LOS ANGELES, August 11, 2021 / PRNewswire / – pearl, the leader in AI solutions for efficiency, accuracy and consistency in dental care, today announced that it has received a patent from the United States Patent Office covering the AI system Company pioneer in detecting fraud, waste and abuse (FWA) in dental insurance claims. The patent – U.S. Patent No. 62 / 962,828 titled “Insurance Fraud Detection Systems and Methods” – is Pearl’s fourth awarded this year for machine learning innovations developed to elevate the healthcare industry. dental.
Pearl’s patented system, which provides the technological basis for its Pearl Protect solution, helps overcome what has long been a barrier for dental insurance companies. Every year, insurance companies lose about $ 12.5 billion – 5 percent of $ 250 billion that the insurance industry spends on dental care – due to fraud and other irregularities in dental claim submissions. Until Pearl introduced a computer vision-based solution to this problem, carriers had to rely on statistical analysis and imprecise heuristic processes to limit FWA. The patent announced today covers a new AI process that provides a much more comprehensive and high-precision defense against FWA.
The challenge of the fight against AOF is multifaceted. With billions of submissions per year, the problem of reviewer resources arises: Because too few reviewers review every request, a large portion of FWA will go without review. But the problem goes beyond the resources of the examiner. Even when an instance of FWA lands on an examiner’s desktop, it is unlikely to be detected.
“With resubmission fraud, the radiographic evidence of claims is real, coming only from a previously approved claim or from a different patient,” said Pearl CEO Ophir Tanz Explain. “An examiner has no way of knowing that this is an FWA unless he can remember seeing the evidence before. Considering the hundreds of carriers and the billions of attachments on the shelf X, there’s almost zero chance an examiner will have seen this x-ray – let alone remember.This makes FWA detection a problem with recalling and sharing information as well as examiner resources. machine learning is the only viable way to tackle all three. We felt an obligation to patients, carriers and the majority of dental providers unfairly tarnished by suspicion about the actions of a few dishonest dentists to apply our expertise in machine learning to design viable FWA reduction technology. ”
The machine learning solution developed by Pearl significantly reduces the vulnerability of carriers to FWA by automatically showing claims containing false and duplicate proof of claims. The patented system deploys a variety of algorithmic computer vision models to accomplish this feat.
“This patent validates the exceptional work of our machine learning engineers in overcoming an entirely different challenge than those they have mastered with our radiological detection systems,” said Cambron Carter, CTO of Pearl. “It is one thing to teach a machine learning system to search for a finite set of relevant known quantities – decay, bone loss, etc. It is another to teach a system to search for an unlimited set. quantities unknown. The latter is a big data problem of the kind that only an unsupervised learning AI system developed by experts can solve. This is exactly the kind of system that Pearl’s patent covers and we are proud to see the originality of our invention recognized.
Over the past 6 months, Pearl has made major inroads in advancing AI and partnering to support and elevate all facets of dentistry. These breakthroughs were codified with an assortment of patents awarded this year for technologies developed to improve the restoration manufacturing workflow, attend radiological pathology detection, and automate settlement of insurance claims.
About Perle
Pearl is shaping the future of dental care by delivering AI and computer vision solutions that improve efficiency, accuracy, transparency and patient care. Founded in 2019 by Ophir Tanz, Pearl is backed by Craft Ventures and other leading venture capital firms. For more information or to request a demonstration, please visit http://www.hellopearl.com.
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