title: Pediatric emergency department crowding: survival tree clustering for length of patient stay.
abstract: The objective of this study is to analyse the length of patient stay in Pediatric emergency department according to diagnosis and the number of patients over a 3 year-period. A survival tree was used, to explore the underlying construct of overcrowding depending of the length of patient stay. The tree was used to cluster 55.183 patients with respect to length of stay where partitioning is based on covariates such as the number of patients, the diagnosis and existence of complementary exams. The hazard ratio test was used to determine optimal partition. The approach is illustrated using Electronic Medical Record Software database available at the Pediatric Emergency Department of Lille University Hospital.
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Féryal
authors.initials: F
authors.lastname: Windal
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Karama
authors.initials: K
authors.lastname: Jeribi
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Grégoire
authors.initials: G
authors.lastname: Ficheur
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Samuel
authors.initials: S
authors.lastname: Degoul
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Alain
authors.initials: A
authors.lastname: Martinot
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Régis
authors.initials: R
authors.lastname: Beuscart
authors.affiliation: EA-2694, Lille Nord de France University.
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Renard
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003441:Crowding; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D005602:France / Q000453:epidemiology; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007902:Length of Stay / Q000706:statistics & numerical data*; D008137:Longitudinal Studies; D008297:Male; D009323:Natural Language Processing; D010372:Pediatrics / Q000706:statistics & numerical data*; D014850:Waiting Lists; D016526:Workload / Q000706:statistics & numerical data