Whether in movies, books, or the news, we continually hear about how artificial intelligence (AI) creeping into our daily lives could eventually become an existential threat. Skeptics wonder whether machines that mimic human intelligence should be allowed to make decisions currently left to highly trained personnel, but in dentistry, AI is proving to be an excellent colleague.
As most dentists know, dental insurers (i.e. payers) perform utilization reviews on a portion of the claims they receive. The purpose of these reviews is to ensure that the reimbursed services are necessary, appropriate, and consistent with the payer’s clinical guidelines and group contract requirements. Payers require dental offices to provide x-rays, periodontal charts and other forms of documentation in order to review certain procedures. Specific requirements vary by payer and plan, and along with review processes, they change periodically. This inconsistency has been a source of frustration for dentists for decades, and payers have been frustrated with the increased costs of reviewing claims, as additional time and communication is required to resolve issues resulting from a insufficient or non-compliant documentation. But the machines are not frustrated; in fact, they excel at complex, repetitive, and detail-oriented tasks, such as selecting mountains of documentation and analyzing millions of medical images. When used appropriately, AI can step in and deliver immediate benefits that reduce frustration and friction between providers and payers.
Ensure complete claims
Dental office staff do their best to include all necessary documentation, but preparing claims can be confusing when requirements vary by payer. Claims may be denied, processing suspended and reimbursement delayed until all requirements are met. Meanwhile, payers don’t have the resources to fully investigate the massive volume of claims pouring into their systems, so they often pay non-compliant claims. A major US payer used AI to learn that more than 75% of their dental claims were paid without the required X-rays or periodontal records.1 Well-designed AI can ease the administrative burden on providers and payers by ensuring that each application submitted includes all required data and documentation, freeing administrative staff from time-consuming phone calls and follow-ups. The AI can filter claims and immediately determine if the required attachments are included (for example, if teeth and relevant anatomical structures are visible in the provided images). When a required attachment is missing from a claim, the AI can automatically search the payer’s database to see if it may have been submitted with a previous claim, or it can trigger an alert to notify the dental practice of what is necessary. AI can also use natural language processing to analyze narrative content to ensure it fully describes the clinical condition. When AI is integrated into the claim preparation process, it can check for missing documents even before the claim is submitted to the payer.
Increase the efficiency of complaints review
Payer systems are often highly automated and most claims complete the settlement process without any human intervention. Usage reviews are only performed on a small sample of claims, so many claim issues go undetected. Additionally, most of the claims selected for review are paid,2 time and effort are therefore often wasted. AI can instantly analyze every request submitted, even to the most active payers. It can flag and annotate questionable claims and prioritize them to help payers improve efficiency and effectiveness, with their highly trained reviewers only receiving potentially problematic claims. Such payor-side process improvements benefit providers by facilitating faster payment of clean claims. They can also benefit patients by helping to contain administrative costs for providers and payers.
Ensure consistency in reviewing complaints
From the supplier’s perspective, since most claims are processed and paid without human intervention, when delays do occur they can seem arbitrary. But if AI is integrated into the claims handling workflow, payers and providers can be assured that when human review is invoked, it is necessary and appropriate. AI uses statistical models to accurately and consistently assess x-rays and determine if a procedure is eligible for payment under a payer’s clinical guidelines. Services that meet the guidelines can be automatically approved, while those that don’t seem to can be routed to the payer’s clinical staff for review. In cases such as periodontitis, where human examination can be subjective,3 AI’s data-driven clinical assessment capabilities can help support clinician decisions.
Prequalification of treatment plans
Today, dental office staff do their best to determine if and to what extent a patient’s recommended treatment will be covered by their insurance plan, but the answer is often unclear until a procedure is n has not already been made, the claim has not been submitted and the payer has not responded. . It’s really frustrating for providers and patients. The RN can quickly pre-screen X-rays to determine if a proposed service will meet a participating payer’s guidelines and how much will be reimbursed by a particular patient’s plan, before the service is rendered.
AI is closing the gap
Dental AI can provide many benefits. It can be a detail-oriented administrative workhorse who outmaneuver an army of staff. It can provide an unbiased second opinion, offering clinical decision support. It can conserve cash flow and speed up repayment. And, perhaps most importantly, AI can help bridge the goodwill gaps between payers, providers, and patients.
Editor’s note: This article originally appeared in the July 2022 print edition of Dental economy magazine. Dentists in North America can take advantage of a free print subscription. Register here.
1. Internal data. A NovoDynamics NovoHealth Dental Claims Quality Assessment Study. 2021.
2.Johnston JW. Michigan’s Delta Dental is tackling fraud with AI technology. 2020 NHCAA Annual Education Conference Presentation. November 19, 2020.
3. Internal data. A dental clinical evaluation study of NovoDynamics NovoHealth. 2018