A DISCRETE EVENT SIMULATION (DES) BASED APPROACH TO MAXIMIZE THE PATIENT THROUGHPUT IN OUTPATIENT CLINIC

Authors

  • Vidanelage L. Dayarathna PhD Student, Graduate Research Assistant, Department of Industrial and Systems Engineering, Mississippi State University, PO Box 9542, Mississippi State, 39762,
  • Hebah Mismesh Master Student, Department of Industrial and Systems Engineering, Mississippi State University, PO Box 9542, Mississippi State, 39762,
  • Mohammad Nagahisarchoghaei PhD Student, Graduate Research Assistant, College of Computing and Informatics, University of North Carolina at Charlotte, North Carolina,
  • Aziz Alhumoud Department of Industrial and Systems Engineering, Mississippi State University, PO Box 9542, Mississippi State, 39762

DOI:

https://doi.org/10.51594/estj.v1i1.36

Keywords:

Healthcare, System Simulation, Discrete Event Simulation (DES), Patient Throughput, Waiting Time.

Abstract

The healthcare system is a complex system which exhibits conditions of uncertainty, ambiguity emergence that incurs incoming patient congestion. Discrete event simulation (FlexSim) is considered as a viable decision support tool in analyzing a system for improvement. Using a data-driven discrete event simulation approach, this paper portrays a comprehensive analysis to maximize the number of patients in an on-campus clinic, located at Mississippi State University. The outcome of the analysis of current system exhibits that deploying a few nurse practitioners results in bottlenecks which decreases the systems’ throughput substantially due to the overall longer patients’ waiting time.  Access to the laboratory is characterized through multi-server queuing network, arrival process is followed discrete distributions, and batch sizes and arrival times are stochastic in nature. In an effort to plummet inpatient congestion at the outpatient clinic, by using empirically calibrated simulation model, we will figure out the best balance between the number of the lab technician and incoming patient during working hour. An analysis of optimal solutions is demonstrated, which is followed by recommendation and avenues for future research.

Published

2019-08-05 — Updated on 2020-06-23

Issue

Section

Articles