An interoperable framework for a clinical decision support system

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dc.contributor.author Bilykh, Iryna. en_US
dc.date.accessioned 2008-04-10T06:00:41Z
dc.date.available 2008-04-10T06:00:41Z
dc.date.copyright 2004 en_US
dc.date.issued 2008-04-10T06:00:41Z
dc.identifier.uri http://hdl.handle.net/1828/592
dc.description.abstract The healthcare sector is facing a significant challenge: delivering quality clinical care in a costly and intricate environment. There is a general consensus that a solution for many aspects of this problem lies in establishing a framework for effective and efficient clinical decision support. The key to good decision support is offering clinicians just-in-time accessibility to relevant patient specific knowledge. However, at the present time, management of clinical knowledge and patient records is significantly inadequate resulting in sometimes uninformed, erroneous, and costly clinical decisions. One of the contributing factors is that the field of healthcare is characterized by large volumes of highly complex medical knowledge and patient information that must be captured, processed, interpreted, stored, analyzed, and exchanged. Moreover, different clinical information systems are typically not interoperable. This thesis introduces an approach for realizing a clinical decision support framework that manages complex clinical knowledge in a form of evidence-based clinical practice guidelines. The focus of presented work is directed on the interoperability of knowledge, information, and processes in a heterogeneous distributed environment. The main contributions of this thesis include definition of requirements, conceptual architecture, and approach for an interoperable clinical decision support system that is stand-alone, independent, and based on open source standards. en_US
dc.subject.lcsh Clinical medicine -- Decision making -- Data processing en_US
dc.title An interoperable framework for a clinical decision support system en_US
dc.contributor.supervisor Jahnke, Jens H. en_US
dc.degree.department Dept. of Computer Science en_US

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