Researchers at the University of Notre Dame have developed a computer-aided method that uses electronic health records (EHRs) to assess personalized disease risk and well-being.

The system, called Collaborative Assessment and Recommendation Engine (CARE), was developed by Notre Dame computer science associate professor Nitesh Chawla and his doctoral student, Darcy Davis. At the heart of CARE is a novel collaborative filtering method that captures patient similarities and produces personalized disease risk profiles for individuals. Using what is known as big data science, the system generates predictions focused on other diseases that are based on big data from similar patients.

“The potential for ‘personalizing’ healthcare from a disease prevention, disease management, and therapeutics perspective is increasing,” Chawla said in a statement. “Healthcare informatics and advanced analytics, or data science, may contribute to this shift from population-based evidence for healthcare decision-making to the fusion of population- and individual-based evidence in healthcare. The key question is how to leverage health population data to drive patient-centered healthcare.”

Chawla said he believes that this work that has been done can lead to reduced readmission rates, improved quality of care ratings, and can demonstrate meaningful use, impact personal and population health, and push forward the discussion and impact on the patient-centered paradigm.

“Imagine visiting your physician’s office with a list of concerns and questions,” he said. “What if you could walk out of the office with a personalized assessment of your health, along with a list of personalized and important lifestyle change recommendations based on your predicted health risks? What if your physician was afforded a limitless experience to gauge the impact of your disease toward developing other diseases in the future? What if you could have the experience of others at your fingertips and fathom the lifestyle changes warranted for mitigating diseases?”

A recent paper from researchers at the Indianapolis-based non-profit organization, the Regenstrief Institute, released by the Institute of Medicine (IOM), made the argument that routinely-collected data from individual patient visits at doctor’s offices and hospitals can be used on a national scale to improve care and reduce costs. According to the paper, the information could better monitor diseases and outbreak, target helpful medical services, reduce unnecessary testing and treatments, prevent medical errors, and accelerate medical research and delivery of new treatments.