Emergency department flow: A new practical patients classification and forecasting daily attendance

被引：10

作者：

Afilal, Mohamed ^{[1
,2
]}

Yalaoui, Farouk ^{[1
]}

Dugardin, Frederic ^{[1
]}

Amodeo, Lionel ^{[1
]}

Laplanche, David ^{[2
]}

Blua, Philippe ^{[2
]}

机构：

[1] Univ Technol Troyes, CNRS, LOSI, Inst Charles Delaunay,UMR 6281, 12 Rue Marie Curie,CS 42060, F-10004 Troyes, France

[2] Ctr Hosp Troyes, Dept Informat Med, 101 Ave Anatole France, F-10000 Troyes, France

来源：

IFAC PAPERSONLINE | 2016年 / 49卷 / 12期

关键词：

Emergency Department Flow; Forecasting; Patient Classification; Time series; TIME-SERIES; ACCIDENT; DEMAND;

D O I：

10.1016/j.ifacol.2016.07.859

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Emergeticy department (ED) bras become the patient's mai I L point of entrance in modern hospitals causing it frequent overcrowding. 'Thus hospital managers are increasingly giving attention to the ED in order to provide better quality service for patients. One of the key elements for a good management strategy is demand forecasting. In this case, forecasting patients flow, which will help decision makers to optimize (doctors, nurses...) and Material (beds, boxs...) resources allocation. The main interest Of this research is forecasting daily attendance at an emergency department. The study was conducted on the Emergency Department of the Hospital of Troyes city, France, in which we propose a new practical ED patients classification that consolidate the CCMU and GEMS.A into one single category and an innovative time -series based forecasting models to predict lot ig and short term daily attendance. The models we developed for this case study shows very good performances (up to 92,29% for the annual Total flow forecast) and robustness to epidemic periods. (C) 2016, IFAC(International Federation of Automatic Control) Hosting by Elsevier Ltd. All right reserved.

引用

页码：721 / 726

页数：6

共 21 条

[1] Short-Term Forecasting of Emergency Inpatient Flow [J].