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Data mining analysis of inpatient fees in Hospital Information System

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7 Author(s)
Yu Hai-yan ; Healthcare Inf. Eng. Res. Center, Zhejiang Univ., Hangzhou, China ; Li Jing-song ; Han Xiong ; Hu Zhen
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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.

Published in:

IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on  (Volume:1 )

Date of Conference:

14-16 Aug. 2009