Smart Monitoring of Complex Health Conditions (e.g., Alzheimer's Disease, Type 1 Diabetes, Surgical Site Infections)In the era of “big data”, an unprecedented opportunity is the abundance of individual data easily acquired from a wide range of perspectives over many years. These powerful sensing infrastructures hold great promises to accelerate the paradigm transition of the U.S. healthcare sector from reactive care to preventive care. In the context of a specific disease such as Alzheimer’s Disease or Type 1 diabetes, one central question is how could we translate the big disease data into better health management of millions of preclinical or diseased Americans. While many diseases manifest complex progression process, involving both temporal dynamics and spatial evolution, how could we model, monitor, and modify these processes, have been challenging, beyond the scope of either statistics or operations research alone. All these issues demand emerging technological breakthroughs rather than incremental extensions of the current methodology. Thus, the big challenge is to answer the following question: how can we transform the role of the current sensing infrastructures from passive information collection into smart monitoring, which can proactively characterize the underlying complex time-varying disease process shaped by individual’s risk factors and environmental exposures? if successful, such a “smart monitoring” method will provide powerful data-driven decision-making capabilities for better disease management, leading to more efficient targeted screening and affordable care, better treatment planning, and improved quality of life for both patients and caregivers.

The figure above illustrates the big data opportunity for Alzheimer's research and disease prevention & management