By Topic

Knowledge Discovery through Mining Emergency Department Data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
A. Ceglowski ; Monash University Melbourne, Australia ; L. Churilov ; J. Wassertheil

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.

Published in:

Proceedings of the 38th Annual Hawaii International Conference on System Sciences

Date of Conference:

03-06 Jan. 2005