Stanford Launches Big Data Cholesterol-Fighting Effort

Stanford University School of Medicine researchers have launched a new project to identify Stanford patients who may have a genetic disease that causes a deadly buildup of cholesterol in their arteries.

Using data analytics and software that can learn to recognize patterns, researchers will comb through electronic health records to identify patients at risk of familial hypercholesterolemia, which often goes undiagnosed until a heart attack strikes.

The project is part of a larger initiative called FIND FH (Flag, Identify, Network, Deliver), a collaborative effort with biotechnology firm Amgen and the nonprofit Familial Hypercholesterolemia Foundation, to use innovative technologies to identify individuals with the disorder who are undiagnosed, untreated, or undertreated. The larger initiative is being funded by Amgen, which is developing an experimental cholesterol-lowering drug. The Stanford project is receiving additional funding from the American Heart Association.

For the Stanford project, researchers will use methods pioneered by Stanford biomedical informatics professor Nigam Shah to “teach” a computer how to recognize a pattern in the electronic records of Stanford patients who have been diagnosed with FH. The computer then will analyze records for signs of the pattern. Researchers will report their findings to the patients’ personal physicians, who can encourage screening and therapy.