Data driven process modelling for a hospital emergency department

Andrzej CEGLOWSKI, Leonid CHURILOV, Jeff WASSERTHIEL

2004

Abstract

This paper describes how key activities in the emergency department of a major hospital were extracted from workflow history. Analysis of these activities help with modification of both administrative and clinical actions for improved efficiency and effectiveness. Extraction of process from data is a relatively new field. This paper’s contributes the innovative determination of processes through data mining, rather than the algorithm-driven approach used to date. Data about patients who present to a major hospital emergency department were used to define clusters of patients who follow common pathways through the emergency department. It is discussed how these “process based” clusters can be used for performance management of the emergency department through evaluation of process inputs, outputs and costs.

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Paper Citation


in Harvard Style

CEGLOWSKI A., CHURILOV L. and WASSERTHIEL J. (2004). Data driven process modelling for a hospital emergency department . In Proceedings of the 1st International Workshop on Computer Supported Activity Coordination - CSAC, (ICEIS 2004) ISBN 972-8865-08-2, pages 61-70. DOI: 10.5220/0002667800610070


in Bibtex Style

@conference{csac04,
author={Andrzej CEGLOWSKI and Leonid CHURILOV and Jeff WASSERTHIEL},
title={Data driven process modelling for a hospital emergency department},
booktitle={Proceedings of the 1st International Workshop on Computer Supported Activity Coordination - CSAC, (ICEIS 2004)},
year={2004},
pages={61-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002667800610070},
isbn={972-8865-08-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Computer Supported Activity Coordination - CSAC, (ICEIS 2004)
TI - Data driven process modelling for a hospital emergency department
SN - 972-8865-08-2
AU - CEGLOWSKI A.
AU - CHURILOV L.
AU - WASSERTHIEL J.
PY - 2004
SP - 61
EP - 70
DO - 10.5220/0002667800610070