HL7 v3 message extraction using Semantic Web techniques Online publication date: Tue, 02-Sep-2014
by Priya Jayaratna; Kamran Sartipi
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Vol. 2, No. 1, 2012
Abstract: Healthcare system integration is an area of utmost importance in the overall eHealth strategy of countries. The overall goal of these efforts is to provide a large scale and unified view of clinical information to healthcare practitioners, thereby enabling them to deliver accurate and timely services to the general public in a cost-efficient manner. In this paper, we present a novel framework for identifying HL7 v3 messages to represent healthcare transactions that take place in an integration scenario. The proposed technique provides a new categorisation of HL7 v3 message functionality according to a set of message contexts extracted by extensive study of HL7 v3 information hierarchies and messaging infrastructure. These contexts allow us to map the key terms in a healthcare scenario to the corresponding HL7 v3 messages using Semantic Web technology. We have developed a prototype tool and will present two healthcare case studies to demonstrate our solution.
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