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Predicting the future of healthcare with analytics

By Shannon Geis, MA
July 11, 2017

We’d all love to be able to predict the future and make business decisions based on what we know is going to happen rather than trying to guess. Increasingly, technologies such as predictive analytics are making the guesswork easier.  

“Predictive analytics actually relies on existing or prior data in order to be able to make a prediction about an outcome that goes far beyond what we think about when we think of estimates,” explains Frank Cohen, MBB, MPA, MGMA member, director of analytics, Doctors Management LLC, Clearwater, Fla. To do this you must train algorithms to recognize certain characteristics based on the available data. 

While this is relatively new technology, it is being used more often in the healthcare world. The Centers for Medicare & Medicaid Services introduced the Fraud Prevention System in 2011, which uses predictive algorithms to ferret out improper payments. “And when they process claims through this program, it sniffs out, if you will, and identifies by the likelihood or probability that a given claim may violate some rules or regulations, or be subject to fraud abuse,” says Cohen. 

While compliance is the most common use for predictive analytics in healthcare right now, according to Cohen, there are a number of other ways that the technology can be used. “For example, predicting when an employee may quit by looking at certain performance components,” he says. “Or predicting which patients are most likely to sue a physician, let’s say, for malpractice.” 

Listen to the full episode to learn more about how predictive analytics could change the way we view healthcare.  

Check out Cohen’s featured session, “Predictive Analytics 101: An Introduction to the Future of Healthcare,” and register for the MGMA 2017 Annual Conference, Oct. 8-11 in Anaheim, Calif. 

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Shannon Geis, MA, Staff writer/editor, MGMA

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