From my perspective, 2014 went out like a lion and 2015 has come in the same way, at least as far as post-audit extrapolation work goes.
Several weeks ago I picked up four new cases, and two of those (as have been a few others in the past) involve physicians who have split their interests between clinical practice and durable medical equipment (DME). It seems that DME continues to be a target for audits, and I’m not surprised, since a CERT study shows that some 60 percent of all DME payments are made in error.
Speaking of extrapolation recoveries, I am expecting to start seeing plenty of Part B extrapolation activity among the RACs. Remember, they are paid a commission, and up until now there hasn’t been any oversight with regard to the high rate of error reported on their end (by that I mean the excessively high rate of reversal of their findings on appeal). Think about it: the RACs have been on a feeding frenzy for the past few years, taking random bites out of thousands of providers, at times seemingly just hoping that they won’t appeal, yet knowing that if they do, their commissions go down the drain. What was their chief complaint during the contracting process? They wanted to make sure that they were paid on their findings and didn’t have to wait until after the final appeal. That’s exactly what I would say if my reversal rate were 70-plus percent.
Another new prospect for 2015 is the use of penny sampling to create random samples for what used to be the attribute appraisal method. Penny sampling is a bit of a twist on a more traditional method and was developed under the direction of Professor Don Edwards of the University of South Carolina. Dr. Edwards is well-known within the healthcare community as a staunch defender of the Centers for Medicare & Medicaid Services (CMS) efforts to drive down rates of fraud, waste, and abuse, and his Minimum Sum Method has been used widely by AdvanceMed and others to create extrapolation overpayment estimates. Penny sampling has yet to be tested with regard to its robustness and “stickiness,” if you will. I have two cases I am working on now for which the sample and extrapolation is based on penny sampling, so stay tuned. More will be revealed.
Dr. Edward’s university Web page features the following message: “According to Edwards, healthcare fraud is both difficult to find as well as prove. First, you have to find abusive providers, and they might be doctors, hospitals, ambulance services, providers of power wheelchairs, or any of a wide range of groups that bill Medicare.”
“One way to do that is through data mining, which involves terabytes of healthcare data,” he added. “It’s really finding a needle in a haystack.”
Now, don’t get me wrong. I have the highest respect and admiration for Dr. Edwards, including his good intentions and his excellent work. Unfortunately, however, there doesn’t seem to be enough attention paid to what has become a myriad of medically unnecessary and administratively complex rules and regulations – of which, I would venture to say, like IRS rules, no one can figure out well enough to follow perfectly. I don’t expect anytime in 2015 to see Dr. Edwards – or anyone else, for that matter – addressing RAC abuse, which as many of us have experienced, is rampant and unchecked.
And I do concur with his statement that data mining is the way to identify potential fraud, waste, and abuse issues – and I fully expect to see more of that this year. CMS has committed a significant portion of its new budget toward the data mining project it started back in July 2011. Every healthcare provider that submits even a single claim to Medicare can rest assured that they are being examined using a very sophisticated set of mathematical and statistical algorithms designed for the sole purpose of picking out needles from a haystack.
Professor W. Edwards Deming summed it up with this quote: “In God we trust. All others must bring data.”
And that’s the world according to Frank.
About the Author:
Frank Cohen is the director of analytics and business intelligence for DoctorsManagement. He is a healthcare consultant who specializes in data mining, applied statistics, practice analytics, decision support, and process improvement. Mr. Cohen is also a member of the National Society of Certified Healthcare Business Consultants (NSCHBC.ORG).
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