We know at Caffery, Oubre, Campbell & Garrison in Lafayette that health care fraud not only exists in Louisiana and across the United States, but runs rampant.
In fact, it is of epidemic proportions and ever-escalating. We duly note in a recent firm blog post addressing malfeasance in the medical realm that its “sheer dimensions … are staggeringly huge
Can health care fraud be curbed and, if so, is there a tool of marked utility that can help investigators efficiently uncover it and provide evidence to aid in civil and criminal prosecutions?
Industry insiders and commentators increasingly believe there is. They collectively laud the growing applications of artificial intelligence (AI) assists that can sift through data and probe for behavioral patterns that point to wrongdoing in the health care sphere.
Insurance companies understandably care about that, and for compelling reasons. A recent Forbes article notes that medical fraud “costs tens of billions of dollars each year in the U.S.” Insurers that can’t detect wrongdoing directly pay out on bogus claims, with policyholders and taxpayers also being harmed materially when that happens.
AI tools and processes are now contributing progressively enhanced software and algorithms to the fight against fraud, with Forbes stressing that they can sometimes help prevent it well before it ever occurs.
AI analyzes company data focused on worker communications and search histories to uncover potential fraud-linked patterns. It can look through electronic health records and doctors’ notes at near lightning speed in search of anomalies that are strikingly irregular. It can quickly spot billing red flags such as the “upcoding” of treatments pegged at premium prices, as well as MD referrals that could have significance in kickback probes.
Concededly, human oversight and expertise will always be central in the AI-assisted fight against fraud.
“Data is going to point the way,” says one forensic researcher, who adds that, “we just have to know how to use it.”
