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Stanford Researchers Use Big Data to Identify Patients at Risk of High-Cholesterol Disorder

Stanford University (01/29/15) Tracie White

Stanford University researchers have launched a project designed to identify hospital patients who may have a genetic disease that causes a deadly buildup of cholesterol in their arteries. The project uses big data and software that can learn to recognize patterns in electronic medical records and identify patients at risk of familial hypercholesterolemia (FH), which often goes undiagnosed until a heart attack strikes. The project is part of a larger initiative called Flag, Identify, Network, Deliver FH, which aims to use innovative technologies to identify individuals with the disorder who are undiagnosed, untreated, or undertreated. For the project, researchers will teach a program how to recognize a pattern in the electronic records of Stanford patients diagnosed with FH. The program then will be directed to analyze Stanford patient records for signs of the pattern, and the researchers will report their findings to the patients’ personal physicians, who can encourage screening and therapy. “These techniques have not been widely applied in medicine, but we believe that they offer the potential to transform healthcare, particularly with the increased reliance on electronic health records,” says Stanford professor Joshua Knowles. If the project is successful at Stanford, it will be tested at other academic medical centers.