How Big Data can Help Combat Healthcare Fraud

With about one-third of the cost of the healthcare industry in the U.S. lost to fraud, waste, and abuse, it is vitally important to society that we report healthcare fraud when we see it. While it is certainly helpful to familiarize yourself with the most common healthcare fraud schemes and pay close attention to all bills received from your healthcare provider, it is not always easy – or possible – to detect healthcare fraud with the naked eye. Thanks to technology and the development of big data, however, there are new and improved ways to detect healthcare fraud today that have never before existed. Below is a brief overview of how you can use big data to help combat healthcare fraud. If you believe you have witnessed healthcare fraud, contact one of our attorneys today to find out how you can report your claim and initiate a whistleblower lawsuit.

Common Types of Healthcare Fraud

The most common type of healthcare fraud is fraudulent billing. Healthcare providers may bill for services that were never rendered, or bill for a more expensive service than the one that was rendered. For example, a doctor might bill a patient for a two-hour visit when in fact the visit was only one hour long. Fraudulent billing in the medical space is so common that it accounts for up to 10% of annual healthcare costs in the U.S.

Other types of common healthcare fraud schemes include filing multiple claims for the same patient, stolen patient identities in order to obtain reimbursement for certain services, and collusion between multiple service providers or between service providers and their patients.

What is Big Data?

You have probably heard the term “big data” thrown around, but you may not be as familiar with what it actually refers to. Big data simply refers to large data sets that require more advanced technologies and processes to analyze and extract. In practice, big data is most commonly used to analyze human behavior and interactions by extracting patterns, trends, and associations from the data sets.

How Big Data can Help Combat Healthcare Fraud

Healthcare payers have started using predictive analytics to prevent healthcare fraud before the fraudulent claims are even paid out. Predictive analytics is not an entirely new model, as banks and insurance companies have used it to mine consumer data in order to determine what their consumers want.

As applied to healthcare fraud, predictive analytics takes a big data set of all healthcare transactions, identifies fraudulent activities, and creates “rules” identifying those fraudulent activities. Then, when the rule is applied to the data set, activity resembling the previously identified fraudulent activity will be instantly detected, and those transactions can be further investigated or cancelled before they are processed.

Contact a San Francisco Whistleblower Attorney Today

If you are interested in learning more about how you can use big data and predictive analytics to help combat healthcare fraud, contact our attorneys. If you believe you have already witnessed healthcare fraud and wish to file a whistleblower case, contact us today so we can get your case moving immediately. We have worked with cutting edge technologies involving big data and have helped numerous whistleblowers report healthcare fraud and successfully file a qui tam claim. Contact us at (800) 427-7020 or visit us online to schedule your free consultation today.

(image courtesy of Marcus Spiske)