Open AccessInformation Logistics Solutions in Healthcare: From Data to Demand Fulfilling Information
Author(s) -
Sven Meister,
Wolfgang Deiters,
Sven Schafer,
Valentin Stahlmann
Publication year - 2014
Publication title -
complex systems informatics and modeling quarterly
Language(s) - English
Resource type - Journals
ISSN - 2255-9922
DOI - 10.7250/csimq.2014-1.03
Subject(s) - event (particle physics) , computer science , information overload , health care , process (computing) , information system , information technology , data science , information and communications technology , information processing , aggregate (composite) , world wide web , engineering , physics , materials science , quantum mechanics , neuroscience , electrical engineering , economics , composite material , biology , economic growth , operating system
The extensive usage of information and communication technologies (ICT) within healthcare, like electronic health records, Ambient Assisted Living (AAL) and telemedicine, results in a continuously increasing amount of heterogeneous data. Data, on the one hand, is not tantamount to information on the other. Data has to be transformed into demand fulfilling information to cope with one of the biggest problems in information science: data and information overload. The objective of this paper is to introduce technologies like Complex Event Processing (CEP) to develop approaches to cope with the problem of information overload in healthcare according to the principles of Information Logistics (ILOG). We will present a solution that is called TiEE (Telemedical ILOG Event Engine) to process vital signs in real-time and aggregate them to relevant pattern, resulting in demand fulfilling information
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