Searching for document contents in an IHE-XDS EHR architecture via archetype-based indexing of document types
Christoph Rinner1, Michael Kohler, Samrend Saboor
1Section for Medical Information Management and Imaging, Medical University of Vienna, Austria.
Abstract:
The shared EHR (electronic health record) system architecture IHE XDS is widely adopted internationally. It ensures a high level of data privacy via distributed storage of EHR documents. Its standard search capabilities, however, are limited; it only allows a retrieval of complete documents by querying a restricted set of document metadata. Existing approaches that aim to extend XDS queries to document contents typically employ a central index of document contents. Hereby they undermine XDS' basic characteristic of distributed data storage. To avoid data privacy concerns, we propose querying EHR contents in XDS by indexing document types based on Archetypes instead. We successfully tested our approach within the ISO/EN 13606 standard.
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