Linking clinical data using XML topic maps

Authors:
Ralf Schweiger;Simon Hoelzer;Dirk Rudolf;Joerg Rieger;Joachim Dudeck
Affiliations:
Institute for Medical Informatics, Justus-Liebig-University, Heinrich-Buff-Ring 44, 35392 Giessen, Germany;Institute for Medical Informatics, Justus-Liebig-University, Heinrich-Buff-Ring 44, 35392 Giessen, Germany;Institute for Medical Informatics, Justus-Liebig-University, Heinrich-Buff-Ring 44, 35392 Giessen, Germany;Institute for Medical Informatics, Justus-Liebig-University, Heinrich-Buff-Ring 44, 35392 Giessen, Germany;Institute for Medical Informatics, Justus-Liebig-University, Heinrich-Buff-Ring 44, 35392 Giessen, Germany
Venue:
Artificial Intelligence in Medicine
Year:
2003

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Abstract

Most clinical data is narrative text and often not accessible and searchable at the clinical workstation. We have therefore developed a search engine that allows indexing, searching and linking different kinds of data using web technologies. Text matching methods fail to represent implicit relationships between data, e.g. the relationship between HIV and AIDS. The international organization for standardization (ISO) topic maps standard provides a data model that allows representing arbitrary relationships between resources. Such relationships form the basis for a context sensitive search and accurate search results. The extensible markup language (XML) standards are used for the interchange of data relationships. The approach has been applied to medical classification systems and clinical practice guidelines. The search engine is compared to other XML retrieval methods and the prospect of a ''semantic web'' is discussed.