I-Corps: A real-time dietary decision support system for the prevention and management of diabetes.

University Of Texas, M.D. Anderson Cancer Center, Houston TX

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is to improve dietary compliance and health outcomes in diabetic and pre-diabetic populations. Almost 30 million Americans adults have Type II diabetes. Type II diabetes is a serious public health concern, as its complications, which include cardiovascular disease, kidney failure, blindness and amputations, greatly affect patients' health and quality of life. To effectively self-manage their disease, patients face the difficult task of controlling their glucose levels by following dietary guidance and preventing excessive weight gain. Digital health products have the potential to improve patient adherence to these recommendations by providing real-time, interactive self-management aid. Yet, existing mobile diabetes self-management applications are limited to their function as glucose trackers. The goal of the proposed project is to develop a proactive diet-related decision-making support system that is personalized to continuously monitored glucose concentrations. The integration of software and sensor technology will result in a more efficient and individualized method to prevent disease progression in Type II diabetics. This I-Corps project examines the commercial feasibility of using biological inputs from wearable sensors to eliminate the need for calorie-tracking and develop personalized and dynamic real-time food-related decision support. Our proprietary algorithms use continuous glucose readings as biological feedback to assist diabetic patients with decisions about what and when to eat. Previous studies have demonstrated improved glycemic control and sustained weight loss using portable glucometers to improve self-regulated eating behavior in overweight non-diabetic populations. The proposed technology will translate this evidence-based biobehavioral intervention approach to Type 2 and pre-diabetic patients in real-time. The user interface will be a mobile platform with graphical outputs to assist with 'in-the-moment' decision-making as well as to monitor their glucose variability. The platform will provide summary statistics for patients that can be shared with their healthcare providers.