Kidney exchange in dynamic sparse heterogenous pools

Ashlagi, Itai; Jaillet, Patrick; Manshadi, Vahideh

doi:10.1145/2492002.2482565

Cited by 28 publications

(17 citation statements)

References 16 publications

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“…2. Some recent theoretical work looks at kidney exchange graphs without blood types but with increasing sparsity (in the size of the pool) for highly-sensitized candidates [4,5]. For these experiments, the probability of an incoming edge to a highlysensitized pair is O(1/n).…”

Section: Simulated Results From Random Graphsmentioning

confidence: 99%

“…Both the theoretical and experimental sides of utilitarian dynamic kidney exchange are active and important areas of research [2,5,7,13,27]. Developing accurate models and scalable algorithms that consider the price of fairness in the dynamic setting will be of increasing importance as fielded kidney exchanges move from static to dynamic matching.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

“…They provide a wealth of opportunities for theoretical and experimental research in both fields. For instance, key questions in practically tractable clearing algorithms [7,13,14,15] and mechanism design [3,5,6,11] remain unsolved. Advances in these areas will benefit the greater artificial intelligence community immensely, and provide valuable experience in fielding real-world artificial intelligence technology.…”

Section: Introductionmentioning

confidence: 99%

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Price of Fairness in Kidney Exchange.

2014

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Kidney exchange provides a life-saving alternative to long waiting lists for patients in need of a new kidney. Fielded exchanges typically match under utilitarian or near-utilitarian rules; this approach marginalizes certain classes of patients. In this paper, we focus on improving access to kidneys for highly-sensitized, or hard-tomatch, patients. Toward this end, we formally adapt a recently introduced measure of the tradeoff between fairness and efficiencythe price of fairness-to the standard kidney exchange model. We show that the price of fairness in the standard theoretical model is small. We then introduce two natural definitions of fairness and empirically explore the tradeoff between matching more hard-tomatch patients and the overall utility of a utilitarian matching, on real data from the UNOS nationwide kidney exchange and simulated data from each of the standard kidney exchange distributions.

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Section: Simulated Results From Random Graphsmentioning

confidence: 99%

Section: Conclusion and Future Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Price of Fairness in Kidney Exchange.

2014

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“…In the Operations Research and Computer Science literatures, dynamic kidney matching has been extensively studied, see e.g., [Zen02,SZ05,AS09,DPS12]. Perhaps most related to our work is that of Ashlagi, Jaillet, and Manshadi [AJM13] who construct a discrete-time finite-horizon model of dynamic kidney exchange. In their model, one new agent arrives at the pool at each period, but, unlike our model, agents who are in the pool neither perish, nor bear any waiting cost.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Matching Market Design

Akbarpour

Gharan

2014

SSRN Journal

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We introduce a simple benchmark model of dynamic matching in networked markets, where agents arrive and depart stochastically and the network of acceptable transactions among agents forms a random graph. We analyze our model from three perspectives: waiting, optimization, and information. The main insight of our analysis is that waiting to thicken the market can be substantially more important than increasing the speed of transactions, and this is quite robust to the presence of waiting costs. From an optimization perspective, naïve local algorithms, that choose the right time to match agents but do not exploit global network structure, can perform very close to optimal algorithms. From an information perspective, algorithms that employ even partial information on agents' departure times perform substantially better than those that lack such information. To elicit agents' departure times, we design an incentive-compatible continuous-time dynamic mechanism without transfers.Keywords: Market Design, Matching, Networks, Continuous-time Markov Chains, Mechanism Design JEL Classification Numbers: D47, C78, C60 * We thank Paul Milgrom and Alvin Roth for valuable comments and suggestions. We also thank Itai Ashlagi, Timothy Bresnahan, Gabriel Carroll, Fuhito Kojima, Matthew Jackson, Muriel Niederle, Afshin Nikzad, Malwina Luczak, Michael Ostrovsky, Bob Wilson, and Alex Wolitzky for their valuable comments, as well as several seminar participants for helpful suggestions. All errors remain our own.

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“…That is, because many patients are highly sensitized, they have few in-edges in the resulting compatibility graph, and are consequently included in very few short cycles. As mentioned above, Ashlagi et al (2013b) have further explained analytically the importance of long chains.…”

Section: The Power Of Long Chains Mystery Explainedmentioning

confidence: 85%

Kidney Exchange and the Alliance for Paired Donation: Operations Research Changes the Way Kidneys Are Transplanted

et al. 2015

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Many end-stage renal disease sufferers who require a kidney transplant to prolong their lives have relatives or associates who have volunteered to donate a kidney to them, but whose kidney is incompatible with their intended recipient. This incompatibility can be sometimes overcome by exchanging kidneys with another incompatible donor pair. Such kidney exchanges have emerged as a standard mode of kidney transplantation in the United States. The Alliance for Paired Donation (APD) developed and implemented an innovative operations research based methodology of non-simultaneous extended altruistic donor (NEAD) chains, which, by allowing a previously binding constraint (of simultaneity) to be relaxed, allowed better optimized matching of potential donors to patients, which greatly increases the number of possible transplants. Since 2006, the APD has saved more than 220 lives through its kidney exchange program, with more than 75% of these achieved through long non-simultaneous chains. The technology and methods pioneered by APD have been adopted by other transplant exchanges, resulting in thousands of lives already saved, with the promise of increasing impact in coming years. The percentage of transplants from non-simultaneous chains has already reached more than 6% of the total number of transplants from live donors (including directed living donors) in the last year. We describe the long-term optimization and market design research that supports this innovation. We also describe how the team of physicians and operations researchers worked to overcome the skepticism and resistance of the medical community to the NEAD innovation.

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Kidney exchange in dynamic sparse heterogenous pools

Cited by 28 publications

References 16 publications

Price of Fairness in Kidney Exchange.

Price of Fairness in Kidney Exchange.

Dynamic Matching Market Design

Kidney Exchange and the Alliance for Paired Donation: Operations Research Changes the Way Kidneys Are Transplanted

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