Hospitals and health systems, overburdened by pandemic-induced staff shortages, are in need of tech to improve workflows, reduce stress and save money. The claims denial process, which is a significant time suck and prone to errors, is ripe for innovation.
It’s estimated that there is more than $200 billion in wasteful spending in healthcare with denied claims a top contributor. By leveraging artificial intelligence, data mining, analytics and automated decision engines, healthcare organizations can streamline many processes and see a major impact in reducing denials in real time.
Experian Health Chief Product Officer, Clarissa Riggins, talked about how Experian is harnessing AI to help speed up and process these requests through its AI Advantage platform. Riggins, who was formerly responsible for product management in the digital health and analytics group at Humana, talked about how AI Advantage has helped speed up prior authorization and claims resubmission utilizing AI.
Asked what causes claims denial, Riggins offered a few reasons. One is pandemic-induced staffing shortages, which continue to stymie providers, large hospitals, and health systems.
“Providers are having a hard time retaining staff. This is really where automation and technology can help,” Riggins said. “The other reason for claims denials is that the pandemic has caused lots of changes to CPT codes. Just trying to keep up with those changes has negatively impacted the claim submission process.”
Between March 2020 and March 2022, Experian has recorded more than 100,000 payer policy changes, Riggins said. Claims denial causes could also stem from errors, scheduling issues or registration information. The need to constantly train new staff —or work short-staffed—has slowed down submission speed and eats into the efficiency of submitting and resubmitting claims.
“If you think about the end-to-end process of revenue cycle management, that is where a lot of them are spending their time. It’s just working those claims and, unfortunately, also reworking the denials,” Riggins noted.
Riggins described how the AI that forms the base of its claims processing tools works. AI is really about perceiving, inferring and synthesizing information, she explained. It’s taking information and data and applying machine learning to train which patterns should be more closely examined and translated into output. This output is specific to AI Advantage.
Their offering covers the pre-claim submission and post-denial processes.
AI Advantage – Predictive Denials takes large sets of data, historical claims information, real-time intelligence and predictive modeling. The goal is to prevent avoidable claims denials as well as to help hospital and health system staff prioritize resubmissions in order to remove the guesswork from where they should be prioritizing their time, according to Riggins.
“We can arm providers with these insights with the ultimate goal of avoiding unnecessary denials and allowing for greater speed and efficiency with those teams of people. The idea is that these products can be implemented separately or combined for pre-claim submission and post processes.”
It also uses historical payment data, said Riggins. The tool looks at each claim and the likelihood of it being denied. It provides important information and data back to the provider about their existing workflow. It’s designed to help hospital staff figure out which claim items are the leading cause for these denials well before they are submitted to the payer. That allows the provider to route the claim to the appropriate associate or specialists to intervene, ideally resulting in a clean claim.
Additionally, the triage component of AI Advantage helps providers focus efforts on denials based on their potential and likelihood for yield, automating decision-making. The predictive algorithm evaluates the probability a denial will be overturned and integrates the probability scores directly into existing work queues. This allows providers to focus their efforts on where they are most likely to have a positive result, according to Experian Health’s website.
“What makes them stand out is the data is tuned, specifically, to a provider’s denial trends. The idea is that the model is continuously learning and adapting,” Riggins said. “The biggest takeaway is that the model is really looking at the value, the probability that denial will be overturned and it’s taking probability scores and integrating them directly into work.”
Although AI Advantage is not the only claims-related automation-analysis software on the market, Riggins explained that Experian Health’s is more comprehensive than of its any rivals.
“Not only do we leverage the historical claim and payment information that is specific and tuned to the providers’ data set, it’s flagged as opportunities to manage denials. It also predicts the most likely Claims Adjustment Reason Codes (CARCs) that a payer would have in return when claims are flagged as high probability for denial.”
Photo: tumsasedgars, Getty Images
