Is $56B enough to get our attention?

February 27, 2019

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$56 billion in overpayments? That’s more than the entire budget for the Department of Homeland Security.  In a March 2017 report (GAO-17-277) by the U.S. Government Accountability Office, it was estimated that the 2016 improper payment rate was $56 billion, or 9.8 percent of all Medicaid expenditures of $576 billion.  Those overpayments represent a combination of fraud, waste, and abuse.  But what are the distinctions among the three and how do we stop, or at least reduce, all three?

The first category, fraud, is often defined as an intentional, illegal act.  Proving intent in a complex environment like healthcare can be very difficult.  As a result, in the grand scheme of things, the monetary value of proven fraud is relatively small. 

Then there is waste and abuse.  What is the difference?  I’m not sure there’s a text book definition for abuse, but I characterize it as the intent to game the system without crossing into illegality or, an illegality where intent can’t be proven.   

And how is waste defined?  Waste is everything else that causes money to leave the system due to less than optimal efficiency.  Inefficiencies can occur in any area and have many root causes.  Individual providers, large provider systems, and medical centers can all be inefficient from either (or both!) the fiscal or quality of care perspective. 

It isn’t just the providers who are inefficient, but also the government agencies, such as Medicaid agencies, who oversee and reimburse health care providers.  They too can contribute to inefficiencies with program rules and constructs.  Perhaps this occurs because of unnecessary overhead, rewards for inefficient practices, or even the failure to reward efficient practices. Perhaps it could be stopped if agencies and plans routinely checked for ineligible providers and ineligible beneficiaries; for example, out of state, incarcerated, or deceased providers and beneficiaries should be their first stop.

I submit that both fraud and abuse are merely subsets of the overall subject of waste.  Though it’s important to distinguish between the categories when discovered, the clear first step should be to identify and address waste in all its forms. With the advent of artificial intelligence, machine learning, and advanced data analytics, there are now cutting-edge tools available to stop this waste in its tracks.

As we move toward managed care, health homes, accountable care organizations, meaningful use, and value-based payments, it’s essential that we don’t confine our analytics to fraud, waste, and abuse silos.  We need to structure our analytics to look for all forms of inefficiency and just as importantly, to balance our efforts to root out the negative behaviors and to also identify program participants that are efficient so that we can continue to reward and replicate those behaviors. 

True performance management, a comprehensive approach to identify all forms of inefficiency and efficiency, would improve success across all programs.  There are at least 56 billion reasons to try.