Patient Journey Optimization using a Multi-agent Approach

With the increasing expectation from patients and the regulations enacted by the government, exploring ways to shorten patient journey has caught increasing attention. Patient journey optimization typically involves treatment operation scheduling at multiple medical units. The decentralized nature of the problem makes conventional centralized operation research methods inapplicable in general and motivates the use of the multi-agent approach. In this paper, we focus on cancer patient treatment. We model patients and medical units as autonomous agents which interact locally via a bidding process and a coordination process for patient journey optimization. With reference to a dataset containing more than five thousand different cancer patient journeys, the effectiveness of the proposed algorithm under different settings of implementation has been experimentally evaluated via experimental simulations.