Patient and business rules extraction and formalisation using SVN and SBVR for automated healthcare

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Patient and business rules extraction and formalisation using SVN and SBVR for automated healthcare

Meersman, Davor, De Leenheer, Pieter and Hadzic, Fedja 2012, Patient and business rules extraction and formalisation using SVN and SBVR for automated healthcare, in ACIS 2012 : Location, location, location : Proceedings of the 23rd Australasian Conference on Information Systems 2012, ACIS, [Geelong, Vic.], pp. 1-11.

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Title	Patient and business rules extraction and formalisation using SVN and SBVR for automated healthcare
Author(s)	Meersman, Davor De Leenheer, Pieter Hadzic, Fedja
Conference name	Australasian Conference on Information Systems (23rd : 2012 : Geelong, Victoria)
Conference location	Geelong, Victoria
Conference dates	3-5 Dec. 2012
Title of proceedings	ACIS 2012 : Location, location, location : Proceedings of the 23rd Australasian Conference on Information Systems 2012
Editor(s)	Lamp, John orcid.org/0000-0003-1891-0400
Publication date	2012
Conference series	Australasian Conference on Information Systems
Start page	1
End page	11
Total pages	11
Publisher	ACIS
Place of publication	[Geelong, Vic.]
Keyword(s)	rule extraction SBVR type 2 diabetes ambient assisted living service value networks
Summary	This paper describes advances in automated health service selection and composition in the Ambient Assisted Living (AAL) domain. We apply a Service Value Network (SVN) approach to automatically match medical practice recommendations to health services based on sensor readings in a home care context. Medical practice recommendations are extracted from National Health and Medical Research Council (NHMRC) guidelines. Service networks are derived from Medicare Benefits Schedule (MBS) listings. Service provider rules are further formalised using Semantics of Business Vocabulary and Business Rules (SBVR), which allows business participants to identify and define machine-readable rules. We demonstrate our work by applying an SVN composition process to patient profiles in the context of Type 2 Diabetes Management.
Notes	Reproduced with the kind permission of the copyright owner.
Language	eng
Field of Research	089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective	970108 Expanding Knowledge in the Information and Computing Sciences
Related work	DU:30049020
Copyright notice	©2012, The Authors/ACIS
Free to Read?	Yes
Persistent URL	http://hdl.handle.net/10536/DRO/DU:30049137

Document type:	Conference Paper
Collections:	ACIS : Proceedings of the 23rd Australasian Conference on Information Systems 2012 Open Access Collection


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