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Distributionally robust chance-constrained program surgery planning with downstream resource

机译:具有下游资源的分布鲁棒的机会受限程序手术计划

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Operation room (OR) is one of the key service resources in healthcare resources and plays an important hub role in hospital operation management. We study surgery planning on a given planning period and take service time uncertainty and downstream resource requirements into consideration. Based on the mean and covariance of service time distribution, we develop a distributionally robust chance-constrained programming framework that minimizes operating costs, allocation costs and peak demand of hospital beds under OR capacity constraints. Decisions including which operating rooms to open, allocation of surgeries to ORs on a given planning period. Mathematically, the proposed model can be reformulated as a tractable second order cone programming (SCOP). Finally, we collect real data from public hospital in Beijing and test the proposed framework to explore some managerial insights for hospitals.
机译:手术室(OR)是医疗资源中的关键服务资源之一,在医院运营管理中起着重要的枢纽作用。我们在给定的计划周期内研究手术计划,并考虑服务时间的不确定性和下游资源需求。基于服务时间分配的均值和协方差,我们开发了一种分布稳定的机会受限的编程框架,该框架在OR能力约束下将运营成本,分配成本和医院病床高峰需求最小化。决定包括打开哪个手术室,在给定的计划周期内将手术分配给手术室。从数学上讲,可以将所提出的模型重新表述为易于处理的二阶锥规划(SCOP)。最后,我们从北京公立医院收集真实数据,并测试提出的框架,以探索对医院的管理见解。

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