Achieving 150 active minutes a week and 5%-7% weight loss reduces risk of developing type 2 diabetes by 58% (71% if you’re over age 60)
We believe that every individual should live a healthier lifestyle. Currently, no scalable and cost-effective solution exists that helps the prediabetic population, therefore providing some sort of guidance is vital. Sweetch reduces the risk of diabetes and improves outcomes of chronic diseases by implementing a personalized intervention that focuses on emotional support and motivation to drive behavior change.
84 million Americans, 63 million Europeans, 493 million Chinese are at risk for type 2 diabetes.
Prediabetes is actually diabetes in its early stage. Prediabetes increases the risk of developing type 2 diabetes, heart disease, and stroke.
Currently, there is no accurate and reliable method to predict who will develop type 2 diabetes and when. In addition, current Diabetes Prevention Programs (DPP) rely on human coaching which presents two significant hurdles - scalability and cost.
Prediction of individual’s diabetes conversion risk
Smartphone and wearables which monitor user’s life habits and behavior
Smartphone sensors, personal habits and preferences, calendar, geolocation, maps, weather information and more
The Feedback Loop: personalized and contextual real-time recommendations, which continuously adapt to the user’s behavior
Sweetch developed a proprietary machine-learning platform that predicts an individual’s 3-year risk for developing Metabolic Syndrome related diseases – type 2 diabetes, hypertension, hyperlipidemia, and obesity.
This risk stratification is critical for early intervention and cost-effective resource allocation by healthcare providers and payers, as it enables to focus on people at highest risk for chronic conditions. A large portion of the prediabetic population are not clinically obvious high-risk patients, on the contrary – they are young, have slightly elevated blood glucose and are slightly overweight.
The idea is to turn the usual, general, and less effective recommendations of “walk 10,000 steps / for 30 minutes a day” and “eat less carbohydrates” into personal, contextual, real-time, recommendations promoting an increase in physical activity, weight loss, and enhancement of health and nutrition.
Sweetch’s health platform automatically turns various smartphone-originated data streams – geolocation, schedule, activity patterns, driving and walking routes, weather, surroundings and more – into personalized and contextual recommendations that guide the user, in real-time, toward achieving the desired goals. Recommendations are continuously adapted to the user’s behavior, promoting a unique set of life habits and motivations.