Chew, Soo Hong & Ho, Joanna L, 1994. "Hope: An Empirical Study of Attitude toward the Timing of Uncertainty Resolution," Journal of Risk and Uncertainty, Springer, vol. 8(3), pages 267-288, May.
    5. Jae-Hyeon Ahn & John C. Hornberger, 1996. "Involving Patients in the Cadaveric Kidney Transplant Allocation Process: A Decision-Theoretic Perspective," Management Science, INFORMS, vol. 42(5), pages 629-641, May.
    6. Cyrus Derman, 1963. "Optimal Replacement and Maintenance Under Markovian Deterioration with Probability Bounds on Failure," Management Science, INFORMS, vol. 9(3), pages 478-481, April.
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    Cited by:

    1. Caulkins, Jonathan P., 2010. "Might randomization in queue discipline be useful when waiting cost is a concave function of waiting time?," Socio-Economic Planning Sciences, Elsevier, vol. 44(1), pages 19-24, March.
    2. repec:pal:jorsoc:v:68:y:2017:i:9:d:10.1057_s41274-017-0219-2 is not listed on IDEAS
    3. Paarsch, Harry J. & Segre, Alberto M. & Roberts, John P. & Halldorson, Jeffrey B., 2011. "Competition and Post-Transplant Outcomes in Cadaveric Liver Transplantation under the MELD Scoring System," CIS Discussion paper series 522, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    4. 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.
    5. 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.
    6. Jingyu Zhang & Brian T. Denton & Hari Balasubramanian & Nilay D. Shah & Brant A. Inman, 2012. "Optimization of Prostate Biopsy Referral Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 529-547, October.
    7. Ching-Feng Lin & Aera LeBoulluec & Li Zeng & Victoria Chen & Robert Gatchel, 2014. "A decision-making framework for adaptive pain management," Health Care Management Science, Springer, vol. 17(3), pages 270-283, September.
    8. Kang, Yuncheol & Sawyer, Amy M. & Griffin, Paul M. & Prabhu, Vittaldas V., 2016. "Modelling adherence behaviour for the treatment of obstructive sleep apnoea," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1005-1013.
    9. Nan Kong & Andrew J. Schaefer & Brady Hunsaker & Mark S. Roberts, 2010. "Maximizing the Efficiency of the U.S. Liver Allocation System Through Region Design," Management Science, INFORMS, vol. 56(12), pages 2111-2122, December.
    10. repec:kap:hcarem:v:20:y:2017:i:2:d:10.1007_s10729-015-9347-x is not listed on IDEAS
    11. Baruch Keren & Joseph Pliskin, 2011. "Optimal timing of joint replacement using mathematical programming and stochastic programming models," Health Care Management Science, Springer, vol. 14(4), pages 361-369, November.


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