Medial EarlySign is building a suite of AI-based population health and clinical decision support solutions to improve the prognosis and treatment capacity for patients. Powered by our cognitive algorithms that analyze ordinary medical data to decode hidden warning signs, the system identifies “subtle signals” within readily available EHR and low-cost laboratory data, with the ability to ‘flag’ those individuals with a higher risk for a targeted outcome.
These tools can help physicians and Care Managers identify life-altering health risks in patients at an earlier stage, resulting in a smarter and more efficient healthcare system that provides personalized, timely medical treatments, and leading to better outcomes for all stakeholders.
Medial EarlySign focuses on identifying those ‘rising risk’ individuals in the population who are most likely to become tomorrow’s high burden patients, in time for preventative action to be taken. This 5% of the population will eventually account for 50% of healthcare costs. We are currently at various stages of development of dozens of AlgoMarkersTM for a variety of outcomes. Our work ranges from early prediction of cancers to personalized and outcome based interpretation of lab results, flagging diabetics at risk of nephropathy to data-driven risk tools for patients.
ColonFlag is the first solution we introduced to the medical world. It helps healthcare providers identify people with a high probability of having colorectal cancer (CRC), often long before any symptoms appear. Applying sophisticated algorithms, built and validated on data from millions of individuals around the world, ColonFlag picks up hidden signals in routine blood tests and flags high-risk individuals. The system then alerts physicians and Care Managers to contact their patients for further, immediate evaluation (e.g. colonoscopy).
ColonFlag bears CE and is not yet cleared by FDA for commercial use in the USA