Academic articles

Simulation Model of a Multi-Hospital Critical Care Network

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.

A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics

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.

A Tutorial on How to Set Up a System Dynamics Simulation on the Example of Covid-19 Pandemic

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.

Creating Simulated Equivalents to Project Long-Term Population Health Outcomes of Underserved Patients

Simulation models can be used to project the long-term outcomes associated with implementing a public health intervention or program at the population level. The main goal of simulation modeling in this paper was to estimate the long-term colorectal cancer outcomes associated with a first screening through the Colorectal Cancer Control Program among low-income and underserved patients in the U.S.

Assessing Resilience of Medicine Supply Chain Networks to Disruptions: a Proposed Hybrid Simulation Modeling Framework

This paper introduces a simulation study of interventions to ensure a stable supply of a generic medicine in Norway. A hybrid simulation modeling framework is proposed to evaluate the effect of alternative supply chain shortage interventions in response to various disruptions to support national decision making with respect to preparedness planning and emergency response.

Planning and Management of Hospitals and Other Healthcare Facilities: Layout Comparison

Factors including hospital space layout, patient behavior, patient flow, and medical procedures interact and relate to each other, and ultimately affect efficiency and performance of healthcare facilities. And hospital layout planning can’t ignore such interdependencies.

This research integrates discrete event simulation (DES) and agent-based simulation (ABS) to help managers examine, plan, and compare different spatial design schemes through the modeling of patient behavior, patient flow, and the establishment of evaluation indexes.

Developing an ED Overcrowding Solution to Improve the Quality of Care

Overcrowding in the Emergency Department (ED) is one of the most important issues in healthcare systems. The lack of downstream beds can affect the quality of care for patients who need hospitalization after an ED visit.

This research proposes a generic simulation model as one of the ED overcrowding solutions to analyze patient pathways from the ED to hospital discharge. The model is adaptable for all pathologies and can include several hospitals within a healthcare network. To identify relevant pathways the research team conducts pathway analysis using Process Mining.

Using Diabetic Retinopathy Care Process Model to Evaluate Interventions

Diabetic retinopathy is a diabetes complication that affects eyes. It’s also the leading cause of blindness for working-age Americans. Early detection, timely treatment, and appropriate follow-up care reduce the risk of severe vision loss from DR by 95%. Unfortunately, less than 50% of people with diabetes follow the recommended eye care screening guidelines.

The research team developed a diabetic retinopathy care process model integrating the natural history of diabetic retinopathy with a patient’s interaction with the care system.