Emergency department flow: A new practical patients classification and forecasting daily attendance. Issue 12 (2016)

• Record Type: Journal Article
• Authors: Afilal, Mohamed; Yalaoui, Farouk; Dugardin, Frédéric; Amodeo, Lionel; Laplanche, David; Blua, Philippe
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 12(2016)
• Page Start: 721
• Page End: 726
• Publication Date: 2016
• Subjects: Emergency Department Flow -- Forecasting -- Patient Classification -- Time series; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.07.859
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Emergency department (ED) has become the patient's main 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 human(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 GEMSA into one single category and an innovative time-series based forecasting models to predict long 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.