HL7 v3 message extraction using Semantic Web techniques

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.