Estimating the best resource allocation at an Emergency Department's Green Zone using BCC super efficiency and bi-objective MCDEA BCC models - Nazhatul Sahima Mohd Yusoff; Azim Athirah Azhar; Cik Nur Athirah Che Rozak; Siti Hapipah Selamat; Norfarziah Adna; Choong, Yeun Liong (Penerbit Universiti Kebangsaan Malaysia, 2021)
Hospitals are healthcare institutions that provide medical and surgical treatment and nursing care for sick or injured people. Hospitals are generally divided into different types of departments, such as emergency, outpatients, and inpatients. The emergency department (ED) is one of the busiest departments, especially during weekends and public holidays as it handles various sorts of emergency cases. The Green Zone of an Emergency Department, which provides treatment for non-critical cases, is known to be a contributor to the extensive waiting period of patients and overcrowding. As one of the busiest departments, many patients have experienced a long waiting period before being able to receive treatment while enduring the congestion in the ED due to overcrowding of patients. This study aims to estimate the best resource allocations for improving the Emergency Department's Green Zone services. Forty resource allocations including the current and proposed allocations, have been analysed using the Data Envelopment Analysis models. Based on the comparison, the DMU36 proposed by the BCC Super Efficiency model is selected as the best and efficient resource allocation compared to the DMU18 proposed by the Bi-Objective MCDEA-BCC model in order to improve the current services in the Emergency Department's Green Zone during weekends and public holidays. The proposed resource allocation suggests the combination of four doctors and four nurses compared to the previous resource allocation of two doctors and two nurses in every shift. The result shows that the patients' waiting time before treatment at the Emergency Department's Green Zone reduces drastically from 177.80 minutes to 11.47 minutes. The findings also improved the utilisation rates of resources and managed to increase the number of patients served during weekends and public holidays.