Big Data to Stall Heart Disease
After partnering in 2008 to develop data analytics to help physicians detect heart disease sooner, IBM, Sutter Hearth and Geisinger Health System have been awarded a $2 million research grant from the National Institutes of Health (NIH).
“Heart failure will remain among our nation’s most deadly and costly diseases unless we discover new methods to detect the illness much earlier,” said Walter “Buzz” Steward, chief research and development officer for Sutter Health and principal investigator for the project.
“Sophisticated analysis of EHR (electronic health record) data could reveal the unique presentation of these symptoms at earlier stages and allow doctors and patients to work together sooner to do something about it,” he said. “Through this research we could transform how heart failure is managed in the future.”
With the funding, the team says they will work toward developing a cost-effective early-detection method for heart disease based on data from an EHR system. But a larger goal is to identify strategies through which primary care facilities can better integrate big data to tailor treatment plans to each individual patient.
The method would look at everything from a patient’s demographic information and medical history to lab test results, medications and allergies in order to identify hidden signs and patterns that point to heart failure risk.
From there, physicians could more actively monitor a patient’s status and educate them about lifestyle and clinical interventions to slow or even reverse the progression of heart failure.
“Our earlier research showed that signs and symptoms of heart failure in patients are often documented years before a diagnosis and that the pattern of documentation can offer clinically useful signals for early detection of this deadly disease,” said Steve Steinhubl, MD, a member of Geisinger’s research team in cardiology. “Now we have the technology to enable earlier diagnosis and intervention of serious conditions like heart failure, leading to better outcomes for patients.”
Together, researchers will begin to test just how effective predictive analytics will prove in a clinical setting over the next several years. If successful, they plan to expand their efforts by using EHR data to combat other chronic diseases.
