Amid the shifting landscape of medical claims, the rise of high-cost and complex in-network claims has become a significant challenge for payers. Data from the Peterson Center on Healthcare and Kaiser Family Foundation highlights the shifting landscape of medical claims. Moderate claims decreased from 60% in 2004 to 45% in 2021, while higher-intensity claims increased from 19% to 37% in the same period.
And the challenge evolves further with the emergence of new high-cost centers such as dialysis. Researchers at the University of Southern California found that outpatient dialysis costs for patients with end-stage kidney disease in the individual market are now a whopping $10,149 per month per patient — more than 300% higher than Medicare reimbursement for the same service.
To address these trends head-on, payers require a combination of actionable data and clinical expertise. The sheer volume and complexity of data involved in high-cost claims, coupled with the nuances associated with complex medical procedures and documentation, can easily exceed the resources payers are able to dedicate to claims review. Working with a strategic partner, payers can access the artificial and human intelligence necessary to identify savings and educate providers on proper coding and billing techniques to speed payments.
The healthcare industry has faced increasing complexity in recent years, especially during the pandemic, with changing regulations and ongoing code updates.
“Over the past decade, the healthcare industry has become increasingly complex with layers of guidelines, regulations, and contracts,” says Zelis Chief Medical Officer Timothy Garrett, MD. “The pandemic initially led to a relaxation of requirements, but they quickly became unclear, changing frequently. Now, post-pandemic, most previous regulations have returned, along with new ones. Meanwhile, updates to codes like ICD-10 and CPT have continued, making it challenging for both provider and payer organizations to keep up.”
Despite the complexity of healthcare, most claims are accurate, but errors do occur as a result of inadvertent mistakes and a lack of understanding of coding practices, especially unbundling.
“While the majority of claims are accurate, plenty contain inaccuracies often due to inadvertent errors,” Garrett explains. “Sometimes, it’s a lack of understanding of correct coding practices, particularly when it comes to unbundling. Providers may not realize that a service is already included in another billed service, leading to errors. Staying updated on these guidelines can be challenging. Some payer organizations lack the resources to pay enough attention to this issue.”
To address their multifaceted challenges, payer organizations increasingly rely on external expertise to bridge knowledge gaps and modernize their processes, thereby enhancing efficiency and accuracy in claims management.
Tasked with both guaranteeing quality healthcare and managing accurate payments, payers face a complex environment that highlights the need for assistance in overcoming knowledge gaps.
The ideal approach for managing healthcare claims involves using advanced data analytics to detect overpayments and inaccuracies, employing automated tools for data collection, and fostering intra-organizational collaboration for developing and communicating claim edits and reviews.
“The payment integrity and healthcare industry are at an inflection point,” Garrett stresses. “Technology, including artificial intelligence, machine learning, and automation, is increasingly seen as the solution for accurate healthcare payments, but advanced technology by itself is not going to be the answer. Industry veterans from all across the payment integrity spectrum provide tremendous value in understanding common claim errors and inaccuracies.”
In short, the real value of artificial intelligence is best harnessed by continuing to bring human expertise to bear on tasks that require deep understanding and nuanced judgment.
Technology, particularly through the implementation of natural language processing (NLP), enables human claim experts to perform their jobs more efficiently by significantly reducing the need for manual searches in extensive documents.
“When discussing expert claims review, it’s important to take into account the time-sensitive aspects of payment accuracy and timely filing,” notes Will Israel, Vice President of Portfolio Management & Product Integrations at Zelis. “AI like NLP eliminates the need for manual searches through extensive documents, allowing reviewers to quickly locate specific information.”
Having technology assists the experts in the evaluation of policy compliance and necessary actions without the labor-intensive task of reading through thousands of pages and various documents and formats.
“Usually, the information is in digital formats like PDFs or even faxes, which can be messy,” Israel adds. “The tricky part is making this messy data usable via OCR to recognize text and converting it into a format machines can understand. This process can be complicated. The key is to make sure you have the right data to work with so you can respond quickly and get accurate results.”
Ultimately, enabling expert claims reviewers to respond more quickly thanks to automation and technology creates more productive relationships between payers and providers around claims reimbursement.
“Ensuring timely payments through an efficient and prompt prepay process that minimizes provider effort can foster a strong partnership. Additionally, clear communication through determination letters and notices is effective in building positive relationships with providers going forward,” says Garrett.
As medical claims become more complex and expensive, most payers will find it essential to use external claims review services. The right partner, equipped with advanced artificial intelligence and expert knowledge, helps payers manage the complexity of medical billing and coding, maintain accuracy in payments, and establish strong relationships with providers.
Zelis has a team of experts ready to help with this. Learn more about Expert Claims Review or contact the team here.
This article originally appeared on Health Payer Intelligence.
