Using real-time data to predict who will get ill – and intervene
Did you know that more than 8 percent or 25 million people in America suffer from diabetes? Diabetes is not only expensive to treat, it can be fatal.
What’s even more startling, an estimated 25 percent of Americans – another 80 million people – are on the verge of getting diabetes, and don’t even know it. This condition, known as pre-diabetes, is dangerous. If untreated, pre-diabetes can damage blood vessels and increase the risk of cardiovascular disease.
If current trends continue in the U.S., one in three adults will have diabetes by 2050.
That’s more than a challenge.
It is a crisis.
And Independence is tackling it head on.
In 2013 we teamed up with New York University and NYU Langone Medical Center in a three year project to develop machine-learning algorithms that use claims data to identify people with undiagnosed diabetes and even predict who will get diabetes.
With predictive analytics, it is possible to slow down the progression of the diabetes epidemic and, perhaps, stop it in its tracks. By identifying people at high risk for diabetes and working with them and their doctors to get the care they need, we can ultimately keep people well and reduce potential complications from the disease.
As a founding member of NYU’s effort to harness today’s flood of data to make advances in medicine, science, and technology, we’re confident that our trail-blazing research can improve patient care and lower costs for people who are at risk for developing diabetes – one of the most prevalent chronic illnesses in the United States.