Abstract
Long waiting times and patient congestion are common problems faced by emergency departments (EDs) worldwide. During pandemics like COVID-19, EDs worldwide start to be flooded with patients and hospitals find it very challenging to provide good treatment to the large number of patients visiting the EDs with their current allocation of resources. Hospitals are in need of a decision support system (DSS) which can predict the excess demand and suggest the appropriate quantity of resources to be allocated at each point of care. The present research focuses on an ED of a large public hospital in India and explores in finding a solution for the long patient waiting time problem experienced by the hospital. This study extends the application domain of SimPy-based simulation modeling with integrated metamodeling and optimization to optimally allocate the resources in the ED. This can be used as a novel DSS which is relatively faster and needs less human interaction by the hospital management compared to the existing methods. The proposed resource allocation by this model reduced the patient waiting time by 44% in the case hospital being studied. Hospitals may use the proposed methodology to appropriately allocate their resources in times of excess demand.
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Battu, A., Venkataramanaiah, S., Sridharan, R. (2023). Patient Flow Optimization in an Emergency Department Using SimPy-Based Simulation Modeling and Analysis: A Case Study. In: Vučinić, D., Chandran, V., Mahbub, A.M., Sobhan, C.B. (eds) Applications of Computation in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-6032-1_22
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DOI: https://doi.org/10.1007/978-981-19-6032-1_22
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