LGI Flag, a machine learning-based solution developed by health care technology pioneer Medial EarlySign, an Israeli company will be implemented this month in  SLUCare patient-care offices. The clinical risk identification tool will use ordinary medical data to help flag patients at greater risk of harboring lower GI disorders associated with chronic occult bleeding such as colorectal cancer, precancerous adenomas, polyps, irritable bowel disease, ulcers, and diverticulitis.

The system flags patients using ordinary data, collected over the course of routine care, and sophisticated machine learning techniques, enabling health care providers to focus attention on patients who are most likely to benefit from further evaluation and possible intervention, review their charts, and determine next steps.

"The ability to identify high-risk patients sooner and intervene with them earlier enables us to help improve care and long-term survival rates," said William Manard, MD, SLUCare Family and Community Medicine physician and Chief Medical Informatics Officer. "Earlier detection and treatments for lower GI disorders can also lead to improved and more manageable outcomes. This is an ideal way to use technology to deliver a higher quality of care for our patients in the greater St. Louis community."

Medial EarlySign spent years investigating existing electronic health record data with leading international health care providers to determine what insights could be gained by applying machine learning techniques to routine medical data. EarlySign is now working closely with SLUCare to effectively deploy these algorithms in its clinical workflow. 

SLUCare and Medial EarlySign were introduced to one another through the BioSTL initiative GlobalSTL, a St. Louis-based organization that recruits high-growth companies from around the world to enrich and expand St. Louis's innovation economy and bring competitive advantages to local corporations and health systems.