Modeling and Analysis of the Emergency Department at University of Kentucky Chandler Hospital Using Simulations

Brenner, Stuart; Zeng, Zhen; Liu, Yang; Wang, Junwen; Li, Jingshan; Howard, Patricia Kunz

doi:10.1016/j.jen.2009.07.018

Cited by 109 publications

(65 citation statements)

References 3 publications

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“…The vast majority of models are very unit specific. Approaches taken include assessment of working practices [1,[3][4][5], shift patterns [5], equipment bottlenecks [9], and in some cases, patient pathways themselves [20]. Interactions of ED patient flow with the wider hospital context are clearly also important [7], and examination of these interactions can be achieved using DES models, or sometimes may be better analysed by other techniques [29,32].…”

Section: Pathway Redesign In Emergency Departmentsmentioning

confidence: 99%

Redesigning the diagnostic pathway for chest pain patients in emergency departments

Rachuba

Salmon

Zhelev

et al. 2017

Health Care Manag Sci

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Patients presenting with chest pain at an emergency department in the United Kingdom receive troponin tests to assess the likelihood of an acute myocardial infarction (AMI). Until recently, serial testing with two blood samples separated by at least six hours was necessary in order to analyse the change in troponin levels over time. New high-sensitivity troponin tests, however, allow the inter-test time to be shortened from six to three hours. Recent evidence also suggests that the new generation of troponin tests can be used to rule out AMI on the basis of a single test if patients at low risk of AMI present with very low cardiac troponin levels more than three hours after onset of worst pain. This paper presents a discrete event simulation model to assess the likely impact on the number of hospital admissions if emergency departments adopt strategies for serial and single testing based on the use of high-sensitivity troponin. Data sets from acute trusts in the South West of England are used to quantify the resulting benefits.

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Section: Pathway Redesign In Emergency Departmentsmentioning

confidence: 99%

Redesigning the diagnostic pathway for chest pain patients in emergency departments

Rachuba

Salmon

Zhelev

et al. 2017

Health Care Manag Sci

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“…Studies include making strategic decisions for various departments (Ballard and Kuhl, 2006;Denton et al, 2006;Vanberkel and Blake, 2007;Leskovar et al, 2011); estimating capacity levels and measuring waiting times (Werker et al, 2009); analysing patient flows (Brenner et al, 2010;Zeng et al, 2012); measuring policy impact (Fletcher et al, 2007); and simulating patient scheduling and utilisations (Harper and Gamlin, 2003;Werker et al, 2009;Lee et al, 2013;Quevedo and Chapilliquén, 2014). It has been argued that the extensive use of process modelling is limited in healthcare compared with other industries (Harper and Pitt, 2004) due to the complexity of the processes and the vast amounts of data required to provide accurate models (Antonacci et al, 2016).…”

Section: Related Workmentioning

confidence: 99%

Maximising Patient Throughput using Discrete-event Simulation

Greenroyd

Hayward

Price

et al. 2017

Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications

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“…For example, much media attention has focused on Emergency Units (EU), often reporting long waits for arriving patients until they are seen by a healthcare professional (see for example [4]). Consequently, EU's have been the focus of much research [2,6,10,28].…”

Section: Introductionmentioning

confidence: 99%

Using Singular Spectrum Analysis to obtain staffing level requirements in emergency units

Gillard

Knight

2014

Journal of the Operational Research Society

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Many Operational Research (OR) techniques use historical data to populate model input parameters. Although the majority of these models take into account stochastic variation of the inputs, they do not necessarily take into account seasonal variations and other stochastic effects that might arise. One of the major applications of OR lies within healthcare, where ever increasing pressure on healthcare systems is having major implications on those who plan the provision of such services. Coping with growing demand for healthcare, as well as the volatile nature of the number of arrivals at a healthcare facility makes modelling healthcare provision one of the most challenging fields of OR. This paper proposes the use of a relatively modern time series technique, Singular Spectrum Analysis (SSA), to improve existing algorithms that give required staffing levels. The methodology is demonstrated using data from a large teaching hospital's emergency unit. Using time dependent queueing theory, as well as SSA, staffing levels are obtained. The performance of our technique is analysed using a weighted mean square error measure, introduced in this paper.

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Modeling and Analysis of the Emergency Department at University of Kentucky Chandler Hospital Using Simulations

Cited by 109 publications

References 3 publications

Redesigning the diagnostic pathway for chest pain patients in emergency departments

Redesigning the diagnostic pathway for chest pain patients in emergency departments

Maximising Patient Throughput using Discrete-event Simulation

Using Singular Spectrum Analysis to obtain staffing level requirements in emergency units

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