AI in the Revenue Cycle—A Use Case for Denial Prevention

Artificial Intelligence (AI), once considered healthcare’s “next big thing,” has proven that it is here to stay. AI’s application in clinical care and pharmaceuticals often receive the most buzz. Potentially equally transformative is the technology’s potential impact on the $43 billion spent each year on healthcare’s revenue cycle.

According to a November 2022 report by global consulting firm Crowe LLP, average denial rates grew from 10.2% in 2021 to 11% in 2022. The average cost to rework a claim is $25 and typically takes about 71 minutes. It also costs about $118 to appeal a denied claim. However, time and value are only part of the overall impact on a health system’s bottom line.

Many organizations invest heavily in reactive solutions—point technologies, staffing surges, and complex appeal processes. These tools may help “manage” denials, but true cost savings lie in prevention. AI-powered tools address many of the resource-intensive and costly processes associated with claims editing and denial management. However, the true value of this technology is its ability to analyze claims for errors before submission.

Many systems offer packaged or custom edits to claims before submission. Often times, these edits are built retrospectively. This requires costly analysis to determine the root cause of the denials, and ongoing maintenance as payers’ adjudication rules shift in response to external forces. Telehealth claims adjudication, for example, changed rapidly during the early days of the COVID-19 pandemic.

The ideal system would analyze claims and spot trends that will likely lead to denials. Applying AI to the constantly changing stream of data removes manual writing and maintenance of edits. This allows health systems to react to changes faster and act accordingly.

The Potential of Predictive Editing

Providers are looking for more effective ways to identify and prevent denied claims. Leveraging AI for predictive editing within the revenue cycle management process can yield significant savings by cutting down on administrative expenses related to claim revisions and denials. This enhances the revenue cycle and enables providers to prioritize patient care over administrative duties.

At Availity^®, our revenue cycle management solution, Essentials Pro™, utilizes an AI-driven predictive editing tool. This feature empowers providers to detect denials early, thus saving valuable time and financial resources. Powered by an AI algorithm, predictive editing focuses on identifying and correcting the subset of denials most likely to be avoidable. Its predictive capabilities stem from analyzing claims data across various provider organizations and individual health plan policies. The solution will return the predicted Claim Adjustment Reason and Remark (CARC & RARC) if the likelihood of denials is very high.

As a result, providers can:

• Reduce the administrative cost of reworking claims.
• Increase edit coverage by capturing complex, payer-specific edit scenarios beyond the scope of traditional edit engines.
• Reduce the administrative effort of maintaining manual rules.
• Allow providers to save on implementation costs because predictive editing can be used within the provider’s existing edit/error management tools.

The path toward a sustainable and healthy revenue cycle requires tools and analytics to help providers submit claims right the first time. AI and machine learning tools have the potential to move your organization from costly denial management to optimized denial prevention.

If you’re interested in learning more about Essentials Pro’s robust RCM features, download our Buyer’s Guide or schedule a meeting with our team today!

About the Author

Anne Neal, Vice President of Product and Payment Accuracy at Availity, brings over 20 years of extensive experience in product development within the healthcare industry. With a focus on leading product portfolios and driving innovation in both payer and provider spaces, Anne has established herself as a visionary leader. Before joining Availity, Anne spearheaded revenue cycle innovation at UnitedHealth Group Optum and spent over two decades at Cognizant’s TriZetto Provider Solutions, where she led the development of its payer core administration platform.

Anne’s mission in healthcare is to create a seamless, personalized, and compassionate system where affordable quality care is accessible to everyone. She holds a bachelor’s in business administration from Staffordshire University and an MBA from Grand Canyon University, with additional executive certifications from Harvard and Columbia. Anne was honored as a Luminary by the Healthcare Businesswomen’s Association in 2020.