Evaluating the Effect of Centralized Administration on Health Care Performances Using Discrete-Event Simulation

2017 ◽  
Author(s):  
Chen Zhang ◽  
Hamza Hanchi ◽  
Sebastiaan Meijer
Keyword(s):  
Health Care ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Event Simulation

Discrete Event Simulation and Real Time Locating Systems

2012 ◽  
Vol 4 (4) ◽  
pp. 16-28
Author(s):  
T. Eugene Day ◽  
Ajit N. Babu ◽  
Steven M. Kymes ◽  
Nathan Ravi
Keyword(s):  
Health Care ◽  
Real Time ◽  
Discrete Event Simulation ◽  
Medical Center ◽  
Discrete Event ◽  
Healthcare Delivery ◽  
The United States ◽  
Careful Consideration ◽  
Health Administration ◽  
Event Simulation

The Veteran’s Health Administration (VHA) is the largest integrated health care system in the United States, forming the arm of the Department of Veterans Affairs (VA) that delivers medical services. From a troubled past, the VHA today is regarded as a model for healthcare transformation. The VA has evaluated and adopted a variety of cutting-edge approaches to foster greater efficiency and effectiveness in healthcare delivery as part of their systems redesign initiative. This paper discusses the integration of two health care analysis platforms: Discrete Event Simulation (DES), and Real Time Locating systems (RTLS) presenting examples of work done at the St. Louis VA Medical Center. Use of RTLS data for generation and validation of DES models is detailed, with prescriptive discussion of methodologies. The authors recommend the careful consideration of these relatively new approaches which show promise in assisting systems redesign initiatives across the health care spectrum.

scholarly journals The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review

2020 ◽  
Vol 5 (1) ◽  
pp. 238146832091524 ◽  
Author(s):  
Shiyong Liu ◽  
Yan Li ◽  
Konstantinos P. Triantis ◽  
Hong Xue ◽  
Youfa Wang
Keyword(s):  
Health Care ◽  
Discrete Event Simulation ◽  
Health Research ◽  
Care Management ◽  
Research Evaluation ◽  
Discrete Event ◽  
Health Care Management ◽  
Temporal Trends ◽  
Event Simulation ◽  
Research Areas

This study systematically examines the diffusion of the discrete event simulation (DES) approach in health services and health care management by examining relevant factors such as research areas, channels with the objective of promoting the application of DES in the health field. We examined 483 journal papers referencing this approach that were published in 230 journals during 1981 to 2014. The application of DES has extended from health service operational research evaluation to the assessment of interventions in diverse health arenas. The increase in the number of adopters (paper authors) of DES and the increase in number of related channels (journals publishing DES-related articles) are highly correlated, which suggests an increase of DES-related publications in health research. The same conclusion is reached, that is, an increased diffusion of DES in health research, when we focus on the temporal trends of the channels and adopters. The applications of DES in health research cover 22 major areas based on our categorization. The expansion in the health areas also suggests to a certain extent the rapid diffusion of DES in health research.

scholarly journals COMPARING SCHEDULING APPOINTMENT RULES PERFORMANCE IN HEALTH CARE UNITS: A DISCRETE EVENT SIMULATION APPROACH

2021 ◽  
Vol 16 (1) ◽  
pp. 28-41
Author(s):  
Thiago Nunes Klojda ◽  
Antônio Pedro de Britto Pereira Fortuna ◽  
Bianca Menezes Araujo ◽  
Daniel Bouzon Nagem Assad ◽  
Thaís Spiegel
Keyword(s):  
Health Care ◽  
Discrete Event Simulation ◽  
Health Care Systems ◽  
Waiting Times ◽  
Discrete Event ◽  
Idle Time ◽  
Event Simulation ◽  
Care Systems ◽  
Demand Scenario ◽  
Patient Waiting

Health care systems are affected by sudden increases in demand that can be generated by factors such as natural disasters, terrorist attacks, epidemics, among others. Patient demand can be divided between scheduled and walk-in and, in pandemic scenarios, both of them must be managed in order to avoid higher patient waiting times or number in queue. A discrete event simulation model is proposed in order to evaluate critical indicators like: patient waiting times, number in queue, resource utilization (doctors), using four different patient schedule appointment rules. In this study it was also considered patients impunctuality, walk-in patients and no-show in different scenarios. The best schedule appointment rules for each demand scenario were evaluated. After comparing six performance indicators, four schedule appointment rules in nine different scenarios it was found that the most known scheduling rule had the lowest queue sizes at scenarios with low or no walk-in patients, whereas, as the unpredictability of the scenarios rose, other rules outperformed it. It was also presented to exist an inverse relation between queue size and the physician idle time. Keywords: discrete event simulation, idle-time, queue management, appointment scheduling, health care.

Incorporating Discrete Event Simulation Into Quality Improvement Efforts in Health Care Systems

2013 ◽  
Vol 30 (1) ◽  
pp. 31-35 ◽  
Author(s):  
Matthew Harris Rutberg ◽  
Sharon Wenczel ◽  
John Devaney ◽  
Eric Jonathan Goldlust ◽  
Theodore Eugene Day
Keyword(s):  
Health Care ◽  
Quality Improvement ◽  
Discrete Event Simulation ◽  
Health Care Systems ◽  
Discrete Event ◽  
Event Simulation ◽  
Care Systems
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