As the U.S. population ages, chronic diseases have become more prevalent. This has important implications for society in terms of healthcare costs and quality of life. One such chronic disease is diabetes, which is characterized by elevated levels of blood sugar. Diabetes exhibits significant complexity by co-occurring with other chronic diseases and interacting with other phenomena. Co-occurring diseases include hypertension, cardiovascular disease, and kidney disease, among others. Interacting factors include lifestyle, social networks, economic standing, health insurance, and the healthcare system. Key goals are to utilize computational models and other methods to study and develop solutions for care regimens, networked diagnosis and care system design, healthcare business models, and insurance/payment models.
Issues Involved or Addressed
Creating large-scale simulation models for designing diagnosis protocols and/or care networks for diabetics; Determining care capacity requirements; Specifying disease progression models of co-occurring diseases; Visualizing disease progression, treatment effectiveness, patient flows through care networks, and other phenomena; Estimating cost and patient outcomes of different treatment alternatives; Analyzing large datasets to gain insight into social effects on patient outcomes; Evaluating healthcare insurance/payment models; Specifying methods for determining and rectifying disparities; Developing serious games to identify novel healthcare business models or treatment methods; Identifying influencers of patient behavior that help or hinder treatment.
Methods and Technologies
Academic Majors of Interest
Preferred Interests and Preparation
This is a highly interdisciplinary project involving a variety of majors at Georgia Tech. The following are example interests and preparation for Georgia Tech majors, but this should not be viewed as limiting.
• Biology – disease biology, blood sugar, disease progression models
• Biomedical Engineering – disease progression models, medical interventions
• Business – public administration, public-private healthcare business models
• Computational Media – digital patient narratives, serious games
• Computer Science – computational models, simulation, machine learning, data repositories, visual analytics
• Economics – health economics, public-private enterprises, insurance, risk
• Human-Computer Interaction – graphical interface design for decision-makers, usability design for patient applications, visualization
• Industrial Engineering – simulation models, complex systems, optimization, statistics and analytics, stochastic models, Markov models and Markov decision processes
• Psychology – patient decision-making, lifestyle and treatment choices, disease psychology
• Public Policy – healthcare policy, public health, insurance, Medicare/Medicaid policy