research-article

A simulation model of patient flow through the emergency department to determine the impact of a short stay unit on hospital congestion

Authors:

Amy L. Cochran,

Keith E. Kocher,

Valerie N. Washington,

Gabriel Zayas-CabánAuthors Info & Claims

WSC '16: Proceedings of the 2016 Winter Simulation Conference

Pages 1982 - 1993

Published: 11 December 2016 Publication History

Abstract

One of the most critical and costly decisions made in emergency departments (EDs) is whether to admit a patient into the hospital. These decisions require investment in time for patient testing and treatment, delaying care to other patients. Short-stay units (SSUs) are an alternative to discharging or fully admitting ED patients, allowing extended patient observation. However, little is understood about the design of an SSU and its impact on outcomes and congestion. Here, we introduce a discrete-event simulation model of a hospital system (ED, inpatient units, and SSUs). By analyzing records from a tertiary teaching hospital, we determine realistic parameters and identify important features, such as triage level and processes depending on triage level, time, and congestion. We contend that performance metrics, e.g. time to first contact, critically depend on downstream hospital units. To demonstrate utility, we use the simulation model to assess bed occupancy over time.

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Cited By

Lay JAugusto VXie XAlfonso-Lizarazo EBongue BCelarier TGonthier RMasmoudi M(2020)Impact of covid-19 epidemics on bed requirements in a healthcare center using data-driven discrete-event simulationProceedings of the Winter Simulation Conference10.5555/3466184.3466271(771-781)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466271
Monks TMeskarian R(2017)Using simulation to help hospitals reduce emergency department waiting timesProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242418(1-12)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242418

A simulation model of patient flow through the emergency department to determine the impact of a short stay unit on hospital congestion
1. Applied computing
  1. Life and medical sciences
  2. Operations research

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Information & Contributors

Information

Published In

cover image ACM Conferences

WSC '16: Proceedings of the 2016 Winter Simulation Conference

December 2016

3974 pages

ISBN:9781509044849

General Chair:
Todd Huschka
Mayo Clinic
,
Program Chair:
Stephen E. Chick
INSEAD

Sponsors

IIE: Institute of Industrial Engineers
INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
SIGSIM: ACM Special Interest Group on Simulation and Modeling
SCS: Society for Modeling and Simulation International

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SAS
AnyLogic: The AnyLogic Company
Palgrave: Palgrave Macmillan
FlexSim: FlexSim Software Products, Inc.
ASA: American Statistical Association
IEEE/SMC: Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics Society
Simio: Simio LLC
ODU: Old Dominion University
ASIM: Arbeitsgemeinschaft Simulation
ExtendSim: ExtendSim
NIST: National Institute of Standards & Technology
Amazon Simulations: Amazon Simulations

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IEEE Press

Publication History

Published: 11 December 2016

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WSC '16

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IIE
INFORMS-SIM
SIGSIM
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WSC '16: Winter Simulation Conference

December 11 - 14, 2016

Virginia, Arlington

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Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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Cited By

Lay JAugusto VXie XAlfonso-Lizarazo EBongue BCelarier TGonthier RMasmoudi M(2020)Impact of covid-19 epidemics on bed requirements in a healthcare center using data-driven discrete-event simulationProceedings of the Winter Simulation Conference10.5555/3466184.3466271(771-781)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466271
Monks TMeskarian R(2017)Using simulation to help hospitals reduce emergency department waiting timesProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242418(1-12)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242418

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