Knowledge Discovery through Mining Emergency Department Data

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Ceglowski, A.  Churilov, L.  Wassertheil, J. 
Monash University Melbourne, Australia 

This paper appears in: System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on
Issue Date: 03-06 Jan. 2005
On page(s): 142c - 142c
ISSN: 1530-1605
Print ISBN: 0-7695-2268-8
Digital Object Identifier: 10.1109/HICSS.2005.371
Date of Current Version: 24 January 2005

Abstract

The complexity of hospital emergency department operations limits comprehension and inhibits efforts to improve efficiency. Attempts have been made to reduce the complexity by streaming patients into similar classes of treatment or grouping them into similar cases. These have not successfully modeled the treatment of patients. This paper describes how the combination of a process philosophy with data mining resulted in the discovery of definitive "treatment pathways". These pathways comprehensively model treatment of patients. Examination of these pathways indicated that the ratio of treatment procedures remained fairly constant. It was concluded that workload in the emergency department varies only by number of presentations, not in type of procedure carried out. Some applications of this knowledge are discussed.

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