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Maximizing the Efficiency of the U.S. Liver Allocation System Through Region Design

Author

Listed:
  • Nan Kong

    () (Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907)

  • Andrew J. Schaefer

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

  • Brady Hunsaker

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

  • Mark S. Roberts

    () (Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15261)

Abstract

Cadaveric liver transplantation is the only viable therapy for end-stage liver disease patients without a living donor. However, this type of transplantation is hindered in the United States by donor scarcity and rapid viability decay. Given these difficulties, the current U.S. liver allocation policy balances allocation likelihood and geographic proximity by allocating cadaveric livers hierarchically. We consider the problem of maximizing the efficiency of intraregional transplants through the redesign of liver allocation regions. We formulate the problem as a set partitioning problem that clusters organ procurement organizations into regions. We develop an estimate of viability-adjusted intraregional transplants to capture the trade-off between large and small regions. We utilize branch and price because the set partitioning formulation includes too many potential regions to handle explicitly. We formulate the pricing problem as a mixed-integer program and design a geographic-decomposition heuristic to generate promising columns quickly. Because the optimal solution depends on the design of geographic decomposition, we develop an iterative procedure that integrates branch and price with local search to alleviate this dependency. Finally, we present computational studies that show the benefit of region redesign and the efficacy of our solution approach. Our carefully calibrated test instances can be solved within a reasonable amount of time, and the resulting region designs yield a noticeable improvement over the current configuration.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormnsc:v:56:y:2010:i:12:p:2111-2122
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    File URL: http://dx.doi.org/10.1287/mnsc.1100.1249
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Anuj Mehrotra & Ellis L. Johnson & George L. Nemhauser, 1998. "An Optimization Based Heuristic for Political Districting," Management Science, INFORMS, vol. 44(8), pages 1100-1114, August.
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    Cited by:

    1. Alumura, Sibel A. & Karab, Bahar Y. & Melo, M. Teresa, 2013. "Location and logistics," Technical Reports on Logistics of the Saarland Business School 5, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    2. n/a, 2012. "Commentaries to "The Vital Role of Operations Analysis in Improving Healthcare Delivery"," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 495-511, October.
    3. Zahiri, B. & Tavakkoli-Moghaddam, R. & Mohammadi, M. & Jula, P., 2014. "Multi-objective design of an organ transplant network under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 101-124.
    4. repec:eee:ejores:v:266:y:2018:i:2:p:652-662 is not listed on IDEAS

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