IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v52y2006i11p1647-1660.html
   My bibliography  Save this article

Recipient Choice Can Address the Efficiency-Equity Trade-off in Kidney Transplantation: A Mechanism Design Model

Author

Listed:
  • Xuanming Su

    (Haas School of Business, University of California, Berkeley, California 94720)

  • Stefanos A. Zenios

    (Graduate School of Business, Stanford University, Stanford, California 94305)

Abstract

In kidney allocation, transplant candidates may have private information about their propensity to enjoy good outcomes after transplantation or about their relative expected improvement in quality of life after transplantation. This paper develops a mechanism design model to investigate the effect of such information asymmetry on the kidney allocation system. In this model, there are n transplant queues corresponding to n candidate types. Candidate types are only observed by the candidates, and each candidate chooses the queue to join by reporting a type. Kidneys have heterogeneous types, and each kidney will be assigned to one of the queues depending on its type. Candidates report their type strategically to join the queue that maximizes their utility. Candidate utility depends on the type of kidney received and the expected waiting time, which is calculated using fluid approximations. We consider two alternative social welfare functions: aggregate utility (emphasizing efficiency) and minimum utility across all candidates (emphasizing equity). The kidney allocation problem is to divide the organ supply among the different queues so that social welfare is maximized, and this problem is solved explicitly under both objective functions. There are three findings: (1) The allocation mechanism induces truth telling by ensuring that candidates who wait longer receive better kidneys; (2) Information rents are earned by high-risk candidates under the efficiency objective and by low-risk candidates under the equity objective; (3) a choice-based kidney allocation system in which candidates choose the type of queue to join leads to outcomes in the middle of the efficiency-equity spectrum.

Suggested Citation

  • Xuanming Su & Stefanos A. Zenios, 2006. "Recipient Choice Can Address the Efficiency-Equity Trade-off in Kidney Transplantation: A Mechanism Design Model," Management Science, INFORMS, vol. 52(11), pages 1647-1660, November.
    • Handle: RePEc:inm:ormnsc:v:52:y:2006:i:11:p:1647-1660
    DOI: 10.1287/mnsc.1060.0541
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.1060.0541
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.1060.0541?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stefanos A. Zenios & Glenn M. Chertow & Lawrence M. Wein, 2000. "Dynamic Allocation of Kidneys to Candidates on the Transplant Waiting List," Operations Research, INFORMS, vol. 48(4), pages 549-569, August.
    2. Xuanming Su & Stefanos Zenios, 2004. "Patient Choice in Kidney Allocation: The Role of the Queueing Discipline," Manufacturing & Service Operations Management, INFORMS, vol. 6(4), pages 280-301, June.
    3. Xuanming Su & Stefanos A. Zenios, 2005. "Patient Choice in Kidney Allocation: A Sequential Stochastic Assignment Model," Operations Research, INFORMS, vol. 53(3), pages 443-455, June.
    4. Israel David & Uri Yechiali, 1985. "A Time-dependent Stopping Problem with Application to Live Organ Transplants," Operations Research, INFORMS, vol. 33(3), pages 491-504, June.
    5. 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.
    6. Jean-Charles Rochet & Philippe Chone, 1998. "Ironing, Sweeping, and Multidimensional Screening," Econometrica, Econometric Society, vol. 66(4), pages 783-826, July.
    7. Eric Maskin & John Riley, 1984. "Monopoly with Incomplete Information," RAND Journal of Economics, The RAND Corporation, vol. 15(2), pages 171-196, Summer.
    8. 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.
    9. Oliver D. Hart, 1983. "Optimal Labour Contracts under Asymmetric Information: An Introduction," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(1), pages 3-35.
    10. J. George Shanthikumar & David D. Yao, 1992. "Multiclass Queueing Systems: Polymatroidal Structure and Optimal Scheduling Control," Operations Research, INFORMS, vol. 40(3-supplem), pages 293-299, June.
    11. Groves, Theodore, 1973. "Incentives in Teams," Econometrica, Econometric Society, vol. 41(4), pages 617-631, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Sakine Batun & Andrew J. Schaefer & Atul Bhandari & Mark S. Roberts, 2018. "Optimal Liver Acceptance for Risk-Sensitive Patients," Service Science, INFORMS, vol. 10(3), pages 320-333, September.
    4. Dimitris Bertsimas & Vivek F. Farias & Nikolaos Trichakis, 2013. "Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation," Operations Research, INFORMS, vol. 61(1), pages 73-87, February.
    5. Oguzhan Alagoz & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2007. "Determining the Acceptance of Cadaveric Livers Using an Implicit Model of the Waiting List," Operations Research, INFORMS, vol. 55(1), pages 24-36, February.
    6. 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.
    7. Zahra Gharibi & Michael Hahsler, 2021. "A Simulation-Based Optimization Model to Study the Impact of Multiple-Region Listing and Information Sharing on Kidney Transplant Outcomes," IJERPH, MDPI, vol. 18(3), pages 1-20, January.
    8. Kargar, Bahareh & Pishvaee, Mir Saman & Jahani, Hamed & Sheu, Jiuh-Biing, 2020. "Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    9. Barış Ata & Anton Skaro & Sridhar Tayur, 2017. "OrganJet: Overcoming Geographical Disparities in Access to Deceased Donor Kidneys in the United States," Management Science, INFORMS, vol. 63(9), pages 2776-2794, September.
    10. 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.
    11. Sahar Ahmadvand & Mir Saman Pishvaee, 2018. "An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach," Health Care Management Science, Springer, vol. 21(4), pages 587-603, December.
    12. 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.
    13. 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.
    14. Sang-Phil Kim & Diwakar Gupta & Ajay Israni & Bertram Kasiske, 2015. "Accept/decline decision module for the liver simulated allocation model," Health Care Management Science, Springer, vol. 18(1), pages 35-57, March.
    15. 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.
    16. Baris Ata & Yichuan Ding & Stefanos Zenios, 2021. "An Achievable-Region-Based Approach for Kidney Allocation Policy Design with Endogenous Patient Choice," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 36-54, 1-2.
    17. Levy, Amnon, 2005. "A decision-rule for transplanting non-cadaveric organs," European Journal of Operational Research, Elsevier, vol. 164(2), pages 548-554, July.
    18. 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.
    19. Can Zhang & Atalay Atasu & Turgay Ayer & L. Beril Toktay, 2020. "Truthful Mechanisms for Medical Surplus Product Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 735-753, July.
    20. Francis Bloch & David Cantala, 2017. "Dynamic Assignment of Objects to Queuing Agents," American Economic Journal: Microeconomics, American Economic Association, vol. 9(1), pages 88-122, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:52:y:2006:i:11:p:1647-1660. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.