An Intelligent Agent Solution for Improving the Efficiency of the Kidney Distribution Process

Abstract

Kidney transplantation is an effective treatment for renal disease that was previously fatal. However, the demand for donor kidneys far exceeds the supply. Due to the scarcity of volunteer donors, the cadaver organs that are retrieved must be optimally utilized. By expanding organ retrieval and sharing pools and improving donor-patient matching algorithms, the utilization of donated organs is enhanced and encouraging medical results are obtained. However, the benefits of enlarged donor and recipient pools may be offset by increasing complexity and decreasing efficiency in the organ distribution process thus increasing cold ischemia time. It is critical to improve distribution process efficiency in order to minimize the time taken to complete the entire process, and thus further enhance patient and graft survival. I attempt to apply supply chain management concepts, agent technologies, mobile communication technologies and decision-making theory to improve the efficiency of the cadaver kidney distribution process. In this thesis I analyze what are the bottlenecks in current cadaver kidney distribution and investigate how agent technology can be applied to improve this process. I propose a distributed multi-agent system operating in a mobile and wireless communication environment to assist transplant coordinators in coordinating with multi-parties in this time-critical distribution process. A prototype system has been developed to help transplanting coordinators in allocating the kidney recipient.