DocumentCode :
2111904
Title :
Time based clustering for analyzing acute hospital patient flow
Author :
Khanna, Saarthak ; Boyle, Justin ; Good, Nicholas ; Lind, Jonathan ; Zeitz, Kathryn
Author_Institution :
Australian E-Health Res. Centre, R. Brisbane & Women´s Hosp., Herston, QLD, Australia
fYear :
2012
fDate :
Aug. 28 2012-Sept. 1 2012
Firstpage :
5903
Lastpage :
5906
Abstract :
This paper describes a novel approach employing time based clustering of health data for visualization and analysis of patient flow. Clustering inpatient and emergency department patient episodes into hourly slots based on recorded timestamps, and then grouping them on required parameters, the technique provides a powerful tool for visualizing and analyzing interactions and interdependencies between hospital patient flow parameters. To demonstrate the efficacy of the approach, we employ time based clustering to address some typical patient flow related queries and discuss the findings.
Keywords :
hospitals; medical information systems; acute hospital patient flow; emergency department patient; health data; hospital patient flow parameter; powerful tool; time based clustering; Australia; Correlation; Data visualization; Discharges (electric); Fluid flow measurement; Hospitals; Robustness; Cluster Analysis; Hospital Administration; Patient Transfer; Queensland; Time Management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2012.6347337
Filename :
6347337
Link To Document :
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