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

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.

[1]  Xuanming Su,et al.  Diminishing Significance of HLA Matching 
 in Kidney Transplantation , 2004, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

[2]  R. Tyrrell Rockafellar,et al.  Convex Analysis , 1970, Princeton Landmarks in Mathematics and Physics.

[3]  D. Howard,et al.  Why do transplant surgeons turn down organs? A model of the accept/reject decision. , 2002, Journal of health economics.

[4]  O. Hart Optimal Labour Contracts Under Asymmetric Information: An Introduction (Now published in Review of Economic Studies, (January 1983).) , 1982 .

[5]  Lawrence M. Wein,et al.  Dynamic Allocation of Kidneys to Candidates on the Transplant Waiting List , 2000, Oper. Res..

[6]  J. Mirrlees An Exploration in the Theory of Optimum Income Taxation an Exploration in the Theory of Optimum Income Taxation L Y 2 , 2022 .

[7]  C. Bryan,et al.  HLA Points Assigned in Cadaveric Kidney Allocation Should Be Revisited: An Analysis of HLA Class II Molecularly Typed Patients and Donors , 2003, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

[8]  David D. Yao,et al.  Multiclass Queueing Systems: Polymatroidal Structure and Optimal Scheduling Control , 1992, Oper. Res..

[9]  Theodore Groves,et al.  Incentives in Teams , 1973 .

[10]  Uri Yechiali,et al.  A Time-dependent Stopping Problem with Application to Live Organ Transplants , 1985, Oper. Res..

[11]  Uri Yechiali,et al.  Sequential Assignment Match Processes with Arrivals of Candidates and Offers , 1990, Probability in the Engineering and Informational Sciences.

[12]  J. Rochet,et al.  Ironing, Sweeping, and Multidimensional Screening , 1998 .

[13]  Jack Edmonds,et al.  Submodular Functions, Matroids, and Certain Polyhedra , 2001, Combinatorial Optimization.

[14]  C M Smith,et al.  Center-specific graft and patient survival rates: 1997 United Network for Organ Sharing (UNOS) report. , 1998, JAMA.

[15]  C. Goodman United Network for Organ Sharing , 1988 .

[16]  Jonathan Himmelfarb,et al.  Donor Kidney Exchanges , 2004, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

[17]  Stuart Boxerman,et al.  The expanded criterial donor dilemma in cadaveric renal transplantation , 2003, Transplantation.

[18]  Xuanming Su,et al.  Incorporating recipient choice in kidney transplantation. , 2004, Journal of the American Society of Nephrology : JASN.

[19]  Stefanos Zenios,et al.  Shared decision making in deceased-donor transplantation , 2006, The Lancet.

[20]  Maureen A. McBride,et al.  United Network for Organ Sharing Donor Data Update, 1988-1995. , 1997, Transplantation proceedings.

[21]  Xuanming Su,et al.  Patient Choice in Kidney Allocation: The Role of the Queueing Discipline , 2004, Manuf. Serv. Oper. Manag..

[22]  G Ardine de Wit,et al.  Health profiles and health preferences of dialysis patients. , 2002, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[23]  E. Maskin,et al.  Monopoly with Incomplete Information , 1984 .

[24]  D. Cox,et al.  Analysis of Survival Data. , 1986 .

[25]  Awi Federgruen,et al.  Characterization and Optimization of Achievable Performance in General Queueing Systems , 1988, Oper. Res..

[26]  Xuanming Su,et al.  Patient Choice in Kidney Allocation: A Sequential Stochastic Assignment Model , 2005, Oper. Res..

[27]  Stefanos A. Zenios,et al.  Modeling the transplant waiting list: A queueing model with reneging , 1999, Queueing Syst. Theory Appl..

[28]  Lutz Fritsche,et al.  Old‐for‐Old Kidney Allocation Allows Successful Expansion of the Donor and Recipient Pool , 2003, American Journal of Transplantation.

[29]  John Hornberger,et al.  Involving Patients in the Cadaveric Kidney Transplant Allocation Process: A Decision-Theoretic Perspective , 1996 .

[30]  R S Woodward,et al.  ECONOMIC COST OF EXPANDED CRITERIA DONORS IN CADAVERIC RENAL TRANSPLANTATION: ANALYSIS OF MEDICARE PAYMENTS1 , 2000, Transplantation.