This paper explores the automation of healthcare process modeling using process mining and simulation for Chronic Obstructive Pulmonary Disease (COPD) clinical pathways. By integrating AnyLogic’s agent-based simulation with real-world hospitalization data, the study is able to validate process-mined models. This approach optimizes patient flow analysis and supports data-driven decision-making in healthcare process automation.
This paper illustrates an emergency response simulation for out-of-hospital cardiac arrest (OHCA) incidents using agent-based modeling and GIS integration. The authors applied AnyLogic simulation software to evaluate dispatch strategies and responder deployment, with the goal of improving survival rates and enhancing urban emergency response efficiency.
This study explores the role of healthcare resilience in emergency departments. An AnyLogic simulation model is used to assess cross-training strategies. The study identifies the most effective workforce flexibility policies to reduce patient waiting times and optimize resource allocation by simulating real-world emergency department operations. The findings highlight how cross-training nurses between triage, adult, and pediatric zones enhances healthcare resilience, ensuring efficient emergency care during patient demand surges.
This study explores the use of healthcare simulation in measuring and improving the resilience of emergency departments (EDs) during demand surges. The model uses AnyLogic discrete-event simulation to replicate patient flow, resource allocation, and response strategies to identify effective interventions. The research provides valuable insights for ED managers seeking to enhance operational efficiency and patient care under pressure.
Predictive modeling in healthcare is crucial in assessing interventions for continuous care, especially for cardiovascular disease (CVD) patients affected by natural disasters. This study uses agent-based modeling in predictive simulation software to forecast health outcomes and plan effective public health interventions. By simulating hurricane events and patient responses, the research highlights the impact of medication adherence and disaster preparedness on reducing CVD mortality.
In this study, researchers investigated the process of orthopedic treatment in an Australian health service, from the point of referral to surgical intervention. In a number of cases, surgical intervention could be avoided through participation in community-based rehabilitation programs.
Blood supply chains are an essential element of healthcare systems. Simulation provides the means to test out digital innovations for blood supply chains regarding their operational efficiency and expected costs.
A discrete event simulation model was developed for a network of eight major intensive care units (ICUs) as well as high-acuity units (HAUs) in British Columbia, Canada. The simulation model will be used to develop strategies for managing the combined impacts of COVID-19 and seasonal influenza without the need for extensive public health interventions to limit transmission.
Demands for health care are becoming overwhelming for healthcare systems around the world regarding the availability of resources, particularly in emergency departments (EDs). This paper provides a case study of the Uppsala University Hospital, where a data-driven simulation model was designed to examine the current state of the patient flow and to investigate potential logistics solutions for improving that flow through a novel strategy.
The Covid-19 virus has substantially transformed many aspects of life, impacted industries, and revolutionized supply chains all over the world. System dynamics modeling can aid in predicting future outcomes of the pandemic and generate key learnings. This tutorial describes how the system dynamics simulation model was constructed for the Covid-19 pandemic using AnyLogic Software. The model serves as a general foundation for further epidemiological simulations and system dynamics modeling.