Detecting Severe Incidents from Electronic Medical Records Using Machine Learning Methods.

Journal: Studies in health technology and informatics
Published Date: Jun 16, 2020

Abstract

The goal of this research was to design a solution to detect non-reported incidents, especially severe incidents. To achieve this goal, we proposed a method to process electronic medical records and automatically extract clinical notes describing severe incidents. To evaluate the proposed method, we implemented a system and used the system. The system successfully detected a non-reported incident to the safety management department.

Authors

  • Kazuya Okamoto
    Division of Medical Information Technology and Administration Planning, Kyoto University Hospital, Kyoto, Japan.
  • Takashi Yamamoto
    Patient Safety Unit, Kyoto University Hospital, Japan.
  • Shusuke Hiragi
    Graduate School of Informatics Kyoto University, Kyoto-City, Kyoto, Japan.
  • Shosuke Ohtera
    Graduate School of Informatics Kyoto University, Kyoto-City, Kyoto, Japan.
  • Osamu Sugiyama
    Preemptive Medicine and Lifestyle-related Disease Research Center, Kyoto University Hospital, Kyoto, Japan.
  • Goshiro Yamamoto
    Kyoto University Hospital, Kyoto-City, Kyoto, Japan.
  • Masahiro Hirose
    Faculty of Medicine, Shimane University, Japan.
  • Tomohiro Kuroda
    Division of Medical Information Technology and Administration Planning, Kyoto University Hospital, Kyoto, Japan.

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