In this case, it’s increasing the accuracy and speed of dental insurance processing, resulting in better medical control, improved financial outcomes for providers and payors, and improved care and customer service for the patient.
Over the years, much has been said about artificial intelligence and the healthcare industry. Much of it has been focused on two extremes. On one hand, there’s the fairly mature use of neural networks for radiological analysis. On the other, there’s the focus on fraud management. Those have become “must have’s” in my perspective. It’s filling the middle ground that interests me. Medical insurance is, as patients, providers, and payors all can agree, is often convoluted and complex.
The general medical insurance industry does deal with radiology and images. However, that’s typically in specialties. In the dental industry, radiology is a regular tool, using x-rays to understand tooth and gum conditions and then to document work that has been done. The basics of AI and radiology have been covered, in this column and many other places, so this article isn’t going to cover the concepts, it’s important to realize how important that analysis is in dental care.
This is the point to briefly discuss fraud. Yes, insurance companies are concerned with fraud but, as with most other industries, fraud is rare. What’s much more frequent are simple user errors, primarily in recording details. For useability in business, what interests me is the ability to speed up claims processing while also improving accuracy. That has even more value than fraud detection, and helps all three groups of stakeholders.
While AI is an employment risk in many use cases, it doesn’t seem to be here. As pointed out, very few claims are processed because there aren’t enough people. Psychology tells us that boredom is a driver of mistakes. Consider the sixty percent number listed above. If the existing personnel can focus on the exceptions, they are kept more interested.
In order to gain those advantages, robust systems are needed. As a reminder, no individual AI tool is a solution, they are components of a larger system. “In NovoHealth Dental, we use different AI technologies to analyze different types of data — there’s no one-size-fits-all solution,” says Sean McMillan, Senior Scientist, NovoDynamics.
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