Exploratory Clustering for Emergency Department Patients.

Autor: FERETZAKIS, Georgios, SAKAGIANNI, Aikaterini, KALLES, Dimitris, LOUPELIS, Evangelos, TZELVES, Lazaros, PANTERIS, Vasileios, CHATZIKYRIAKOU, Rea, TRAKAS, Nikolaos, KOLOKYTHA, Stavroula, BATIANI, Polyxeni, RAKOPOULOU, Zoi, TIKA, Aikaterini, PETROPOULOU, Stavroula, DALAINAS, Ilias, KALDIS, Vasileios
Zdroj: Studies in Health Technology & Informatics; 2022, Vol. 295, p503-506, 4p, 1 Chart, 1 Graph
Abstrakt: Emergency department (ED) overcrowding is an increasing global problem raising safety concerns for the patients. Elaborating an effective triage system that properly separates patients requiring hospital admission remains difficult. The objective of this study was to compare a clustering-related technique assignment of emergency department patients with the admission output using the k-means algorithm. Incorporating such a model into triage practice could theoretically shorten waiting times and reduce ED overcrowding. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index