Healthcare fraud is a serious crime that affects individuals, taxpayers, insurance companies, healthcare providers and businesses in challenging ways. The National Health Care Anti-Fraud Association estimates that roughly 3% of annual healthcare spending goes towards fraudulent claims.
Still, other agencies say that number could reach up to 10%, resulting in over $300 billion lost annually to healthcare fraud cases.
The healthcare industry generates insane amounts of data daily, especially regarding financial and transactional data. The billing of healthcare services is a complex task that can result in significant consequences for individuals, providers or businesses when purposely or accidentally conducted erroneously.
While fraud investigators are critical to all operations in the healthcare ecosystem, real-time fraud detection is extremely limited through human-only investigation teams. The amount of fraud is simply overwhelming.
Artificial Intelligence (Ai) software grants a multi-faceted solution which is already being implemented in numerous industries for gathering data, analyzing patterns, predicting potential areas of future threats, and providing real-time fraud detection.
For instance, many financial institutions are beginning to implement Ai technology to help detect and reduce the occurrence of fraud through questionable checks, mobile banking, funds transfers, and card activity both outside of and within typical banking hours.
This type of technology, called RembrandtAi™ can also be potentially applied to the medical claim fraud/abuse detection and prevention industry.
More on RembrandtAi™ in just a moment.
First, let’s examine what exactly healthcare fraud is, its impact in the US, and how Ai may be the key to minimizing its damage.
Types of Healthcare Fraud and Abuse
Fraud is defined as the intentional act of deceiving or misrepresenting facts, resulting in unauthorized payments or benefits. Typically, healthcare fraud, or abuse, includes actions considered inappropriate, improper, medically unnecessary, or outside acceptable professional conduct standards.
Healthcare fraud or abuse is generally conducted in one of two ways – by the provider or by patients/other individuals – and both can have dire consequences for everyone involved.
Patients can commit healthcare fraud through medical identity theft/swapping. This is also one of the most commonly reported versions of identity theft, with some of the highest reported costs associated with data breaches.
Scammers posing as legitimate health insurance companies often commit healthcare fraud by signing people up for bogus coverage plans or charging their insurance for non-rendered services. In extreme cases, individuals may commit healthcare fraud by providing/billing for health services or equipment under falsified licenses.
But healthcare providers have even more methods available for committing fraud and have been found to be among the largest potential fraudsters in the industry.
For example, Dr. Michael Ligotti, a medical director at substance abuse facilities, was found to have billed insurance companies more than $746 million for fraudulent urine tests and addiction treatments. He was recently sentenced to 20 years… but much of the money may be unrecoverable.
Here are some common healthcare provider frauds that may be discoverable by real-time artificial intelligence:
Extra Payments: medically unnecessary procedures that cause extra payments that are often not covered by insurance plans (i.e., diagnostic testing methods or genetic testing)
Double Billing: submitting more than one charge for the same services.
Phantom Billing: charging for services or procedures that were never performed.
Upcoding: charging for procedures or services that are more expensive than what were given.
Because of its ability to examine and interpret massive amounts of data in near real-time, artificial intelligence has the potential capability to see which providers may be exhibiting a pattern of abuse and could alert insurance fraud teams of the issues before they grow to the level of Dr. Ligotti’s $746 million.
Its Impact on the US Healthcare System and Those Who Use It
According to the FBI, “Health care fraud is not a victimless crime. It affects everyone—individuals and businesses alike—and causes tens of billions of dollars in losses each year.”
For the consumer, fraud raises the costs of healthcare and insurance premiums, making it even more difficult for the average family to afford it. It can also cause billions of taxpayer dollars to be lost when people or providers commit healthcare fraud through public healthcare systems, like Medicare.
Additionally, patients that receive procedures or prescriptions they don’t need sometimes suffer physical or financial damage that can be life changing.
An effective medical claim fraud/abuse detection system is needed to avoid further rising costs, wasted resources, and potentially dangerous and unnecessary medical procedures.
Traditional Healthcare Fraud Detection Methods and Their Limitations
The False Claims Act of 1863 is the earliest known US law enacted to criminalize fraudulent claims against the government. Healthcare fraud continues to be the primary source of settlements under this law.
In fact, in fiscal year 2022, the US Department of Justice recovered over $2.2 billion under this act, amounting to roughly $6.2 million per incident. But $2.2 billion is just a drop in the bucket when it comes to healthcare fraud, and many if not most frauds go completely undetected.
You see, traditional ways of finding and proving fraudulent claims involve gathering data and having teams of investigators review it through auditing processes. This can take months or even years of pouring over information and offers little to no real-time fraud detection, as issues are often not discovered until after the payments have been made.
In the Dr. Ligotti case, for example, he apparently ran his scam for nearly a decade.
But thanks to recent technological advancements, a medical claim fraud/abuse detection system can now effectively diminish successful frauds with support from Ai software.
Benefits of Ai-Backed Healthcare Fraud Detection Systems
Artificial Intelligence technology provides incredible benefits for all sorts of business processes, especially for handling data, financial transactions, and for security and fraud protection. Ai software works by analyzing copious amounts of data, learning financial patterns, alerting to potential discrepancies, and increasing overall efficiency.
When deviations appear, Ai can flag those accounts (either individual or provider) and conduct real-time fraud analysis before any payments or claims are confirmed.
While it is not entirely foolproof, Ai software is an exceptional tool for making the lives of fraud investigators much easier. Detecting healthcare fraud in real-time allows the government and private insurers to find the guilty parties much faster, reduce wasted resources, and mitigate the adverse effects victims may face.
Introducing RembrandtAi™
An Ai-backed medical claim fraud/abuse detection system is more efficient at detecting and preventing fraudulent transactions than human fraud teams alone.
RembrandtAi™ has the ability to flag for suspicious transactions near-instantly, could accumulate and “map” individual provider claims submissions (to discover potentially illicit billing patterns) an allows insurers, both public and private to quickly review these transactions before claims are paid.
As healthcare continues evolving with more technological integrations, RembrandtAi™ presents a scalable Ai solution that can save the government, insurers, and all Americans billions of dollars. Artificial intelligence is the key to protecting the healthcare industry as we advance into the tech-based future.
Discover how RembrandtAi™ can help insurance companies (both private and public) detect fraudulent activity by requesting a full demonstration, HERE
