Title: HL7 v3 message extraction using Semantic Web techniques

Authors: Priya Jayaratna; Kamran Sartipi

Addresses: Department of Computing and Software, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada. ' Faculty of Engineering and Applied Science, University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, ON, L1H 7K4, Canada

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.

Keywords: health informatics; healthcare systems; semantic web; HL7 v3 messages; scenario; system interoperability; information modelling; interaction; healthcare transactions; context; knowledge management; electronic healthcare; e-health; system integration.

DOI: 10.1504/IJKEDM.2012.044699

International Journal of Knowledge Engineering and Data Mining, 2012 Vol.2 No.1, pp.89 - 115

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 03 Jan 2012 *

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