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Kidney exchange simulation and optimization

Author

Listed:
  • Nicolau Santos

    (INESC TEC)

  • Paolo Tubertini

    (DEI - Università di Bologna)

  • Ana Viana

    (INESC TEC
    Instituto Superior de Engenharia - Instituto Politécnico do Porto)

  • João Pedro Pedroso

    (INESC TEC
    Universidade do Porto - Faculdade de Ciências)

Abstract

One of the challenges in a kidney exchange program (KEP) is to choose policies that ensure an effective and fair management of all participating patients. In order to understand the implications of different policies of patient allocation and pool management, decision makers should be supported by a simulation tool capable of tackling realistic exchange pools and modeling their dynamic behavior. In this paper, we propose a KEP simulator that takes into consideration the wide typology of actors found in practice (incompatible pairs, altruistic donors, and compatible pairs) and handles different matching policies. Additionally, it includes the possibility of evaluating the impact of positive crossmatch of a selected transplant, and of dropouts, in a dynamic environment. Results are compared to those obtained with a complete information model, with knowledge of future events, which provides an upper bound to the objective values. Final results show that shorter time intervals between matches lead to higher number of effective transplants and to shorter waiting times for patients. Furthermore, the inclusion of compatible pairs is essential to match pairs of specific patient–donor blood type. In particular, O-blood type patients benefit greatly from this inclusion.

Suggested Citation

  • Nicolau Santos & Paolo Tubertini & Ana Viana & João Pedro Pedroso, 2017. "Kidney exchange simulation and optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1521-1532, December.
  • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:12:d:10.1057_s41274-016-0174-3
    DOI: 10.1057/s41274-016-0174-3
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    References listed on IDEAS

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    1. Constantino, Miguel & Klimentova, Xenia & Viana, Ana & Rais, Abdur, 2013. "New insights on integer-programming models for the kidney exchange problem," European Journal of Operational Research, Elsevier, vol. 231(1), pages 57-68.
    2. M. Beccuti & V. Fragnelli & G. Franceschinis & S. Villa, 2011. "Dynamic Simulations of Kidney Exchanges," Operations Research Proceedings, in: Bo Hu & Karl Morasch & Stefan Pickl & Markus Siegle (ed.), Operations Research Proceedings 2010, pages 539-544, Springer.
    3. Tayfun Sönmez & Alvin E. Roth & M. Utku Ünver, 2007. "Efficient Kidney Exchange: Coincidence of Wants in Markets with Compatibility-Based Preferences," American Economic Review, American Economic Association, vol. 97(3), pages 828-851, June.
    4. Roth, Alvin E. & Sonmez, Tayfun & Utku Unver, M., 2005. "Pairwise kidney exchange," Journal of Economic Theory, Elsevier, vol. 125(2), pages 151-188, December.
    5. Kristiaan M. Glorie & J. Joris van de Klundert & Albert P. M. Wagelmans, 2014. "Kidney Exchange with Long Chains: An Efficient Pricing Algorithm for Clearing Barter Exchanges with Branch-and-Price," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 498-512, October.
    6. Saidman, Susan L. & Roth, Alvin E. & Sonmez, Tayfun & Unver, M. Utku & Delmonico, Francis L., 2014. "Increasing the Opportunity of Live Kidney Donation by Matching for Two and Three Way Exchanges," MPRA Paper 58247, University Library of Munich, Germany.
    7. Glorie, K.M., 2012. "Estimating the probability of positive crossmatch after negative virtual crossmatch," Econometric Institute Research Papers EI 2012-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    Cited by:

    1. Péter Biró & Flip Klijn & Xenia Klimentova & Ana Viana, 2021. "Shapley-Scarf Housing Markets: Respecting Improvement, Integer Programming, and Kidney Exchange," Working Papers 1235, Barcelona School of Economics.
    2. Itai Ashlagi & Alvin E. Roth, 2021. "Kidney Exchange: An Operations Perspective," Management Science, INFORMS, vol. 67(9), pages 5455-5478, September.
    3. Klimentova, Xenia & Viana, Ana & Pedroso, João Pedro & Santos, Nicolau, 2021. "Fairness models for multi-agent kidney exchange programmes," Omega, Elsevier, vol. 102(C).
    4. Katarína Cechlárová & Martina Hančová & Diana Plačková & Tatiana Baltesová, 2021. "Stochastic modelling and simulation of a kidney transplant waiting list," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 909-931, September.
    5. Klimentova, Xenia & Biró, Péter & Viana, Ana & Costa, Virginia & Pedroso, João Pedro, 2023. "Novel integer programming models for the stable kidney exchange problem," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1391-1407.
    6. Radu-Stefan Mincu & Péter Biró & Márton Gyetvai & Alexandru Popa & Utkarsh Verma, 2021. "IP solutions for international kidney exchange programmes," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 403-423, June.
    7. Tiago Monteiro & Xenia Klimentova & João Pedro Pedroso & Ana Viana, 2021. "A comparison of matching algorithms for kidney exchange programs addressing waiting time," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 539-552, June.
    8. Kevin Leyton-Brown & Paul Milgrom & Neil Newman & Ilya Segal, 2023. "Artificial Intelligence and Market Design: Lessons Learned from Radio Spectrum Reallocation," NBER Chapters, in: New Directions in Market Design, National Bureau of Economic Research, Inc.

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