A hybrid agent-based and Discrete Event Simulation approach for sustainable strategic planning and simulation analytics

2014 ◽  
Author(s):  
Masoud Fakhimi ◽  
Anastasia Anagnostou ◽  
Lampros Stergioulas ◽  
Simon J. E. Taylor
Keyword(s):  
Strategic Planning ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Approach ◽  
Agent Based ◽  
Event Simulation ◽  
Hybrid Agent

scholarly journals Modeling Clinical Outcomes in Prostate Cancer: Application and Validation of the Discrete Event Simulation Approach

2018 ◽  
Vol 21 (4) ◽  
pp. 416-422 ◽  
Author(s):  
Feng Pan ◽  
Odette Reifsnider ◽  
Ying Zheng ◽  
Irina Proskorovsky ◽  
Tracy Li ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Outcomes ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Approach ◽  
Event Simulation

Reducing Handoffs and Improving Patient Flow in the ED

2021 ◽  
Author(s):  
Vishnunarayan Girishan Prabhu ◽  
Kevin Taaffe ◽  
Ronald Pirrallo ◽  
William Jackson ◽  
Michael Ramsay
Keyword(s):  
Performance Metrics ◽  
Patient Flow ◽  
Discrete Event ◽  
Common Source ◽  
Agent Based ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Healthcare Settings ◽  
Shift Schedules ◽  
Hybrid Agent

Abstract Over 145 million people visit US Emergency Departments annually. The diverse nature and overwhelming volume of patient visits make the ED one of the most complicated healthcare settings. In particular, handoffs, the transfer of patient care from one physician to another during shift transition are a common source of errors resulting from workflow interruptions and high cognitive workload. This research focuses on developing a hybrid agent-based discrete event simulation model to identify physician shifts that minimize handoffs without affecting other performance metrics. By providing overlapping shift schedules as well as implementing policies that restrict physicians from signing up a new patient during the last hour of the shift, we observed that handoffs and patient time in the emergency department could be reduced by as much as 42% and 17%, respectively.

Multi-Methodology Approach

2021 ◽  
pp. 98-128
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multiple Methods ◽  
Soft Systems ◽  
Agent Based ◽  
Event Simulation ◽  
Pluralistic Approach ◽  
The Difference

The pluralistic approach in today's world needs combining multiple methods, whether hard or soft, into a multi-methodology intervention. The methodologies can be combined, sometimes from several different paradigms, including hard and soft, in the form of a multi-methodology so that the hard paradigms are positivistic and see the organizational environment as objective, while the nature of soft paradigms is interpretive. In this chapter, the combination of methodologies has been examined using soft systems methodologies (SSM) and simulation methodologies including discrete event simulation (DES), system dynamics (SD), and agent-based modeling (ABM). Also, using the ontological, epistemological, and methodological assumptions underlying the respective paradigms, the difference between SD, ABM, SSM; a synthesis of SSM and SD generally known as soft system dynamics methodology (SSDM); and a promising integration of SSM and ABM referred to as soft systems agent-based methodology (SSABM) have been proven.

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