Optimal cost adjustment for a selfish routing healthcare network.

Abstract

South Korea's large hospitals are severely burdened by patient congestion because patients throng to these places expecting to get treated better given their higher-quality healthcare. Effective cost management of the healthcare system is one way to reduce patient congestion in a large hospital. This study proposes methods that can help direct patient flows in a desirable direction and suggests ways to effectively manage the cost of healthcare. The study also discusses how selfish patients act in ways that maximize their benefits by choosing a specific hospital and in turn forcing the hospital and the healthcare network to bear more costs than is necessary. The study proposes a model describing the need for intervention from the government to control the cost escalation resulting from selfish routing. The study proposes two heuristic algorithms to solve the suggested model. The flow-based algorithm addresses the target quantum of flows, and the utility-based algorithm targets the value of cost functions. Performances of heuristics are evaluated through numerical experiments. The utility-based algorithm yields higher values for objectives, while the flow-based algorithm controls the extent of investment. A case study based on data from the Seoul city database is also analyzed. The cost adjustment policy is compared with simple, uniformly improved network policies, and findings show that such policies have the strength needed to improve the cost-effectiveness of the healthcare system if implemented fully and effectively.