However, before diving too deeply into AI’s potential in payment integrity, let’s take a closer look at the size and scope of overutilization.

Dimensions of the Problem
Fraud is often cited as the primary culprit behind improper claims payments, but the reality is that overutilization drives a much greater share of overall waste – as much as 40 percent, according to Truven Health Analytics.

There are many causes of overutilization, most of which have nothing to do with Angelina Jolie.

For example, some healthcare services are overutilized because of provider practice patterns and the availability of resources. Physicians in a particular region of the country prescribe more pain medications than the national average because that is the local standard of care. Similarly, more back operations are performed in some regions than in others due to the relative availability of surgeons and hospital beds.

Overutilization also can result from disparities in provider contracts with complex riders, a shortage of staff resources to oversee accuracy of billed versus treated charges and a lack of financial investments in quality auditing and technological solutions to catch mistakes in claims before payments are made.

A more fundamental and hard-to-detect issue stems from billing behavior. Providers frequently contract with third-party vendors to handle claims coding and billing. While outsourcing can generate efficiencies and cost-savings, lack of clarity and consistency in procedures can lead to significant upcoding and unbundling of claims, or the unnecessary use of modifiers.

How AI makes a difference
Unlike the resource-intensive and largely static nature of traditional payment integrity processes, intelligent algorithms continually learn and evolve with each claim. As a result, health plans now have an opportunity to reduce unwarranted utilization by far more than they have been able to do up to now.

However, identifying anomalies only scratches the surface of what is possible. Payment integrity covers a broad spectrum of issues starting with outlier identification all the way to behavior-led organized crimes. Payment integrity solutions have moved from basic rules related to payment integrity such as policy and pricing edits, diagnostic versus procedure mapping, and other similar linear dimensions, to a multi-dimensional approach working across the enterprise.

Healthcare technology advancements have focused on increasing the effectiveness of multi-dimensional analytics – aggregating data from medical records, contact centers, claims, authorizations, and provider networks to capture trends (and errors) across the claims value stream.

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