Visualising a state-wide patient data collection : a case study to expand the audience for healthcare data Luo, Wei, Gallagher, Marcus, O'Kane, Di, Connor, Jason, Dooris, Mark, Roberts, Col, Mortimer, Lachlan and Wiles, Janet 2010, Visualising a state-wide patient data collection : a case study to expand the audience for healthcare data, in HIKM 2010 : Proceedings of the 4th Australasian Workshop on Health Informatics and Knowledge Management, Australian Computer Society, Sydney, N.S.W., pp. 45-52. Attached Files Name Description MIMEType Size Downloads Title Visualising a state-wide patient data collection : a case study to expand the audience for healthcare data Author(s) Luo, Wei orcid.org/0000-0002-4711-7543 Gallagher, Marcus O'Kane, Di Connor, Jason Dooris, Mark Roberts, Col Mortimer, Lachlan Wiles, Janet Conference name Australasian Workshop on Health Informatics and Knowledge Management (4th : 2010 : Brisbane, Queensland) Conference location Brisbane, Queensland Conference dates 18-21 Jan. 2010 Title of proceedings HIKM 2010 : Proceedings of the 4th Australasian Workshop on Health Informatics and Knowledge Management Editor(s) Maeder, Anthony Hansen, David Estivill-Castro, Vladimir Simoff, Simeon J. Publication date 2010 Conference series Australasian Workshop on Health Informatics and Knowledge Management Start page 45 End page 52 Total pages 8 Publisher Australian Computer Society Place of publication Sydney, N.S.W. Keyword(s) visualisation exploratory data analysis routine data collection Summary This paper describes the application of existing and novel adaptations of visualisation techniques to routinely collected health data. The aim of this case study is to examine the capacity for visualisation approaches to quickly and e ectively inform clinical, policy, and scal decision making to improve healthcare provision. We demonstrate the use of interactive graphics, fluctuation plots, mosaic plots, time plots, heatmaps, and disease maps to visualise patient admission, transfer, in-hospital mortality, morbidity coding, execution of diagnosis and treatment guidelines, and the temporal and spatial variations of diseases. The relative e ectiveness of these techniques and associated challenges are discussed. ISBN 9781920682897 1920682899 Language eng Field of Research 080109 Pattern Recognition and Data Mining Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2010, Australian Computer Society Persistent URL http://hdl.handle.net/10536/DRO/DU:30052498 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 14 May 2013, 13:51:07 EST Tue, 14 May 2013, 14:37:19 EST Thu, 16 May 2013, 15:16:35 EST Fri, 10 Oct 2014, 09:05:41 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 641 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Tue, 14 May 2013, 13:51:07 EST