Twitter users who post personal health-related information online may help hospitals predict how many emergency room visits they can expect on a given day, according to new research from the University of Arizona.
In today's post-Affordable Care Act business-to-consumer insurance market, payers will sink or swim based on their ability to adopt analytics, according to LifeHealthPro.
Maine is piloting a project to use predictive modeling software to comb through nearly all of the state residents' electronic health records to determine which patients are most at risk of visiting the emergency room, being admitted to the hospital, suffering a stroke or heart attack or developing type 2 diabetes.
Using predictive modeling to fight fraud, the Massachusetts insurance exchange recouped $2 million in six months and avoided paying hundreds of thousands of dollars inappropriately, according to technology research and assessment firm GCN.
Text-mining the data in electronic health records can help identify patients with multiple sclerosis (MS) and track the key clinical traits in the course of their disease, according to a new study in the Journal of the American Medical Informatics Association (JAMIA).
With the advent of healthcare reform, it's more important than ever for healthcare providers to identify and target high-risk patients to prevent readmissions. The problem is determining which model best predicts those patients.
Using predictive modeling to classify patient populations based on individual risk and anticipated response to an intervention can help hospitals achieve the much-touted triple aim goals, concludes a Walgreens study published this week in Health Affairs.
Utah's Intermountain Medical Center developed a computerized algorithm to identify heart attack patients at risk for readmissions, presented at the American Heart Association Scientific Sessions 2012 in Los Angeles.
As hospitals face penalties for excess readmissions starting in October, they can predict which patients are most likely to bounce back to their facility by simply picking up the phone.
In a continuing fight against fraudulent claims, the Centers for Medicare & Medicaid Services is relying more heavily on predictive modeling, reported The Washington Post.