April 17, 2014

Risk of Trusting Data

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Last week the Centers for Medicare & Medicaid Services (CMS) released data on the reimbursement Medicare pays to individual physicians.

The data provides a great illustration of one of the challenges of healthcare: it is risky to trust data, and it is risky to dismiss it. There is another risk of data as well: sometimes its mere existence can change behavior. This may seem counterintuitive, but sometimes data can actually increase the risk of a compliance problem.

Data analysis tends to encourage providers to make sure that they look “normal” or “typical” to a reviewer. While that effort often will benefit the compliance process, there are many times that accurate coding will yield “atypical” data. If an organization attempts to mechanically shift coding so that the results look normal, there is a real risk that can result in inaccurate coding and/or billing.

Data always has the potential to be misleading. Many news stories focus on how many of the recipients of the most Medicare dollars live in Florida. You don’t need a statistics degree to come up with a possible factor that might be an innocent explanation for the data anomaly, however: there are more Medicare recipients in Florida than in most other states. One would expect that physicians whose practices are focused on care for geriatric patients would be at the top of the list for Medicare reimbursement. I have seen this problem with many of my clients. I represented a geriatric psychiatrist who was the recipient of the most Medicare dollars of any psychiatrist in his state. The government was certain that this demonstrated that he must be “overcoding.” He had far more total Medicare receipts than other psychiatrists, and the government made a demand for $1 million. It took some time, but we ultimately convinced the government to drop the case. Data prompted the investigation, but a detailed review of the charts ended it. (I should add that convincing the government to drop the case took a considerable amount of time, and that patience is an important trait to exhibit during most government inquiries – patience and a willingness to prepare a very thorough defense.)

Ophthalmologists and oncologists appeared at the top of the reimbursement lists in a number of states. These specialists are reimbursed for drugs that are administered to patients, and the reported data reflected this reimbursement rather than focusing exclusively on professional services. This is another example of how data can mislead. Without understanding exactly what information is included in data, it is easy to draw inaccurate conclusions.

A story in my home state of Minnesota focused on a physician at a large medical institution who was reported as receiving $11 million from Medicare. Why? It’s because he is the lab director, and as lab director, his name appears on all of the organization’s lab tests. Under Medicare rules, it is totally appropriate to bill under the name of the lab director. Lab tests are performed under general supervision, and that means that the supervising physician must be responsible for the techs and the equipment. While there may be any number of physicians who fulfill that role, the lab director certainly does. The data was accurate, but terribly misleading.

Because individuals at the top of the Medicare lists received so much attention, there is a natural instinct to avoid being such an outlier. It is understandable that many have an instinct to try to “normalize” their data, changing practices so that going forward the data is more consistent with expectations. While I understand that desire, I think people are often too quick to try to bring everyone into a bell curve. The goal should be accuracy, not being “typical.” If accurate data leaves you looking like an outlier, so be it. I have jokingly encouraged people to get an“Anomalies Happen” bumper sticker. Compliance isn’t looking like everyone else; compliance is doing things the right way. Data can be useful to determine areas that may benefit from a focused review, but it is important to remember that the initial data inquiry is a tool, not a conclusion.

About the Author

David Glaser is a shareholder in Fredrikson & Byron's Health Law Group and helped establish its Health Care Fraud & Compliance Group. David helps healthcare entities negotiate the maze of healthcare regulations, providing advice about risk management, reimbursement and business planning issues. He has considerable experience in healthcare regulation and litigation, including compliance, criminal and civil fraud investigations, and reimbursement disputes.

Contact the Author

dglaser@fredlaw.com

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David M. Glaser, Esq.

David M. Glaser, Esq., is a shareholder in Fredrikson & Byron’s Health Law Group. David helps clinics, hospitals, and other healthcare entities negotiate the maze of healthcare regulations, providing advice about risk management, reimbursement, and business planning issues. He has considerable experience in healthcare regulation and litigation, including compliance, criminal and civil fraud investigations, and reimbursement disputes. David’s goal is to explain the government’s enforcement position and to analyze whether the law supports this position. David is a popular panelist on Monitor Mondays and is a member of the RACmonitor editorial board.

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