JDR Vol.5 No.6 pp. 697-705
doi: 10.20965/jdr.2010.p0697


Risk Management for Hospitals Using the Incident Report

Yurie Takeda*1, Mitsuhiro Higashida*2, Yoshimasa Nagao*3, Manabu Yotsubashi*4, Shosuke Sato*1, and Haruo Hayashi*5

*1Graduate School of Informatics, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan

*2NTT Service Integration Laboratories, 3-9-11 Midori-cho, Musashino-Shi, Tokyo, Japan

*3Patient Safety Division, Kyoto University Hospital, 54 Shogoin, Kawahara-Cho, Sakyo-Ku, Kyoto-Shi, Kyoto, Japan

*4NTT Data Kansai Corporation, 3-3-20 Umeda, Kita-Ku, Osaka-Shi, Osaka, Japan

*5Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan

August 12, 2010
November 25, 2010
December 1, 2010
risk management, incident report, patient safety, cloud computing

Since medical service risk management has been recognized as vital to improving medical service quality and safety, the problem has been actively tackled. Medical institution incident reports describe accidents occursin daily medical services, but descriptions largely in text make it difficult to collect and editing such reports and medical institutions cannot currently share such reports. To solve the text-related problem, we propose test analysis and to enable sharing, we propose using software as a service (SaaS), also known as software on demand.

Cite this article as:
Yurie Takeda, Mitsuhiro Higashida, Yoshimasa Nagao, Manabu Yotsubashi, Shosuke Sato, and Haruo Hayashi, “Risk Management for Hospitals Using the Incident Report,” J. Disaster Res., Vol.5, No.6, pp. 697-705, 2010.
Data files:
  1. [1] Ministry of Health, Labour and Welfare, “operate project of network condition for measure for patient safety, 2001,
  2. [2] Department of Service promotion Office of Metropolitan Hospital Management, “The count complete of accidents and incidents in metropolitan hospital,” 2002,
  3. [3] Yoshikazu Asada, Taro Kanno and Kazuo Furuta European Safety and Reliability Conf., “Development of incident report analysis system based on m-SHEL ontology,” (ESREL), 2008.
  4. [4] T. Okabe,T. Yoshikawa, and T. Furuhashi, “A Proposal of Analysis System for Medical Incident Reports using Metadata and Cooccurrence Information,” Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol.18, No.5, pp. 689-700.
  5. [5] Y. Ootake, “Research for knowledge extraction from freedescription incident report,” Department of Electrical and Electronic Engineering, Mie University, pp. 1-48, 2007,
  6. [6] T. Terashita, T. Tanikawa, A. Endoh, K. Sumiyoshi, M. Hirota, K. Ogasawara, Y. Fukushima, R. Kawano, T. Sakurai, and H. Katoh, “A trial of the attribution analysis of the incident reports using data mining techniques,” the 24th Joint Conference on Medical Informatics, pp. 644-645, 2004.
  7. [7] S. Sato, H. Hayashi, N. Maki, and M. Inobuchi, “The Development of an Algorithm Using the TFIDF / TF Index to Extract Automatically the Set of Keywords of Corpus about Fields Related to Emergency Management –A Case Study Utilizing Web News Articles for the 2004 Niigata-Ken-Chuetsu Earthquake Disaster–,” Institute of Social Safety Science, No.8, pp. 367-376, 2006.
  8. [8] S. Sato, H. Hayashi, N. Maki, and M. Inoguchi, “The External Validity of an Algorithm Using TFIDF to Extract the Set of Keywords of Corpus about Disasters and Crises,” Institute of Social Safety Science, No.9, pp. 65-74, 2007.
  9. [9] M. Degawa, “Reportage medical accident,” Asahi Shimbun Publications Inc., pp. 51-52, 2009.
  10. [10] Asahi Shimbun, “‘find out’ Decade of Patient safety,” No.8, Feb. 4, 2009 (morning edition).
  11. [11] The Japan Council for Quality Health Care Division of Adverse Event Prevention, “Absolute of project of medical accident information,” 2008,

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 05, 2021