Risk Mining: Mining Nurses’ Incident Factors and Application of Mining Results to Prevention of Incidents

  • Shusaku Tsumoto
  • Kimiko Matsuoka
  • Shigeki Yokoyama
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4259)


To err is human. How can we avoid near misses and achieve medical safety? From this perspective, we analyzed the nurses’ incident data by data mining with the ”concept of quality control” that near misses are produced by the system rather than individuals. Nurses’ incident data were collected during the 18 months at the emergency room. Significant rules (If-then rules) indicated that the medication errors are likely to occur when mental concentration is disrupted by interruption of work, etc. Based on the results of the analysis, the nurses’ medication check system was improved. During the last 6 months, the check system was put into effect. The frequency of the medication errors decreased to about one-twenties or less. It was considered that the data mining analysis contributes the decision support on the improvement of incidents.


Medication Error Domain Expert Risk Information Hospital Information System Incident Report 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shusaku Tsumoto
    • 1
  • Kimiko Matsuoka
    • 2
  • Shigeki Yokoyama
    • 3
  1. 1.Department of Medical InformaticsShimane University, School of MedicineIzumoJapan
  2. 2.Osaka Prefectural General HospitalOsakaJapan
  3. 3.Department of Medical InformationKoden IndustryTokyoJapan

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