Researchers at the University of Notre Dame have developed a computerized assessment tool to help doctors offer patients a personalized disease management and wellness plan.
The system, called Collaborative Assessment and Recommendation Engine (CARE), uses big data analytics to compare population health data to each individual's risk factors. Their work is published in the Journal of General Internal Medicine.
"In its most conservative use, the CARE rankings can provide reminders for conditions that busy doctors may have overlooked. Utilized to its full potential, CARE can be used to explore broader disease histories, suggest previously unconsidered concerns and facilitate discussion about early testing and prevention…" Notre Dame computer science associate professor Nitesh V. Chawla said in an announcement.
"What if you could walk out of the [doctor's] 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 [could] 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?"
In addition to improving patient health by better empowering them to take needed action, Chawla said the tool could reduce readmission rates, improve care quality ratings and more.
A recent Institute of Medicine discussion paper posed the possibility of harnessing the data about individual patients collected every day in doctor's offices and hospitals to improve health for everyone.
The days of just collecting information are over, according to Brian Dixon, assistant professor of health informatics at Indiana University and research scientist with the Regenstrief Institute. It's time to put all that data to work, he said in a recent post.
In an effort to do that, there's been a spate of partnerships announced lately between healthcare organizations and analytics technology vendors as they attempt to mine troves of data to aid the individual patient.