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Using Markov Models for Decision Support in Management of High Occupancy Hospital Care

机译:使用马尔可夫模型进行高占用医院护理管理中的决策支持

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We have previously used Markov models to describe movements of patients between hospital states; these may be actual or virtual and described by a phase-type distribution. Here we extend this approach to a Markov reward model for a healthcare system with constant size. This corresponds to a situation where there is a waiting list of patients so that the total number of in-patients remains at a constant level and all admissions are from the waiting list. The distribution of costs is evaluated for any time and expressions derived for the mean cost. The approach is then illustrated by determining average cost at any time for a hospital system with two states: acute/rehabilitative and long-stay.
机译:我们以前使用过马尔可夫模型来描述医院患者的运动;这些可以是实际的或虚拟的,并通过相位类型分发描述。在这里,我们将这种方法扩展到Markov奖励模型,用于具有恒定大小的医疗保健系统。这对应于有患者等待列表的情况,以便患有患者的总数保持在持续水平,并且所有入学都来自等候名单。为均值的任何时间和表达评估成本的分布。然后通过在具有两个状态的医院系统的任何时间确定平均成本来说明该方法:急性/康复和长期留下。

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