AI Solutions for Healthcare

Looking to AI Solutions for Healthcare Payment Accuracy


In 2020 alone, over $6B in fraudulent claims were reported and according to the Department of Justice, over 300 individuals were charged with fraud in the same year.

We have to stop and ask ourselves – why are we as a healthcare system still so challenged with creating integrity across the cost containment spectrum?

For many without an AI solution, any combination of the following challenges may be true when it comes to ensuring healthcare payment accuracy:

  • Disparate, home-grown fraud detection systems
  • Limited ability to bring together all claim types
  • Limited scope of codes being analyzed
  • Lack of meaningful and actionable insights
  • Inability to move up the payment spectrum to fraud, waste and abuse prevention and avoidance

Whether intended or accidental fraud, waste or abuse, educating providers on ways to improve claim integrity and bring down pre-claim costs is critical to protecting the bottom line and quality outcomes.

Utilizing traditional rules-based systems to fuel provider education and compliance programs will only leave you looking backwards – chasing vs. preventing. Forward-looking -and -thinking healthcare companies are looking for sophisticated AI to launch them into the next level of fraud prevention. And, for a good reason.

The below best practices can be used to optimize provider education and compliance programs using advanced AI-based fraud detection, without creating provider abrasion.

1. Create automated provider education & compliance programs using AI-based technologies
Automating provider coding and billing education programs can drive greater ROI without adding workload to existing staff. 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.  The problem with this approach is that schemes are always changing.  This means the reports, filters and rules your teams rely on to catch problems can’t always identify the new problems, and new schemes can slip through the cracks until they add up and impact the bottom line.

Instead, advanced AI solutions find all types of payment errors and identifies suspicious and anomalous activity missed by other AI solutions, including faster, earlier, more comprehensive detection of exposure.  With a more complete and accurate view of provider performance, providers can act before they see impacts to the bottom line.

The secret is truly in the sauce and, the healthcare industry is quickly learning that not all AI is created equal.

2. Analyze all claim types for a holistic view across the payment spectrum
Most fraud detection systems are limited in the types of claims they can ingest and integrate.  Looking to a system that can ingest and analyze all claim types, including professional, facility, and pharmacy claims will create a holistic view across the payment spectrum. Excluding one claim type from your analysis will create a gap in your view of provider practice patterns and create missed opportunities to promote coding best practices and reduce costs pre-claim.

2. Broaden claim type analysis beyond basic E&M codes and modifiers
Today, most solutions used to gain insight into provider billing and coding performance and then deliver education back to providers are limited in the type of codes that can be analyzed, commonly restricted to E&M codes.  What this creates is a highly narrow view for both the health plan and the provider. Finding an AI-based platform that analyzes complex codes and shares an expanded view of coding and billing patterns and performance with providers is foundational to true and impactful behavior change.

3. Empower providers with pre-claim self-monitoring & engagement
Step one to driving provider engagement is making sure you are engaging through the right channel – make it easy for them to access information. Some providers prefer letters, some prefer provider portals, and many prefer email. Then, put the power in their hands. Give them interpretable insights and let them self-monitor their historical trends, behavioral insights, peer-to-peer comparisons, and more through an easy to access portal.  With pre-claim monitoring, providers can address concerning patterns and behaviors prior to submission of claims.  Non-compliant providers can be transferred to the special investigations unit (SIU) and addressed through traditional SIU lead management.

This level of transparency will improve provider education and engagement and ultimately fuel behavior changes without creating provider abrasion.

4. Prioritize provider education and engagement
With limited time and resources, having the ability to prioritize provider outreach and education will help create the greatest return and impact on savings. Visibility into the greatest outlier performance can create focus and put your resources where needed most.

Health plans have a real opportunity in front of them today, one that did not exist even a decade ago. As technology advances we find ourselves faced with new levels of insights and performance and if adopted in the right way, real change will happen.