A discrete event simulation to evaluate impact of radiology process changes on emergency department computed tomography access

2021 ◽  
Author(s):  
Kayse Lee Maass ◽  
Elizabeth Halter ◽  
Todd R. Huschka ◽  
Mustafa Y. Sir ◽  
Michelle R. Nordland ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Emergency Department ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Event Simulation

scholarly journals Factors Influencing Door-To-Doctor Time In An Emergency Department: Discrete Event Simulation Model

2016 ◽  
Vol 19 (7) ◽  
pp. A624 ◽  
Author(s):  
RA Ribeiro ◽  
EN Baungratz ◽  
G Vaccaro ◽  
PS Schmitz ◽  
AK Fernandes ◽  
...  
Keyword(s):  
Emergency Department ◽  
Simulation Model ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Factors Influencing

Capacity Decision in Emergency Hospital Operation Rooms

2018 ◽  
pp. 140-155
Author(s):  
Ana Carolina Pereira de Vasconcelos Silva ◽  
Daniel Bouzon Nagem Assad ◽  
Thais Spiegel
Keyword(s):  
Emergency Department ◽  
Problem Solving ◽  
Discrete Event Simulation ◽  
Operations Management ◽  
Discrete Event ◽  
Design Management ◽  
Simulation Tool ◽  
Event Simulation ◽  
Production Distribution ◽  
Capacity Decision

The operations management is a multidisciplinary field that investigates, for instance, the design, management and processes improvement focused on the development, production, distribution and delivery of products and services, encompassing activities such as the implementation of policies, making quota decisions, identification and problem solving, response to uncertainty, among others. Regarding the resources dimensioning in hospitals, the Brazilian scenario is limited to legislative instruments that assume a prior and added sizing. This chapter uses a discrete event simulation tool to set the amount of operation rooms needed for patient care in an emergency department, so that emergency patients have guaranteed compliance, minimizing the cancellation of elective surgeries because of this type of demand. As a result, it was found that the minimum amount established by normative instruments was not appropriate to the specific requirements of the organization.

Uncovering effective process improvement strategies in an emergency department using discrete event simulation

2014 ◽  
Vol 3 (2) ◽  
pp. 93-104 ◽  
Author(s):  
Oh Hong Choon ◽  
Zhang Dali ◽  
Phua Tien Beng ◽  
Chow Peck Yoke Magdalene
Keyword(s):  
Emergency Department ◽  
Discrete Event Simulation ◽  
Process Improvement ◽  
Discrete Event ◽  
Event Simulation ◽  
Improvement Strategies

scholarly journals Lean healthcare integrated with discrete event simulation and design of experiments: an emergency department expansion

2019 ◽  
Author(s):  
Gustavo Teodoro Gabriel ◽  
Afonso Teberga Campos ◽  
Aline de Lima Magacho ◽  
Lucas Cavallieri Segismondi ◽  
Flávio Fraga Vilela ◽  
...  
Keyword(s):  
Emergency Department ◽  
Confidence Interval ◽  
Design Of Experiments ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Optimal Number ◽  
Management Tools ◽  
Lean Principles ◽  
Event Simulation ◽  
Lean Healthcare

Background. Discrete Event Simulation (DES) and Lean Healthcare are management tools that are efficient and assist in the quality and efficiency of health services. In this sense, the purpose of the study is to use lean principles jointly with DES to plan the expansion of a Canadian emergency department and to the demand that comes from small closed care centers. Methods. For this, we used simulation and modeling method. We simulated the emergency department in FlexSim Healthcare® software and, with the Design of Experiments (DoE), we defined the optimal number of locations and resources for each shift. Results. The results show that the ED cannot meet expected demand in the current state. Only 17.2% of the patients were completed treated, and the Length of Stay (LOS), on average, was 2213.7, with a confidence interval of (2131.8 - 2295.6) minutes. However, after changing decision variables, the number of treated patients increased to 95.7% (approximately 600%). Average LOS decreased to 461.2, with a confidence interval of (453.7 - 468.7) minutes, about 79.0%. In addition, the study shows that emergency department staff are balanced, according to Lean principles.

Effect of different patient peak arrivals on an emergency department via discrete event simulation: a case study

SIMULATION ◽  
2021 ◽  
pp. 003754972110387
Author(s):  
Giordano Fava ◽  
Tommaso Giovannelli ◽  
Mauro Messedaglia ◽  
Massimo Roma
Keyword(s):  
Emergency Department ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Central Italy ◽  
Healthcare Management ◽  
Critical Event ◽  
Medium Size ◽  
Event Simulation ◽  
Des Model

Emergency department (ED) overcrowding is a well-recognized worldwide phenomenon which affects the quality of emergency care. A direct consequence of overcrowding is a long wait for visit and treatment of people who require primary care, possibly endangering the lives of critical patients. Healthcare management literature devoted to analyze ED operational policies is very wide, and many approaches have been proposed to address this important problem. However, less attention has been given to patient peak arrivals caused by the occurrence of some critical events which can strongly strain the operational efficiency of an ED. In this paper, we consider the particular case study of a medium-size ED located in a region of Central Italy recently hit by a severe earthquake, aiming at assessing the effects of such an occurrence on the ED operation. In particular, we propose a discrete event simulation (DES) model to analyze the patient flows through this ED, simulating unusual operational conditions due to a critical event, like a natural disaster, which causes a sudden spike in the number of patient arrivals. The availability of detailed data concerning the ED processes enabled building an accurate DES model and performing extensive scenario analyses. The model provides a valid decision support system for the ED managers in assessing specific emergency plans to be activated in case of mass casualty disasters.

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