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Optimal cost adjustment for a selfish routing healthcare network

机译:自私路由医疗网络的最佳成本调整

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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.
机译:韩国的大型医院因患者拥挤而承受着沉重的负担,因为患者蜂拥到这些地方,希望得到更好的治疗,因为他们的医疗质量更高。医疗系统的有效成本管理是减少大型医院患者拥挤的一种方法。这项研究提出了一些方法,可以帮助引导患者流向理想的方向,并提出了有效管理医疗成本的方法。该研究还讨论了自私的患者如何通过选择特定的医院,进而迫使医院和医疗保健网络承担超出必要的成本,从而实现利益最大化。该研究提出了一个模型,描述了政府干预的必要性,以控制自私路由导致的成本上升。本研究提出了两种启发式算法来求解该模型。基于流的算法处理流的目标量,基于效用的算法以成本函数的值为目标。通过数值实验评估了启发式算法的性能。基于效用的算法为目标生成更高的值,而基于流的算法控制投资范围。本文还分析了基于首尔市数据库数据的案例研究。成本调整政策与简单、统一改进的网络政策进行了比较,结果表明,如果全面有效地实施,这些政策具有提高医疗系统成本效益所需的力量。

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