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Mining Information Dependency in Outpatient Encounters for Chronic Disease Care

机译:用于慢性病护理的门诊遭遇的挖掘信息依赖

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Chronic disease care, e.g., care of type 2 diabetes mellitus, is a long-term, complex process involving collaboration and coordination among multiple healthcare providers. To facilitate and accelerate the process, it is key to understand the information flow and identify the information dependency (e.g., temporal dependency of co-occurrence and sequential occurrence) during care provision, which is also the objective of this work. Since most health interventions and decisions are made in outpatient encounters for chronic patients, in this paper, we propose an approach to mine temporal information dependency in outpatient encounter records using sequential pattern mining techniques. By exploring the real data of over 10,000 type 2 diabetes patients from three hospitals, the proposed approach effectively works out sets of meaningful information dependency patterns for different patient groups. The discovered information dependency can be used to guide the information sharing between different health providers, and optimize the chronic disease care coordination.
机译:慢性病护理,例如,护理2型糖尿病,是一个长期的复杂过程,涉及多个医疗保健提供者之间的合作和协调。为了促进和加速过程,它是了解信息流的关键,并在护理条款期间识别信息依赖性(例如,共同发生和顺序发生的时间依赖性),这也是这项工作的目标。由于大多数健康干预和决策都是在慢性患者的门诊遭遇中所做的,因此,在本文中,我们提出了一种使用顺序模式采矿技术在门诊遇到记录中挖掘时间信息依赖性的方法。通过探索来自三家医院的10,000型糖尿病患者的真实数据,所提出的方法有效地为不同患者组提供了有意义的信息依赖模式。发现的信息依赖项可用于指导不同健康提供者之间的信息共享,并优化慢性病护理协调。

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