Apparently, HHS Secretary Kathleen Sebelius ad Eric Holder, the US Attorney General had a ‘summit’ regarding Medicare Fraud and Abuse. You can read the whole report here.
At the summit, Secretary Sebelius announced that starting July 1, HHS will begin using innovative predictive modeling technology to identify fraudulent Medicare claims on a nationwide basis, and stop claims before they are paid. This initiative builds on the new anti-fraud tools and resources provided by the Affordable Care Act that are helping move CMS beyond its former “pay & chase” recovery operations to an approach that focuses on preventing fraud and abuse before payment is made.
I think this is a good idea. There are patterns of abuse that repeat themselves in almost every fraudulent agency and it is easy to write programs that identify them. In one of my ZPIC audits that I am working, there is a clear and distinct pattern of low utilization combined with very long lengths of stay. This is not to say that all patients had old start of care dates. Many of the patients have been admitted and discharged several times over. The numbers you review regarding length of stay based on individual admissions may be lower than what the feds calculate based on the entire claims history of the patient.
Another pattern that shows up repeatedly is high therapy use. I have two excellent clients that have inordinately high therapy use but I don’t worry about them. Many of the patients are total knee replacements or other ortho surgery and after six to nine visits, the patients are discharged. But if all of your therapy patients are being seen for ‘gait instability’ related to chronic illnesses and all of them receive 14 or more therapy visits, expect to find yourself on the ‘naughty list’.
Overuse of any one diagnosis code alerts the feds to potential fraud. Not everyone with impaired vision has a diagnosis that can be supported with physician documentation. And most who do will have other claims in the Medicare system that supports the diagnosis such as ophthalmologist claims and pharmacy claims for eye medications. The feds access to information is unmatched. If they use it properly, no one who is even an inch over the line will be spared.
What I find particularly sad is that when I look at agencies’ clinical records, I see some practices that are common, ineffective and are certain to place the agency on a watch list somewhere. For instance, a nurse will have been taught, and in very good faith believes that if a patient has diabetes, it should always be primary because it pays more. And then she goes to work for one of my clients and it may take a while before the diagnosis problem is discovered. And yet, these same agencies are continually leaving money on the table by not assessing a patient accurately. They routinely increase payment inappropriately by a few dollars while ignoring the hundreds of dollars per day they leave on the table.
Before I take on any client, I look at the CMS reported outcomes. In particular, I look at the hospitalization rate calculated by CMS. There may be various reasons why different agencies send their patients to the hospital but when it comes to extraordinarily high hospitalization rates (over fifty percent), there is only one reason. The agency does not discharge patients to the community. In other words, most of the patients who are discharged from the agency are discharged because they are in the hospital over the end of the episode and the discharge is because the agency has not been able to follow OASIS requirements resulting in a discharge and readmit. If you think the Feds don’t know this, consider that I know it and I have a fraction of one percent of the data the feds have available to them.
So, look at your numbers. Look for patterns. If you are concerned that the new data mining implemented in July may pick up on some unusual patterns in your agency call me. I can be reached at 225.253.4876 or you can always email me. I will find your patterns, deconstruct them and help you reconstruct your care so that you make as much money as you ethically can without creating patterns that even remotely resemble anything less than one hundred percent compliant with Medicare payment guidelines.