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Real time access control of patient service in the pediatrics department

机译:儿科患者服务的实时访问控制

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Motivated by patients' increasing demand and inevitable uncomfortable waiting for the scarce healthcare service, we develop a real-time automatic appointment scheduling (AS) policy considering both the difference and fairness among heterogeneous types of patients. This paper discusses the AS system based on the assumption of independent but non-identical patient arrivials with independent and identically distributed random service durations. The AS policy chooses the patient for the next diagnosis from the waiting pool automatically to minimize the expected total “disutility” according to the current system state. We construct a continuous-time Markov Decision Process (MDP) in a finite horizon to formulate the AS system. Through mathematical analysis the myopic optimal policy and a “switching-curve” are derived in this paper. In the numerical experiment, a case based on the Pediatric clinic of the Peking University Third Hospital (PUTH) is investigated by constructing a simulation model of the AS system. Three heuristic policies along with the myopic policy are testified in both the Markovian settings and the real-world scenario. Our simulation results confirm the effectiveness of the myopic policy that the total “disutility” of patients can be greatly alleviated.
机译:由于患者需求的增长以及不可避免地等待稀缺的医疗服务,我们考虑到不同类型患者之间的差异和公平性,开发了一种实时自动预约计划(AS)策略。本文讨论了基于独立但不相同的患者到达的假设,并具有独立且均等分布的随机服务时间的AS系统。 AS策略会根据当前系统状态自动从等待池中选择患者进行下一次诊断,以最大程度地减少预期的总“功用”。我们在有限的范围内构造一个连续时间的马尔可夫决策过程(MDP),以制定AS系统。通过数学分析,得出了近视最优策略和“切换曲线”。在数值实验中,通过构建AS系统的仿真模型,以北京大学第三医院儿科门诊为例。在马尔可夫环境和实际场景中都证明了三种启发式策略以及近视策略。我们的模拟结果证实了近视策略的有效性,即可以大大减轻患者的总“无用”。

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