Early detection of abnormal patient arrivals at hospital emergency department

Handle URI:
http://hdl.handle.net/10754/593679
Title:
Early detection of abnormal patient arrivals at hospital emergency department
Authors:
Harrou, Fouzi; Sun, Ying ( 0000-0001-6703-4270 ) ; Kadri, Farid; Chaabane, Sondes; Tahon, Christian
Abstract:
Overcrowding is one of the most crucial issues confronting emergency departments (EDs) throughout the world. Efficient management of patient flows for ED services has become an urgent issue for most hospital administrations. Handling and detection of abnormal situations is a key challenge in EDs. Thus, the early detection of abnormal patient arrivals at EDs plays an important role from the point of view of improving management of the inspected EDs. It allows the EDs mangers to prepare for high levels of care activities, to optimize the internal resources and to predict enough hospitalization capacity in downstream care services. This study reports the development of statistical method for enhancing detection of abnormal daily patient arrivals at the ED, which able to provide early alert mechanisms in the event of abnormal situations. The autoregressive moving average (ARMA)-based exponentially weighted moving average (EWMA) anomaly detection scheme proposed was successfully applied to the practical data collected from the database of the pediatric emergency department (PED) at Lille regional hospital center, France.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 International Conference on Industrial Engineering and Systems Management (IESM)
Conference/Event name:
2015 International Conference on Industrial Engineering and Systems Management (IESM)
Issue Date:
21-Oct-2015
DOI:
10.1109/IESM.2015.7380162
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7380162
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.contributor.authorChaabane, Sondesen
dc.contributor.authorTahon, Christianen
dc.date.accessioned2016-01-18T07:58:02Zen
dc.date.available2016-01-18T07:58:02Zen
dc.date.issued2015-10-21en
dc.identifier.doi10.1109/IESM.2015.7380162en
dc.identifier.urihttp://hdl.handle.net/10754/593679en
dc.description.abstractOvercrowding is one of the most crucial issues confronting emergency departments (EDs) throughout the world. Efficient management of patient flows for ED services has become an urgent issue for most hospital administrations. Handling and detection of abnormal situations is a key challenge in EDs. Thus, the early detection of abnormal patient arrivals at EDs plays an important role from the point of view of improving management of the inspected EDs. It allows the EDs mangers to prepare for high levels of care activities, to optimize the internal resources and to predict enough hospitalization capacity in downstream care services. This study reports the development of statistical method for enhancing detection of abnormal daily patient arrivals at the ED, which able to provide early alert mechanisms in the event of abnormal situations. The autoregressive moving average (ARMA)-based exponentially weighted moving average (EWMA) anomaly detection scheme proposed was successfully applied to the practical data collected from the database of the pediatric emergency department (PED) at Lille regional hospital center, France.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7380162en
dc.titleEarly detection of abnormal patient arrivals at hospital emergency departmenten
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2015 International Conference on Industrial Engineering and Systems Management (IESM)en
dc.conference.date21-23 Oct. 2015en
dc.conference.name2015 International Conference on Industrial Engineering and Systems Management (IESM)en
dc.conference.locationSeville, Spainen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionLAMIH, UMR CNRS 8201, University of Valenciennes and Hainaut-Cambresis, UVHC, Le Mont Houy, Franceen
kaust.authorHarrou, Fouzien
kaust.authorSun, Yingen
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