THE STATE OF PREDICTIVE ANALYTICS

IN U. S. HEALTHCARE

IF THERE IS ONE WORD THAT HAS TAKEN ON NEW MEANING FOR HEALTHCARE IN THE NEW ERA OF ACCOUNTABLE CARE, IT IS THIS ONE: RISK.

Risk has traditionally, in healthcare, corresponded to a doctor’s or institution’s chance for malpractice. But now, as providers and payers take on new responsibilities in the areas of patient experience, clinical outcomes, population health management, and financial accountability, “risk” takes on a multitude of new meanings and roles in the business of healthcare.

With the expansion of risk, the ability to predict needs and outcomes is more important than ever. Imagine, for instance, a physician being able to predict whether a patient is more or less likely to comply with their medication regimen based on various demographic factors. Or, imagine a health system being able to project which of its patients are most at risk for high-impact events like infections and readmissions—and taking the steps to proactively manage those patients to avoid these events.

Decision making like this can be possible through the use of predictive analytics—the ability to mine data in order to forecast probabilities and trends, and ultimately, manage risk. Indeed, predictive analytics has the potential to radically change healthcare, and the way decisions are made at the bedside and in the corner office.

How are U.S. healthcare organizations leveraging predictive analytics right now? Are they using them at all? What are the barriers to integrating predictive analytics within a healthcare organization? This survey of 388 healthcare executives answers those questions and more.