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Data Mining Analysis of Inpatient Fees in Hospital Information System

机译:医院信息系统住院费用数据挖掘分析

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Although data mining and knowledge discovery techniques have been used to clinical medicine frequently, little research has been conducted on hospital decision-making. Decision-making is a crucial part of hospital management, and it goes the whole process of medical behavior. Medical data in Hospital Information System is always complicated and especial, and this consequently aggravates burden on data analysis. In this paper, we explore how data mining and knowledge discovery can be applied to hospital management, and propose a modified data mining method that is appropriate for mass data in Hospital Information System. We first build a model based on inpatient fees theme, and then analyze it in three aspects: medical insurance fee, department annual fee and fee compositions. The knowledge discovery and analysis is based on Intersystem BI tool DeepSee.
机译:尽管数据挖掘和知识发现技术已被频繁地用于临床医学,但是关于医院决策的研究却很少。决策是医院管理的关键部分,它贯穿于医疗行为的全过程。医院信息系统中的医疗数据始终是复杂且特殊的,因此加重了数据分析的负担。在本文中,我们探索了如何将数据挖掘和知识发现应用于医院管理,并提出了一种适合医院信息系统中大量数据的改进的数据挖掘方法。我们首先基于住院费用主题构建模型,然后从三个方面进行分析:医疗保险费,部门年费和费用构成。知识发现和分析基于系统间BI工具DeepSee。

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