According to the CDC, over 100 million adults are living with diabetes or pre-diabetes in the United States. Given the complex approach required to help lower A1C levels and prevent or reduce diabetes complications, managing this group has posed healthcare professionals with immense challenges. KenSci’s solution provides out of box AI capabilities to risk stratify high risk population and predict time to:
The KenSci AI driven Remote Diabetes Management solution, powered by Azure IoT Connector for FHIR helps care teams remotely manage their at-risk diabetes population using real-time device data from continuous glucose monitors, activity tracking devices combined with longitudinal health record information. KenSci’s machine learning driven risk stratification and recommendation system automates the complexity of prioritizing at risk patients and surfaces the right intervention to fill gaps in Diabetes care in real time.
The deployment of this solution involves 5 key stages: