research-article

Evaluating alternative resource allocation in an emergency department using discrete event simulation

Authors:

Leonardo Bedoya-Valencia,

Emre KiracAuthors Info & Claims

Simulation, Volume 92, Issue 12

Pages 1041 - 1051

https://doi.org/10.1177/0037549716673150

Published: 01 December 2016 Publication History

Abstract

Reducing emergency department ED overcrowding in the hope of improving the ED's operational efficiency and healthcare delivery is an important objective for healthcare providers. This research analyzes resource allocation with the objective of reducing patient length-of-stay LOS and time to be seen by a physician or physician assistant TBSPPA while leveling resource utilization. Different levels of resources physicians, physician assistants, and nurses were changed in controlled experiments in order to analyze patients' LOS and TBSPPA, as well as resource utilization. The experiments were performed using a simulation model based on data from an ED at a local hospital. The simulation model accounts for patients with different severity levels as well as different rates for patient arrivals. Based on the severity, patients are treated by combinations of multiple resources, often with interspersed waiting time. Results indicate that the simulation model can be used as a tool to help decision makers in the ED with the allocation of resources. The experiments show an average reduction of 14% in the average patients' LOS, 16% in the average patients' TBSPPA, and leveled resource utilization between 70% and 80% when allowing a restructure of the ED resource capacities.

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Cited By

Heib ACurrie COnggo BSmith HKerr J(2023)A Generalized Symbiotic Simulation Model of an Emergency Department for Real-Time Operational Decision-MakingProceedings of the Winter Simulation Conference10.5555/3643142.3643228(1042-1053)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3643142.3643228
Fava GGiovannelli TMessedaglia MRoma M(2022)Effect of different patient peak arrivals on an emergency department via discrete event simulationSimulation10.1177/0037549721103875698:3(161-181)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1177/00375497211038756
Shoaib MRamamohan V(2022)Simulation modeling and analysis of primary health center operationsSimulation10.1177/0037549721103093198:3(183-208)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1177/00375497211030931
Show More Cited By

Evaluating alternative resource allocation in an emergency department using discrete event simulation
1. Applied computing
  1. Life and medical sciences
  2. Operations research

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cover image Simulation

Simulation Volume 92, Issue 12

12 2016

63 pages

Issue’s Table of Contents

Copyright © © The Authors 2016.

Publisher

Society for Computer Simulation International

San Diego, CA, United States

Publication History

Published: 01 December 2016

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Cited By

Heib ACurrie COnggo BSmith HKerr J(2023)A Generalized Symbiotic Simulation Model of an Emergency Department for Real-Time Operational Decision-MakingProceedings of the Winter Simulation Conference10.5555/3643142.3643228(1042-1053)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3643142.3643228
Fava GGiovannelli TMessedaglia MRoma M(2022)Effect of different patient peak arrivals on an emergency department via discrete event simulationSimulation10.1177/0037549721103875698:3(161-181)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1177/00375497211038756
Shoaib MRamamohan V(2022)Simulation modeling and analysis of primary health center operationsSimulation10.1177/0037549721103093198:3(183-208)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1177/00375497211030931
Zülch GVollstedt TDurak U(2019)Simulation-supported assessment of qualification and department organization in industrial maintenanceProceedings of the 2019 Summer Simulation Conference10.5555/3374138.3374142(1-12)Online publication date: 22-Jul-2019
https://dl.acm.org/doi/10.5555/3374138.3374142
Rosemarin HRosenfeld AKraus S(2019)Emergency department online patient-caregiver schedulingProceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v33i01.3301695(695-701)Online publication date: 27-Jan-2019
https://dl.acm.org/doi/10.1609/aaai.v33i01.3301695
Hofmann MMeyer-Nieberg SUhlig TJohansson BJain S(2018)Inferential statistics and simulation generated samplesProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320583(479-490)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320583
Troy PWestaway LGrondin ARezanowicz T(2017)Rationalizing healthcare budgeting when providing services with mandated maximum delaysProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242417(1-12)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242417
Chen PLin M(2017)Development of simulation optimization methods for solving patient referral problems in the hospital-collaboration environmentJournal of Biomedical Informatics10.1016/j.jbi.2017.08.00473:C(148-158)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1016/j.jbi.2017.08.004

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