Last week, the Department of Justice (DOJ) announced a $1.5 million settlement with a Riverdale, Md., based doctor alleged to have performed medically unnecessary autonomic nervous function tests and neurobehavioral status exams.
In December, an internist in Elkton agreed to pay the United States $1.2 million to settle allegations that she “submitted false claims … for medically unnecessary injections and evaluation and management services that were not documented.”
And that same month, an internist in Glenn Dale agreed to pay the U.S. $1 million to settle “allegations that he submitted false claims to the United States for medically unnecessary autonomic nervous function tests and peripheral vascular tests.”
In many ways, these settlements are like so many others from around the country that DOJ proudly touts. Hardly a week goes by without the department issuing one of its splashy press releases. At the end of each came a particularly ominous note from the office: “This case arose from a recent initiative inside the United States Attorney’s Office. The United States Attorney’s Office has dedicated resources to enable it to review Medicare billing data. The review of that data has enabled the United States Attorney’s Office to identify areas of concern where it appears that billing irregularities may have taken place.”
Health care data analysis is emerging as a way for government prosecutors to hone in on potential wrongdoers. Indeed, in his now-standard speech, United States Attorney General Jeff Sessions proudly describes how DOJ is using data analysis to determine “who is prescribing the most drugs, who is dispensing the most drugs and whose patients are dying of overdoses.”
As former prosecutors who pioneered the use of data analysis in our own health care prosecutions, we commend our former colleagues for their work in this space. But, as individuals who saw both the power of data and its limitations, we caution against over-reliance on data analysis.
We write specifically to remind our former colleagues that certain physicians will stand out among their peers for perfectly innocent reasons. It would be little surprise, for example, that a pain management physician might be writing more opioid prescriptions than, say, a podiatrist. Likewise, it would be normal — and, indeed, expected — that certain internists and primary care physicians would order more diagnostic tests to assess a patient’s condition than specialists, who might already know the cause of a patient’s ailments.
Looking at data analytics in a vacuum creates the potential for many well-intentioned practitioners to land on DOJ’s radar. For example, as Maryland residents know well, the greater capital area generally has more affluent residents than the rest of the country, but it also has a population that suffers from higher instances of substance abuse and mental illness. Therefore, it would be expected that physicians in this region would be more likely to promote and prescribe regimens that fit these demographic trends. Data alone often ignores these real-world differences.
Ultimately, we recognize that data analysis is a powerful tool that law enforcement is increasingly harnessing to identify and develop prosecutions. We commend our former colleagues for this work. Yet, as with most things, the devil is in the details. We trust that our former colleagues — dedicated public servants — will pay attention to these details and remember that simply being an outlier is not the same as being an outlaw.
A. Lee Bentley III is the former U.S. attorney for the Middle District of Florida. Jason Mehta (firstname.lastname@example.org) is a former federal prosecutor in the same office. Both are now in private practice in Tampa.