Enhanced monitoring of abnormal emergency department demands

Handle URI:
http://hdl.handle.net/10754/621314
Title:
Enhanced monitoring of abnormal emergency department demands
Authors:
Harrou, Fouzi; Sun, Ying ( 0000-0001-6703-4270 ) ; Kadri, Farid
Abstract:
This paper presents a statistical technique for detecting signs of abnormal situation generated by the influx of patients at emergency department (ED). The monitoring strategy developed was able to provide early alert mechanisms in the event of abnormal situations caused by abnormal patient arrivals to the ED. More specifically, This work proposed the application of autoregressive moving average (ARMA) models combined with the generalized likelihood ratio (GLR) test for anomaly-detection. ARMA was used as the modelling framework of the ARMA-based GLR anomaly-detection methodology. The GLR test was applied to the uncorrelated residuals obtained from the ARMA model to detect anomalies when the data did not fit the reference ARMA model. The ARMA-based GLR hypothesis testing scheme was successfully applied to the practical data collected from the database of the pediatric emergency department (PED) at Lille regional hospital center, France. © 2015 IEEE.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Harrou F, Sun Y, Kadri F (2015) Enhanced monitoring of abnormal emergency department demands. 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA). Available: http://dx.doi.org/10.1109/ISDA.2015.7489202.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)
Conference/Event name:
15th International Conference on Intelligent Systems Design and Applications, ISDA 2015
Issue Date:
13-Jun-2016
DOI:
10.1109/ISDA.2015.7489202
Type:
Conference Paper
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorHarrou, Fouzien
dc.contributor.authorSun, Yingen
dc.contributor.authorKadri, Fariden
dc.date.accessioned2016-11-03T06:57:29Z-
dc.date.available2016-11-03T06:57:29Z-
dc.date.issued2016-06-13en
dc.identifier.citationHarrou F, Sun Y, Kadri F (2015) Enhanced monitoring of abnormal emergency department demands. 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA). Available: http://dx.doi.org/10.1109/ISDA.2015.7489202.en
dc.identifier.doi10.1109/ISDA.2015.7489202en
dc.identifier.urihttp://hdl.handle.net/10754/621314-
dc.description.abstractThis paper presents a statistical technique for detecting signs of abnormal situation generated by the influx of patients at emergency department (ED). The monitoring strategy developed was able to provide early alert mechanisms in the event of abnormal situations caused by abnormal patient arrivals to the ED. More specifically, This work proposed the application of autoregressive moving average (ARMA) models combined with the generalized likelihood ratio (GLR) test for anomaly-detection. ARMA was used as the modelling framework of the ARMA-based GLR anomaly-detection methodology. The GLR test was applied to the uncorrelated residuals obtained from the ARMA model to detect anomalies when the data did not fit the reference ARMA model. The ARMA-based GLR hypothesis testing scheme was successfully applied to the practical data collected from the database of the pediatric emergency department (PED) at Lille regional hospital center, France. © 2015 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectARMAen
dc.subjectEmergency departmenten
dc.subjecthypothesis testingen
dc.subjectmonitoringen
dc.subjectovercrowdingen
dc.subjecttime seriesen
dc.titleEnhanced monitoring of abnormal emergency department demandsen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)en
dc.conference.date14 December 2015 through 16 December 2015en
dc.conference.name15th International Conference on Intelligent Systems Design and Applications, ISDA 2015en
dc.contributor.institutionPIMM Laboratory, UMR CNRS 800, Arts et Métiers ParisTech, Paris, Franceen
kaust.authorHarrou, Fouzien
kaust.authorSun, Yingen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.