Codrington-Virtue, Anthony and Chaussalet, Thierry J. and Millard, Peter H. and Whittlestone, Paul and Kelly, John (2006) A system for patient management based discrete-event simulation and hierarchical clustering. In: Lee, D.J. and Nutter, Brian and Antani, Sameer and Mitra, Sunanda and Archibald, James, (eds.) Nineteenth IEEE International Symposium on Computer-Based Medical Systems: 22-23 June 2006, Salt Lake City, Utah. Proceedings. IEEE Computer Society, Las Alamitos, USA, pp. 800-804. ISBN 0769525171
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumb...
Hospital Accident and Emergency (A&E) departments in England have a 4 hour target to treat 98% of patients from arrival to discharge, admission or transfer. Managing resources to meet the target and deliver care across the range of A&E services is a huge challenge for A&E managers. This paper develops an intelligent patient management tool to help managers and clinicians better understand patient length of stay and resources within an A&E area. The developed discrete-event simulation model gives a highlevel representation of ambulance arrivals into A&E. The model facilitates analysis in the following ways: visually interactive software showing patient length of stay in the A&E area; patient activity broken down into sub-groups so that intelligence might be gathered on how sub-groups affect the overall length of stay; understanding the number of patient treatment places and nurse resources required. To support ease of inputs for scenario and sensitivity testing, data is entered into the simulation model (Simul8) via Excel spreadsheets. The model discussed in this paper used patient length of stay grouped by A&E diagnosis codes and was limited to ambulance arrivals. The analysis was derived from A&E attendance in 2004 from an English hospital.
|Item Type:||Book Section|
|Research Community:||University of Westminster > Electronics and Computer Science, School of|
|Deposited On:||29 Sep 2006|
|Last Modified:||11 Aug 2010 15:31|
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