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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.

Pediatric Emergency Department Crowding: Survival Tree Clustering for Length of Patient Stay