Data Analytics & Detecting Medicare Fraud – A Promising Idea Still Awaiting Proof of Concept

For analyzing so-called “Big Data” sets, data analytics is an invaluable set of tools and techniques. Now the HHS OIG plans to expand its efforts to use data analytics to detect Medicare fraud. While promising, it remains to be proven that the tool and techniques will be cost-effective in this context.

The fiscal year 2017 was a big year for the Office of Inspector General of the Department of Health and Human Services (“OIG”). Among many important accomplishments, the OIG undertook “the largest healthcare fraud takedown in history,” involving more than 400 defendants and more than $1.3 billion in false billings to Medicare and Medicaid.

This action was notable not just for the number of defendants involved and the amount of money recovered, but for the fact that as characterized by the OIG, it was a “data-driven effort.” Therefore, the case represents a signature moment in the evolution of healthcare fraud enforcement, as we transition from a “pay and catch” approach to using data analytics to support targeted enforcement.