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Improving the efficiency of a hospital emergency department: a simulation study with indirectly imputed service-time distributions
Authors:Yong-Hong Kuo  Omar Rado  Benedetta Lupia  Janny M Y Leung  Colin A Graham
Institution:1.Big Data Decision Analytics Research Centre,The Chinese University of Hong Kong,Shatin,Hong Kong;2.PriceWaterhouseCoopers Advisory Spa,Milan,Italy;3.Luxottica Group Spa,Treviso,Italy;4.Department of Systems Engineering and Engineering Management,The Chinese University of Hong Kong,Shatin,Hong Kong;5.Accident and Emergency Medicine Academic Unit,The Chinese University of Hong Kong,Shatin,Hong Kong
Abstract:This paper presents a case study which uses simulation to analyze patient flows in a hospital emergency department in Hong Kong. We first analyze the impact of the enhancements made to the system after the relocation of the Emergency Department. After that, we developed a simulation model (using ARENA) to capture all the key relevant processes of the department. When developing the simulation model, we faced the challenge that the data kept by the Emergency Department were incomplete so that the service-time distributions were not directly obtainable. We propose a simulation–optimization approach (integrating simulation with meta-heuristics) to obtain a good set of estimate of input parameters of our simulation model. Using the simulation model, we evaluated the impact of possible changes to the system by running different scenarios. This provides a tool for the operations manager in the Emergency Department to “foresee” the impact on the daily operations when making possible changes (such as, adjusting staffing levels or shift times), and consequently make much better decisions.
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