Scenario-based analysis of fast track strategy optimization on emergency department using integrated safety simulation

Hajjarsaraei, Hedieh; Shirazi, Babak; Rezaeian, Javad

doi:10.1016/j.ssci.2018.03.025

Cited by 21 publications

(24 citation statements)

References 31 publications

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“…Hajjarsaraei, et al [1] proposed a DES model integrated with system dynamics (ISS) to reduce patient waiting time, LoS, and number of patients who leave without being seen (LWBS). The ISS model assesses the optimization of the fast track strategy [42] and the impact of sensitive policy parameters on the safety performance of ED.…”

Section: Related Workmentioning

confidence: 99%

“…However, only a few ED models examine the operational patient flow process in ED with respect to reducing patient throughput time [15,16]. These models include integrated safety simulation [1], agentbased simulation (ABS) [2], and interactive simulation-based decision support framework [3]. Patient throughput time is the total amount of time spent to serve a patient (from the patient's time of arrival to the time of exit from ED).…”

Section: Introductionmentioning

confidence: 99%

“…The issue of patient throughput time relates to the long patient throughput time in ED. Patient throughput time is essential in obtaining patient satisfaction; providing quality treatment while reducing the throughput time of patients enhances ED performance in terms of achieving patient satisfaction and providing effective treatment services [1,[17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…Waiting time refers to the total time that a patient waited before being served in ED; overcrowding in ED increases patient waiting time [24,25]. LoS is related to the total time that a patient spent in ED, and it starts from the time when the patient entered ED (arrival time) to the time the patient physically left ED (departure time) [1]. The relationship of patient waiting time and LoS with patient throughput time is directly incremental.…”

Section: Introductionmentioning

confidence: 99%

“…. • The empirical assessment of the proposed SIM-PFED in terms of reducing patient throughput time is based on actual ED datasets from four hospitals, namely, Shahid Rajaei Hospital (SRH) [1], Santa Casa de São Paulo Hospital [2], hospital in North Dublin, Ireland [3], Urgent Care Center(UCC) [20]. These datasets are considered to be under the context of the proposed model (simulation of patient flow in ED).…”

Section: Introductionmentioning

confidence: 99%

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SIM-PFED: A Simulation-Based Decision Making Model of Patient Flow for Improving Patient Throughput Time in Emergency Department

2021

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Healthcare sectors face multiple threats, and the hospital emergency department (ED) is one of the most crucial hospital areas. ED plays a key role in promoting hospitals' goals of enhancing service efficiency. ED is a complex system due to the stochastic behavior of patient arrivals, the unpredictability of the care required by patients, and the department's complex nature. Simulations are effective tools for analyzing and optimizing complex ED operations. Although existing ED simulation models have substantially improved ED performance in terms of ensuring patient satisfaction and effective treatment services, many deficiencies continue to exist in addressing the key challenge in ED, namely, long patient throughput time. The patient throughput time issue is affected by causative factors, such as waiting time, length of stay, and decision-making. This research aims to develop a new simulation model of patient flow for ED (SIM-PFED) to address the reported key challenge of the patient throughput time. SIM-PFED introduces a new process for patient flow in ED on the basis of the newly proposed operational patient flow by combining discrete event simulation and agent-based simulation and applying a multi-attribute decisionmaking method, namely, the technique for order preference by similarity to the ideal solution. Experiments were performed on three actual hospital ED datasets to assess the effectiveness of SIM-PFED. Experimental results revealed the superiority of SIM-PFED over other alternative models in reducing patient throughput time in ED by consuming less patient waiting time and having a shorter length of stay. The findings also demonstrated the effectiveness of SIM-PFED in helping ED decision-makers select the best scenarios to be implemented in ED for ensuring minimal throughput time while being cost effective.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

SIM-PFED: A Simulation-Based Decision Making Model of Patient Flow for Improving Patient Throughput Time in Emergency Department

2021

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Evaluation of Fast-Track Implementation on Emergency Department: A Literature Review

Viera

Reis

Chaves

et al. 2021

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

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Managing low–acuity patients in an Emergency Department through simulation–based multiobjective optimization using a neural network metamodel

Boresta,

Giovannelli,

Roma

2024

Health Care Manag Sci

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This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on optimizing resource allocation in minor injuries units, which are the ED units that can treat low-acuity patients, with the aim of minimizing patient waiting times and ED operating costs. We formulate this problem as a general multiobjective simulation-based optimization problem where some of the objectives are expensive black-box functions that can only be evaluated through a time-consuming simulation. To efficiently solve this problem, we propose a metamodeling approach that uses an artificial neural network to replace a black-box objective function with a suitable model. This approach allows us to obtain a set of Pareto optimal points for the multiobjective problem we consider, from which decision-makers can select the most appropriate solutions for different situations. We present the results of computational experiments conducted on a real case study involving the ED of a large hospital in Italy. The results show the reliability and effectiveness of our proposed approach, compared to the standard approach based on derivative-free optimization.

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Scenario-based analysis of fast track strategy optimization on emergency department using integrated safety simulation

Cited by 21 publications

References 31 publications

SIM-PFED: A Simulation-Based Decision Making Model of Patient Flow for Improving Patient Throughput Time in Emergency Department

SIM-PFED: A Simulation-Based Decision Making Model of Patient Flow for Improving Patient Throughput Time in Emergency Department

Evaluation of Fast-Track Implementation on Emergency Department: A Literature Review

Managing low–acuity patients in an Emergency Department through simulation–based multiobjective optimization using a neural network metamodel

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