One of the most powerful ways that data can be used in medicine is to calculate risk. When enough data points are gathered and analyzed, physicians and public health workers can determine not only what factors might play a role in a disease, but also the trigger point at which someone might become at high risk for contracting it.
Heart disease is an excellent example of this. It is the No. 1 cause of death in the U.S., attributable to one in four deaths [source: CDC]. Previously, physicians used to calculate the risk of heart disease primarily using cholesterol values. If cholesterol was high, patients were prescribed medication; if low, they were deemed to not be at risk.
However, using a collection of data gathered from multiple sources, the American College of Cardiology and the American Heart Association found commonalities in heart disease patients that extended far beyond simply having high cholesterol. With massive data sets on weight, race, age, history, cholesterol and a few other factors, the groups have generated a test that acts as a much more comprehensive and personalized risk calculator, called the ASCVD Risk Estimator [source: Gaglioti]. As a result, doctors have changed the way they practice and calculate risk for heart disease.