Thrust 2

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

Integration with Emerging Health Management Tools: Mobile health (mHealth) technology is providing great opportunities to enhance various healthcare practices. There are billions of smartphone users worldwide who will use a healthcare application. While mHealth tools, together with the innovations in other health information technologies, are enhancing our data collection, communication, and healthcare delivery capacities, these tools need to be equipped with smart decision-making methodologies to maximize their impact in real-world healthcare settings. The Figure below shows the user interface of a mobile monitoring tool, named as mPOWEr, for which we have been developing and implementing our methodologies for disease progression modeling, risk monitoring, and prediction, etc. mPOWEr is developed for monitoring surgical patients by collecting data such as pre-operative variables, individual’s clinical and physiological variables, operative variables, post-operative variables, and outcomes. It includes a patient-facing mobile app and provider-facing web-based reporting dashboard that will provide a secure solution to remotely monitor surgical wounds for infection. mPOWEr will be a critical approach for filling in the gap in the care process, particularly for the surgical patients after discharge.

The figure above comes from http://mpowercare.org. More details about mPOWEr and the interdisciplinary research team can be found from http://mpowercare.org.