Andrew Frost: Denials continue to be a challenge in the healthcare industry. Denials are on the rise, attributed to payer prior authorization and eligibility changes. Statistics indicate that denials make up, on average, 6-13%¹ of a practice’s claims. Shockingly, 85%¹ of these denials are preventable and can be overturned, yet a staggering 65%² are never appealed. There’s clearly an opportunity to reduce costs and increase speed of payment, and payment in general, by solving potential denials before they go into the abyss.

Alice McMahan: The staggering number of denials that are never appealed result in substantial financial losses, with healthcare providers spending approximately $118 per claim³ on appeals. Nationwide, this amounts to as much as $8.6 billion³ in administrative costs. Furthermore, $262 billion⁴ in denied claims are written off annually as bad debt. Customer confusion, staff shortages and a lack of expertise compound the problem, making proactive denials management imperative. We have to start changing the conversation from managing denials to preventing them. Data is our most powerful weapon in this fight against rising denials, and as a leader in the clearinghouse industry, we’ve been able to leverage our data to build a proprietary engine to change the game.

Andrew: The industry has seen a shift from identification and analysis toward automation and prevention. Providers are increasingly turning to technology and outsourcing as viable solutions to manage denials more effectively. The landscape has progressed beyond the traditional focus of identifying denials to incorporating advanced technologies that allow proactive prevention, reducing the burden on healthcare providers and ensuring more efficient revenue cycle management.

Alice: That’s right Andrew–providers can no longer rely on the payer to respond in a timely manner or provide thorough details on how to resolve a denial. Physician practices, hospitals and health systems are now looking for strategic investments to proactively reduce denials, save time and optimize payment turnaround times. All we can do is rely on the power of our own data. The way our engine is powered allows providers to build engines based on their historical claim data to best predict the outcomes of claims before they’re even submitted. This is a huge evolution in the way denials are managed and can be a game changer for both small and large provider groups.

Andrew: The approach was developed in response to significant challenges such as ineffective follow-up on denials, variations in payer definitions and slow, poor follow-up on appeals. Addressing denials before a claim is submitted became crucial. This solution emerged as a response to these inefficiencies, aiming to streamline the entire denials management process and provide timely interventions to prevent revenue leakage.

Alice: First and foremost–revenue loss! Hospitals, health systems and providers are all suffering from increased write-offs and rising staffing costs with nothing to show for it. We understand that each practice or organization suffers from unique challenges, and in some cases, practices don’t know where to start tackling these challenges. We knew our solution had to supply providers with a path to understanding how to solve and prevent the various types of denials they encounter.  We wanted to provide a probability for denial in our prediction. We also knew we had to include things like denial reason codes and groups for the solution to be truly effective.

Andrew: Machine learning and AI integration is pivotal to our proactive denials management methodology. We leverage the vast amounts of data available in our customer ecosystem, allowing modern AI learning models to identify potential denials more accurately. Unlike existing solutions that require building and maintenance of algorithms and logic, our approach harnesses the power of AI to continuously learn and adapt. This ensures being proactive can be more efficient and effective, significantly improving denials identification and prevention.

Alice: Being part of Cognizant allows us to harness our technical partners’ expertise and re-engineer healthcare together. We are a proven leader in generative AI solutions and services, so we needed to come up with a way to empower our clients with adaptive, cutting-edge technology that helps them improve their business processes. Incorporating machine learning into our denial prediction capabilities was a pivotal step in producing a holistic solution to reduce denials and administrative costs, as well as improve the financial wellbeing of the practice.

Andrew: As we witness the success of our proactive approach, the next steps will involve continuous improvement and advancements. We envision enhancing machine learning model accuracy, creating a customer experience that not only identifies denials but guides users on what actions to take. Fixing denials with automation will be a key focus, reducing manual interventions and speeding up the entire process. Additionally, we plan to surround our solution with advanced analysis and trending capabilities to provide insight into success rates and further empower healthcare providers in their revenue cycle management journey.

Alice: Our customers are begging for efficiency whether it be with technology, new solutions or outsourcing certain aspects of their RCM workflow. We believe our solution being seamlessly integrated into the provider’s workflow will create an opportunity to reallocate staff to more revenue-generating activities and decrease overall denial write-offs. All of this produces more money for the organization and allows it to focus on more strategic initiatives—most importantly, taking care of patients.