DocumentCode
174893
Title
Enhancing Patient Safety through Human-Computer Information Retrieval on the Example of German-Speaking Surgical Reports
Author
Stocker, Christian ; Marzi, Leopold-Michael ; Matula, Christian ; Schantl, Johannes ; Prohaska, Gottfried ; Brabenetz, Aberto ; Holzinger, Andreas
Author_Institution
Res. Unit Human-Comput. Interaction Inst. for Med. Inf., Med. Univ. Graz, Graz, Austria
fYear
2014
fDate
1-5 Sept. 2014
Firstpage
216
Lastpage
220
Abstract
In view of the high number of deaths and complication rates of major surgical procedures worldwide, surgical safety is described as a substantial global public-health concern. Naturally, patient safety has become an international priority. The increasing amount of electronically available clinical documents holds great potential for the computational analysis of large repositories. However, most of this data is in textual form and the clinical domain is a challenging field for the appliance of natural language processing. This is particularly the case if you deal with a language other than English, due to the little attention from the international research community. In this project, we are concerned with the utilization of a Germanspeaking operative report repository for the purpose of risk management and patient safety research. In this particular paper we focus on the description of our information retrieval approach. We investigated the thought process of a domain expert in order to derive his information of interest and describe a facet-based way to navigate this kind of information in the form of extracted phrases. Initial results and feedback has been very promising, but a formal evaluation is still missing.
Keywords
human computer interaction; information retrieval; medical information systems; natural language processing; surgery; English language; German-speaking operative surgical report repository; clinical domain expert; computational analysis; electronically available clinical documents; facet-based method; global public-health concern; human-computer information retrieval; information retrieval approach; natural language processing; patient safety enhancement; patient safety research; risk management; surgical procedures; surgical safety; textual data; Data mining; Informatics; Information retrieval; Natural language processing; Risk management; Safety; Surgery; Content Analytics; Knowledge Discovery; Text Mining; natural language processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Database and Expert Systems Applications (DEXA), 2014 25th International Workshop on
Conference_Location
Munich
ISSN
1529-4188
Print_ISBN
978-1-4799-5721-7
Type
conf
DOI
10.1109/DEXA.2014.53
Filename
6974852
Link To Document