For Dental Insurance Carriers the Time to Digitize is Now

The emergence of technologies in recent years that include intraoral cameras and scanners, digital x-ray systems, and 3D Cone Beam Computed Technology (CBCT) imaging have helped bring a new level of efficiency to the way dental professionals serve their patients. However, despite the advent of these advancements and the inroads that artificial intelligence (AI) has made in dentistry and across the healthcare continuum, some claims and billing processes have a long way to go, technologically speaking.

The fact that there are multi-billion-dollar insurance companies still using paper-based billing systems in 2023 is, frankly, preposterous. Considering the availability of AI tools that can improve not only diagnostics and treatment-related processes in dentistry as well as technology that can be applied to coverage and billing, the time is now for the insurance industry to embrace digitization.

For businesses that want to save money and increase their bottom line, the shift to becoming more digital and less paper-based is, in many ways, a no-brainer. According to a study by the Journal of the American Medical Association, the total cost of waste in the U.S. healthcare industry related to administrative complexity, including paper-based billing processes, is more than $265 billion annually.  

Given such a staggering statistic, in dentistry as well as across all medical disciplines, the moment is long overdue to relegate record keeping on paper and fax-based communication to the dustbin. 

How Computer Vision Can Automate Claims Adjudication

One example of how AI can impact the insurance claims process is the role that computer vision can play in helping clinicians by automating claims adjudication. Computer vision is a subcategory of AI that focuses on building and using digital systems to process, analyze and interpret visual data. Using digital images and deep learning models, machines can accurately identify and classify objects and then react to what they “see.”

In a medical office, a lab, or hospital, when a clinician is using AI-based technology to annotate an X-ray, CAT scan or MRI, if the system is designed to utilize computer vision, the patient’s insurance company can adjudicate the claim process automatically. As a result, diagnostic imaging as well as the insurance claims process related to it can be carried out in real time which will greatly reduce and, in some cases, eliminate the gap in time between when a procedure is conducted, and the claim is approved.

The Convergence of AI in Medical Care and Billing

As the industry increasingly recognizes the value of consumerism in healthcare, the convergence of AI tech in medical care and the insurance process has enormous potential for serving patients. As billing issues continue to be seen by patients as one of the most significant pain points in their healthcare journey, AI-based dental and medical claims processes have enormous potential to improve patient behaviors and enhance the patient experience.

Using tools such as computer vision, medical providers can easily and correctly synchronize a patient’s health plan with insurers that have incorporated AI into their operations and processes. When clinicians have access to AI technology to help them improve the diagnostic process as well as determine in real time what procedures will be covered or not covered by insurance, the patient enjoys a transparent and seamless experience that virtually eliminates billing surprises down the road.

Despite the availability of technology that can redefine archaic billing processes, some of the largest insurance carriers in the country have – to their own detriment as well as their members’ – fallen behind on the road to digitization.

As players in the healthcare space continue to escalate their focus on improving the patient journey through better experiences and healthier outcomes, businesses that hold on to the old ways of doing things are going to find it increasingly difficult to compete with their more tech-savvy counterparts.

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