New York University (NYU) and its affiliated four-hospital Manhattan-based academic medical center, NYU Langone Medical Center, are teaming up with Philadephia-based payer, Independence Blue Cross, to develop machine-learning algorithms that can detect cases of undiagnosed diabetes.
In addition, NYU Langone will look to use the analytics to predict pre-diabetes in patients. According to research cited in this press release, 79 million people in the U.S. have “pre-diabetes,” where blood glucose levels are higher than normal, but not yet high enough to be diagnosed as diabetes.
“Without a doubt, improved ways to accelerate the diagnosis of diabetes in affected people will improve health, reduce the complications of the disease, and reduce health care costs,” stated Ann Marie Schmidt, M.D., a professor of endocrinology and medicine at NYU Langone Medical Center and co-investigator.
Dr. Schmidt and the other investigators of this collaboration will use Independence Blue Cross’ medical and pharmacy claims data and apply machine-learning algorithms to determine the undiagnosed diabetes and pre-diabetes patients.
NYU Langone is just the latest large academic medical center to invest in a large-scale analytics initiative. Recently, the University of Pittsburgh Medical Center (UPMC) and the University of California at Los Angeles (UCLA) have announced similar analytics-based initiatives.
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