Big Data Slams the Door on Medicare Fraud
Medicare fraud is huge. In the news just about every day, you get the idea that people are either trying to get away with it or getting busted for it all the time. You’d be right. But, Big Data is already doing good work to change that. Recently, Federal authorities busted nearly 300 people allegedly involved in a $712 million Medicare fraud scheme. According to a report entitled: “Ensuring the Integrity of Medicare Part D� data analysis played a significant role in the operation leading to the arrest of the alleged perpetrators. Medicare Part D is a popular section of the Medicare Law provision that adds an optional prescription drug benefit to the policies of Medicare beneficiaries. The program began in 2006 and, today, annual spending tops more than $121 billion. As you can imagine, with numbers that massive, fraud is a problem. Fraudsters will get prescriptions to give to others or simply resell. Others will go from one doctor to the next trying to get more drugs. Worse, some physicians are taking bribes to write
unnecessary prescriptions, and some pharmacies are dispensing drugs without proper authorization. The massive scale of the system involved invites this sort of risk. Fraudsters believe they won’t get caught because they have gotten away with it for so long. Big data analysis is closing that gap. According to the report, investigators were able to use broad-based data analysis to determine areas in which fraud was most likely occurring. This predictive ability – a hallmark of big data analysis – helped authorities to narrow the field and identify a host of likely targets. Among the red flags: physicians ordering extremely high numbers or relative percentages of certain drugs known to have potential for abuse. Further investigation turned up 700 physicians who had, in fact, over ordered drugs as well as many pharmacies that had been filling prescriptions without proper paperwork. This sort of wide net program might have been tactically impossible just a few short years ago, but thanks to Big Data, individuals were efficiently identified, investigated and brought to justice. At every step of the process, data analysis helped investigators predict and identify, tracking unusual activity and helping them determine where to look for more. With Big Data helping to direct the investigation, authorities were able to quickly and efficiently bring to bear otherwise limited resources. Using data to compare national averages, investigators first identified certain medical facilities that were prescribing well above that average. From there they continued to crunch data, eliminating nearly half of the potential suspects, allowing investigators to focus strictly on those most likely to be engaged in fraudulent practices. Even with all the number crunching and elimination, investigators still found hundreds of doctors and pharmacies involved in what appeared to be fraudulent practices. However, bringing these numbers down into a range where the available resources could conduct the necessary investigations would have been impossible without the extrapolative and predictive faculties of Big Data. Just one more way Big Data is working for all of us to save money and live better, safer lives in the wild West of the digital world. Jonah Engler is a financial expert who embraces the latest technology trends.