Develop Theories and Methodologies for Improved Treatment Times in Integrated Emergency Department Systems

Emergency Departments (ED) struggle to deliver treatments to specific diseases efficiently. Often the root cause of the treatment delays are upstream or downstream of the ED because the health care system is interconnected. Furthermore, the consequences of delayed treatment often occur significantly downstream of the ED. Therefore, we need to better understand these external factors and develop models and simulations that consider factors that are outside of the ED to fully characterize the issues. Through this research program, I aim to develop theories and methodologies to substantially improve treatment times leading to better patient outcomes. The methodology to carry out this research program will have three key themes: 1. Understand the association of external factors on efficiency of ED treatment through data analytics and visualizations - Health data can help us to better understand the details of interconnectedness with upstream and/or downstream variables. Health data is increasingly becoming available, and with data linkages at the patient level, it is possible to obtain rich and big datasets. Data analytics and novel interactive visualizations of the data can reveal patterns of the interplay of upstream and downstream variables. Novel interactive visualizations and data analytics through the development of statistical models can reveal the association with external variables 2. Develop mathematical models to minimize ED treatment times - Mathematical models using operations research methodology will be developed to minimize time to ED treatment for stroke and heart attack. The modeling will include: linear programming, non-linear programming, and stochastic models. These optimization models can provide new benchmarks for ED treatment of specific diseases. 3. Develop computer simulation of the ED treatment process for specific diseases incorporating external factors - Discrete-event computer simulation models will be developed for the ED treatment process of specific diseases such as stroke and heart attack. These simulations will be used to test various scenarios prior to implementing the changes to better understand the effects of the changes on treatment efficiency. The key outputs from this research program will include novel interactive visualizations, mathematical models, and accurate simulations that optimize ED treatment times for specific diseases. In the first 5 years, there will be 5 Master's and 2 PhD students working on specific aspects of this research program.