Automatic Analysis of Critical Incident Reports: Requirements and Use Cases

被引:9
作者
Denecke, Kerstin [1 ]
机构
[1] Bern Univ Appl Sci, Bern, Switzerland
来源
HEALTH INFORMATICS MEETS EHEALTH | 2016年 / 223卷
关键词
Data mining; Critical incidents reporting; Natural language processing; BIOMEDICAL TEXT; SYSTEM;
D O I
10.3233/978-1-61499-645-3-85
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Increasingly, critical incident reports are used as a means to increase patient safety and quality of care. The entire potential of these sources of experiential knowledge remains often unconsidered since retrieval and analysis is difficult and time-consuming, and the reporting systems often do not provide support for these tasks. The objective of this paper is to identify potential use cases for automatic methods that analyse critical incident reports. In more detail, we will describe how faceted search could offer an intuitive retrieval of critical incident reports and how text mining could support in analysing relations among events. To realise an automated analysis, natural language processing needs to be applied. Therefore, we analyse the language of critical incident reports and derive requirements towards automatic processing methods. We learned that there is a huge potential for an automatic analysis of incident reports, but there are still challenges to be solved.
引用
收藏
页码:85 / 92
页数:8
相关论文
共 12 条
  • [1] Aronson AR, 2001, J AM MED INFORM ASSN, P17
  • [2] A survey of current work in biomedical text mining
    Cohen, AM
    Hersh, WR
    [J]. BRIEFINGS IN BIOINFORMATICS, 2005, 6 (01) : 57 - 71
  • [3] Semantic Structuring of and Information Extraction from Medical Documents Using the UMLS
    Denecke, K.
    [J]. METHODS OF INFORMATION IN MEDICINE, 2008, 47 (05) : 425 - 434
  • [4] Sentiment analysis in medical settings: New opportunities and challenges
    Denecke, Kerstin
    Deng, Yihan
    [J]. ARTIFICIAL INTELLIGENCE IN MEDICINE, 2015, 64 (01) : 17 - 27
  • [5] Natural language processing: State of the art and prospects for significant progress, a workshop sponsored by the National Library of Medicine
    Friedman, Carol
    Rindflesch, Thomas C.
    Corn, Milton
    [J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2013, 46 (05) : 765 - 773
  • [6] Linguistic Analysis of Large-Scale Medical Incident Reports for Patient Safety
    Fujita, Katsuhide
    Akiyama, Masanori
    Park, Keunsik
    Yamaguchi, Etsuko
    Furukawa, Hiroyuki
    [J]. QUALITY OF LIFE THROUGH QUALITY OF INFORMATION, 2012, 180 : 250 - 254
  • [7] Application of data mining to the identification of critical factors in patient falls using a web-based reporting system
    Lee, Ting-Ting
    Liu, Chieh-Yu
    Kuo, Ya-Hui
    Mills, Mary Etta
    Fong, Jian-Guo
    Hung, Cheyu
    [J]. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2011, 80 (02) : 141 - 150
  • [8] Automated categorisation of clinical incident reports using statistical text classification
    Ong, Mei-Sing
    Magrabi, Farah
    Coiera, Enrico
    [J]. QUALITY & SAFETY IN HEALTH CARE, 2010, 19 (06): : e55
  • [9] Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications
    Savova, Guergana K.
    Masanz, James J.
    Ogren, Philip V.
    Zheng, Jiaping
    Sohn, Sunghwan
    Kipper-Schuler, Karin C.
    Chute, Christopher G.
    [J]. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2010, 17 (05) : 507 - 513
  • [10] The anaesthesia critical incident reporting system: an experience based database
    Staender, S
    Davies, J
    Helmreich, B
    Sexton, B
    Kaufmann, M
    [J]. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 1997, 47 (1-2) : 87 - 90