HL7 v3 message extraction using Semantic Web techniques

Integration of legacy healthcare systems with new HL7 standard systems is an area of utmost importance in the overall eHealth strategy of the provincial and federal governments of Canada and several other countries. A large body of researchers from across Canada are engaged in delivering solutions such as shared Electronic Health Record, Ontario Laboratory Information System and Ontario Pharmacy System based on HL7 v3 standard. However, due to inherent complexity of HL7 v3 standard and the healthcare domain at large, successful completion of such projects is a difficult task. In this paper, we propose a well-defined framework for designing message workflow during HL7 v3 based system integration. The framework provides a behavior based classification technique for HL7 v3 Interactions that conform well with real-life healthcare transactions. The framework is assisted by a semantic web tool for extracting HL7 v3 messages from healthcare scenarios. Consequently, the proposed approach drastically reduces domaindependant and expert-dependent complexities for software professionals who perform healthcare system integration using HL7 v3 standard.