CMS release of physician data illustrate challenges of health care

ByDavid M. Glaser, JD

In early April, CMS released data on the reimbursement Medicare paid to individual physicians. The data and its release provide a great illustration of one of the challenges of health care. It is risky to trust data, and it is risky to dismiss it. There is another risk of data — sometimes its existence can change behavior. This may seem counter-intuitive, but sometimes data can actually increase the risk of a compliance problem.

Data analysis tends to encourage people to make sure that they look “normal” or “typical” to a reviewer. While that effort will often 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/billing.

Data anomaly

Data always has the potential to be misleading. Many news stories focused on how many of the largest recipients of Medicare dollars were in Florida. You don’t need to a statistics degree to come up with a possible factor that might be an innocent explanation for the data anomaly. There are more Medicare recipients in Florida than in most other states. One would expect that physicians whose practice is focused on care for geriatric patients would be at the top of the list for Medicare dollars.

I have seen this problem with many of my clients. I represented a geriatric psychiatrist and he was the largest recipient of Medicare dollars of any psychiatrist in his state. The government was certain that this demonstrated he must be “overcoding.” He had far more total Medicare receipts than other psychiatrists. 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. Patience is an important trait in most government inquiries. Patience, and a willingness to prepare a thorough defense can save you millions of dollars in a government investigation.

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

Compliance

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? Because he is the lab director and as the lab director, his name appears on all of the organizations lab tests. Under Medicare rules, it is totally appropriate to bill under the name of the lab director. Lab tests are done 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 were 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 people have an instinct to try to “normalize” the data, changing practices so that going forward, the data is more consistent with expectations. While I understand the 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, then so be it. I have joking 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.