Resumen de Simulación para investigar el impacto de factores dependientes e independientes en el sistema del departamento de emergencias utilizando computación de alto rendimiento y modelado basado en agentes
Increased life expectancy, and population aging in Spain, along with their corresponding health conditions such as non-communicable diseases (NCDs), have been suggested to contribute to higher demands on the Emergency Department (ED).
Spain is one of such countries which an ED is occupied by a very high burden of patients with NCDs. They very often need to access healthcare systems and many of them need to be readmitted even though they are not in an emergency or dangerous situations.
Furthermore many NCDs are a consequence of lifestyle choices that can be controllable. Usually, the living conditions of each chronic patient affect health variables and change the quantity of these health variables, so they can change the stability situation of the patients with NCDs to instability and its resultant will be visiting ED.
In this study, a new method for the prediction of future performance and demand in the emergency department (ED) in Spain is presented. Prediction and quantification of the behavior of ED are, however, challenging as ED is one of the most complex parts of hospitals. Future years of Spain’s ED behavior was predicted by the use of detailed computational approaches integrated with clinical data. First, statistical models were developed to predict how the population and age distribution of patients with non-communicable diseases change in Spain in future years. Then, an agent-based modeling approach was used for simulation of the emergency department to predict impacts of the changes in population and age distribution of patients with NCDs on the performance of ED, reflected in hospital LoS, between years 2019 and 2039.
Then in another part of this study, we propose a model that helps to analyze the behavior of chronic disease patients with a focus on heart failure patients based on their lifestyle. We consider how living conditions affect the signs and symptoms of chronic disease and, accordingly, how these signs and symptoms affect chronic disease stability. We use an agent-based model, a state machine, and a fuzzy logic system to develop the model. Specifically, we model the required 'living condition' parameters that can influence the required medical variables. These variables determine the stability class of chronic disease.
This thesis also investigates the impacts of Tele-ED on behavior, time, and efficiency of ED and hospital utilization. Then we propose a model for Tele-ED which delivers the medical services online.
Simulation and Agent-based modeling are powerful tools that allow us to model and predict the behavior of ED as a complex system for a given set of desired inputs. Each agent based on a set of rules responds to its environment and other agents. This thesis can answer several questions in regards to the demand and performance of ED in the future and provides health care providers with quantitative information on economic impact, affordability, required staff, and physical resources. Prediction of the behavior of patients with NCDs can also be beneficial for health policy to plan for increasing health education in the community, reduce risky behavior, and teaching to make healthy decisions in a lifetime. Prediction of behavior of Spain’s ED in future years can help care providers for decision-makers to improve health care management.
