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How AI is helping to prevent healthcare fraud

Criminals are getting smarter and the healthcare industry is no exception. In 2021 alone, the Department of Justice (DOJ) recovered more than $5.6 billion from civil fraud and false claims cases. This is the DOJ’s biggest haul since 2014, but a drop in the bucket compared to the estimated $380 billion is lost every year to fraud, waste, and abuse. 

These numbers add up to higher premiums and out-of-pocket expenses for consumers, as well as reduced benefits or coverage. What’s more, relaxed telehealth mandates put into place during the COVID-19 pandemic, the increased digitization of health, and the emergence of telehealth platforms have made it easier than ever for fraudsters to operate are all contributing to a growing problem. Pressure is mounting on healthcare providers and payers to find solutions to prevent fraud. 

What savvy providers are doing to circumvent criminals

Battling fraud isn’t just for healthcare payers – providers play an integral role too. What are the newest tools in a provider’s fraud prevention arsenal? Automated provider education and compliance programs using advanced AI-based technologies. While some health plans and agencies have looked to more traditional fraud detection systems that rely on rules and reports to flag issues with claims or providers, this approach doesn’t always work because healthcare fraud schemes are always changing. This means the reports, filters, and rules that teams may rely on to catch problems won’t always identify the new problems, and new schemes can slip through the cracks until they add up and impact the bottom line.

When it comes to fraud, not all AI is equal

The secret exists within sophisticated AI, and healthcare leaders are quickly learning that even so-called “advanced” tools aren’t capable of keeping up with today’s fraud. Only top-grade AI solutions are able to find all types of payment errors and identify suspicious and anomalous activity that might have been missed through traditional means. These solutions have been built to include faster, earlier, more comprehensive detection of exposure. With a more complete and accurate view of provider performance, providers can act before they see impacts on their bottom line.

An example of this in action is a system that can ingest and analyze all claim types, including professional, facility, and pharmacy claims through AI rules. Excluding one claim type from the analysis will create a gap in the view of provider practice patterns and create missed opportunities to promote coding best practices and reduce costs pre-claim.

Providers benefit from a broader and more complex view of codes and customization

Another way that providers can educate themselves and implement an effective AI system is to find AI tools that are able to analyze complex codes and share an expanded view of both coding and billing patterns and performance with providers. This is foundational to true and impactful behavior change. A provider must once again move away from legacy systems that are limited in the type of codes that can be analyzed, commonly restricted to E&M codes, because this creates a highly narrow view for both the health plan and the provider.

Electronic medical records are another area that is vastly improving with AI. On the healthcare payer side, AI is beginning to play a significant role with EMRs when it comes to providing insights on medical records history prior to authorizing a procedure or test. Using AI in this way will boost efficiency and cost savings. 

Finally, regardless of how advanced and innovative the AI is, providers won’t reap the benefits without significant adoption and education. One way to increase engagement is to work with providers through the channels they prefer.  Would they rather work with email, letters, or provider portals? By offering flexible channels that promote engagement, they are able to better serve their clients.

Real change is underway – now is the time to adapt 

Health plans have a real opportunity in front of them today, one that did not exist even a decade ago. They can rapidly adapt AI to fight fraud, waste, and abuse, streamline repetitive processes, automate workflows, and even personalize member experiences.

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