Risk mining in medicine: application of data mining to medical risk management

  • Authors:

  • Shusaku Tsumoto;Yuko Tsumoto;Kimiko Matsuoka;Shigeki Yokoyama

  • Affiliations:

  • Department of Medical Informatics, Shimane University, School of Medicine, Izumo, Japan;Department of Fundamental Nursing, Shimane University, School of Nursing, Izumo, Japan;Department of Fundamental Nursing, Shimane University, School of Nursing, Izumo, Japan;Osaka Prefectural General Hospital, Osaka, Japan

  • Venue:
  • WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
  • Year:
  • 2006

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Abstract

Organizations in our modern society grow larger and more complex to provide advanced services due to the varieties of social demands. Such organizations are highly efficient for routine work processes but known to be not robust to unexpected situations. According to this observation, the importance of the organizational risk management has been noticed in recent years. On the other hand, a large amount of data on the work processes has been automatically stored since information technology was introduced to the organizations. Thus, it has been expected that reuse of collected data should contribute to risk management for large-scale organizations. This paper proposes risk mining, where data mining techniques were applied to detection and analysis of risks potentially existing in the organizations and to usage of risk information for better organizational management. We applied this technique to the following three medical domains: risk aversion of nurse incidents, infection control and hospital management. The results show that data mining methods were effective to detection of risk factors.