NovoDynamics’ New NovoHealth Dental Automates Insurance Claim Verification Process

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The new solution uses dental AI to help providers correct incomplete insurance claims prior to payer review.

NovoDynamics’ New NovoHealth Dental Automates Insurance Claim Verification Process | Image Credit: © NovoDynamics

NovoDynamics’ New NovoHealth Dental Automates Insurance Claim Verification Process | Image Credit: © NovoDynamics

NovoDynamics, a leading provider of artificial intelligence (AI) solutions for the dental industry, just announced the commercial deployment of the latest version of NovoHealth Dental. This cutting-edge technology is designed to transform the insurance claim verification process by automating the detection of missing documentation, such as x-ray images, charts, and correspondence, based on payer-specific guidelines for dental procedure codes.

NovoHealth Dental also ensures that the anatomical references in the claim are clearly visible in attached images, alerting dental offices promptly if any essential documentation is missing. This dental AI helps providers correct incomplete insurance claims prior to payer review.

“NovoHealth Dental’s pre-emptive claim quality and verification approach saves both payers and providers significant time, effort, and costs,” says NovoDynamics Dental Director Joseph Borg, DDS, in a press release. “And, by adding intelligent automation early in the claim submission workflow, NovoHealth Dental Claim Quality Assurance also brings greater consistency and transparency to the system, making it easier for dentists and their patients to know when their claims qualify for payment.”

Historically, insurance personnel have had the challenging task of manually assessing claim attachments for the required clinical review images. With the enormous volume of submissions, clinicians could only inspect a small fraction, leading to incomplete claims being either paid or causing delays in the review process. This resulted in unnecessary costs and inconsistencies in payment outcomes.

NovoHealth Dental Claim Quality Assurance automatically:

  • Recognizes and classifies attachment types, distinguishing between radiographs (x-ray images), photographs, charts, and correspondence.
  • Separates individual views from full-mouth series and specifies each image as bitewing, periapical, or panoramic.
  • Identifies and labels quadrants and teeth and ascertains if the necessary anatomy is visible.
  • • Determination of compliance with the specific evidence requirements outlined by the payer, with prompt notifications to dental offices for unfulfilled claim requirements.

Additionally, NovoHealth Dental goes beyond assessing completeness by also performing clinical analyses to ascertain if the evidence provided meets the criteria for payment based on the insurer's guidelines. Moreover, the system can identify potentially questionable submissions. When a claim adheres to the payer's standards, it can be expedited for auto-adjudication. In cases where NovoHealth Dental raises concerns that may warrant denial, it annotates, flags, prioritizes, and automatically routes the claim for clinician review. This approach results in enhanced review productivity, consistency, and cost savings for payers, as well as faster, more accurate, and more predictable claim decisions for providers and their patients.

NovoDynamics, with its extensive experience in AI, has consistently delivered solutions that address critical healthcare challenges, streamline processes for payers and providers, and enhance the quality of patient care. As an In-Q-Tel portfolio company, NovoDynamics has been leveraging its AI expertise and advanced image processing technology to tackle complex issues for governments, commercial enterprises, and academic institutions since 2001.

The platform, which uses NovoDynamics AI to automatically analyze dental insurance claims in real time at enterprise scale, allows NovoHealth Dental to quickly assure claim quality; accurately support clinical assessments; and reliably detect fraud, waste, and abuse.

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