scholarly journals Patient Flow Simulation Using Historically Informed Synthetic Data

2021 ◽  
Author(s):  
Ezra Kenny ◽  
Hamed Hassanzadeh ◽  
Sankalp Khanna ◽  
Justin Boyle ◽  
Sandra Louise
Keyword(s):  
Emergency Department ◽  
Simulation Model ◽  
Patient Flow ◽  
Discrete Event ◽  
Synthetic Data ◽  
Flow Simulation ◽  
Average Patient ◽  
Future Demands ◽  
Healthcare Administrators ◽  
Using Data

Hospital overcrowding is a major problem for healthcare systems around the globe. In order to better estimate future demands and adequate resources for coping with such demands, statistical and computerised modelling can be applied. This can then allow healthcare administrators and decision makers to quantify the impacts of various “what-if” scenarios on hospital performance measures. This paper investigates the application of Discrete Event Simulation towards optimising Emergency Department resources while measuring overall length of stay and queuing time of emergency patients as a target performance measure. In particular, we explore strategies for generating historically informed synthetic data that helps the simulation model track patient flow through the target hospital over a future time frame. Using the developed simulation model, several resource configurations are tested using data from one of the busiest emergency departments in the state of Queensland as the baseline while quantifying the impacts of such changes on key patient flow metrics. It was found that adding a single bed (and associated resources) to the emergency department would result in a 23% decrease in average patient treatment delay.

scholarly journals Modeling, Assessment and Design of an Emergency Department of a Public Hospital through Discrete-Event Simulation

2021 ◽  
Vol 11 (2) ◽  
pp. 805
Author(s):  
Alexandre Castanheira-Pinto ◽  
Bruno S. Gonçalves ◽  
Rui M. Lima ◽  
José Dinis-Carvalho
Keyword(s):  
Emergency Department ◽  
Simulation Model ◽  
Emergency Departments ◽  
Patient Flow ◽  
Waiting Times ◽  
Discrete Event ◽  
Analytical Description ◽  
Northern Region ◽  
Optimized Design ◽  
Initial State

Emergency departments in hospitals are having many difficulties in achieving the performance levels required by health regulators and society. The waiting times as well as the total throughput time are examples of performance indicators that emergency departments need to improve in order to provide a better service to the community. To achieve improvement of performance, the present paper shows a methodology to assist the design process of an emergency department using simulation techniques. In this study, the emergency department of a hospital located in the northern region of Portugal was considered to test the proposed simulation technique. The emergency department initial state was assessed, in terms of patient flow, as well as the human resources needed at every stage of the service. In order to understand in depth the process that a patient goes through during an emergency episode, a comprehensive study was performed on the hospital database. This allowed the analytical description of an emergency episode, which was further used as an input to the simulation model. After developing the simulation model with the information obtained by the hospital’s database, a validation stage was performed. Finally, in order to achieve an optimized design for the emergency department several variant scenarios were considered and evaluated. This methodology proved to be very useful in determining an optimized operation for complex, and non-linear systems.

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

A Simulation Model for Resource Balancing in Healthcare Systems

2017 ◽  
pp. 78-93
Author(s):  
Arzu Eren Şenaras ◽  
Hayrettin Kemal Sezen
Keyword(s):  
Health Care ◽  
Emergency Department ◽  
Simulation Model ◽  
Waiting Times ◽  
Discrete Event ◽  
Healthcare Systems ◽  
Event Simulation ◽  
Package Program ◽  
Effective Policy ◽  
Very High

This study aims to analyze resource effectiveness through developed model. Changing different number of resources and testing their response, appropriate number of resources can be identified as a basis of resource balancing through what-if analysis. The simulation model for emergency department is developed by Arena package program. The patient waiting times are reduced by the tested scenarios. Health care system is very expensive sector and related costs are very high. To raise service quality, number of doctor and nurse are increased but system target is provided by increased number of register clerk. Testing different scenarios, effective policy can be designed using developed simulation model. This chapter provides the readers to evaluate healthcare system using discrete event simulation. The developed model could be evaluated as a base for new implementations in other hospitals and clinics.

A Simulation Model for Resource Balancing in Healthcare Systems

2020 ◽  
pp. 336-351
Author(s):  
Arzu Eren Şenaras ◽  
Hayrettin Kemal Sezen
Keyword(s):  
Health Care ◽  
Emergency Department ◽  
Simulation Model ◽  
Waiting Times ◽  
Discrete Event ◽  
Healthcare Systems ◽  
Event Simulation ◽  
Package Program ◽  
Effective Policy ◽  
Very High

This study aims to analyze resource effectiveness through developed model. Changing different number of resources and testing their response, appropriate number of resources can be identified as a basis of resource balancing through what-if analysis. The simulation model for emergency department is developed by Arena package program. The patient waiting times are reduced by the tested scenarios. Health care system is very expensive sector and related costs are very high. To raise service quality, number of doctor and nurse are increased but system target is provided by increased number of register clerk. Testing different scenarios, effective policy can be designed using developed simulation model. This chapter provides the readers to evaluate healthcare system using discrete event simulation. The developed model could be evaluated as a base for new implementations in other hospitals and clinics.

scholarly journals How an election can be safely planned and conducted during a pandemic: Decision support based on a discrete event model

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261016
Author(s):  
Nadine Weibrecht ◽  
Matthias Rößler ◽  
Martin Bicher ◽  
Štefan Emrich ◽  
Günther Zauner ◽  
...  
Keyword(s):  
Simulation Model ◽  
Social Life ◽  
Discrete Event ◽  
The Novel ◽  
Event Simulation ◽  
District Council ◽  
Event Model ◽  
Using Data ◽  
The One ◽  
Democratic Elections

In 2020, the ongoing COVID-19 pandemic caused major limitations for any aspect of social life and in specific for all events that require a gathering of people. While most events of this kind can be postponed or cancelled, democratic elections are key elements of any democratic regime and should be upheld if at all possible. Consequently, proper planning is required to establish the highest possible level of safety to both voters and scrutineers. In this paper, we present the novel and innovative way how the municipal council and district council elections in Vienna were planned and conducted using an discrete event simulation model. Key target of this process was to avoid queues in front of polling stations to reduce the risk of related infection clusters. In cooperation with a hygiene expert, we defined necessary precautions that should be met during the election in order to avoid the spread of COVID-19. In a next step, a simulation model was established and parametrized and validated using data from previous elections. Furthermore, the planned conditions were simulated to see whether excessive queues in front of any polling stations could form, as these could on the one hand act as an infection herd, and on the other hand, turn voters away. Our simulation identified some polling stations where long queues could emerge. However, splitting up these electoral branches resulted in a smooth election across all of Vienna. Looking back, the election did not lead to a significant increase of COVID-19 incidences. Therefore, it can be concluded that careful planning led to a safe election, despite the pandemic.

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