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Denied Claims Harm Patients and Providers — How AI Can Help Heal the System

By Jim Bohnsack

Hospital finance executives are grappling with three pressing revenue cycle management (RCM) challenges: staffing shortages, a surge in claims denials, and the convoluted prior authorization process.

These issues not only strain financial resources but also jeopardize the quality of patient care. Leveraging advanced technologies like artificial intelligence (AI) and automation, health care providers can address these hurdles, streamline operations, and ensure timely and effective patient treatment while securing financial stability.

In June, the American Medical Association (AMA) House of Delegates laid out its priorities for reforms to a health care system plagued by troubles with inflation—made worse by claims denials, prior authorizations, and staffing uncertainties that hinder providers as they try to manage costs and run their operations efficiently. Priorities include the following:

• ensure the clinical validity of care and offer patients continuity;
• offer transparency and fairness from the prior authorization process;
• approve claims in a timely manner; and
• offer alternative options for care in case of a denial.

While calls for reform—such as those from the AMA—persist, hospitals need immediate solutions to enhance the claims process and improve revenue cycles.

Implementing AI tools can help providers accelerate approval processes, increase transparency, and reduce friction between payers and providers. This approach minimizes patient wait times and ensures providers receive timely payments. As payers already leverage AI for automated claims, aligning provider systems with these advancements can significantly streamline operations, boost financial stability, and improve patient care outcomes.

Overcoming Medicare Advantage Hurdles With AI
A focal point of struggles with prior authorization is Medicare Advantage plans, which have grown in popularity over the last decade. While there are philosophical and practical criticisms of these offerings, they’re undoubtedly popular among patients, giving them more options for quality care than they may get from Medicare alone. And for providers, while the plans are a headache, they offer a chance for additional revenue than what CMS will typically pay out.

However, as the AMA noted in its 2023 AMA prior authorization physician survey, 94% of providers were experiencing care delays related to prior authorizations. Reforms have since been passed that require payers to be more objective with the care they approve or deny. To help themselves, providers now need to change the way they file claims.

As mentioned previously, payers have been using AI to process claims for years, and it helps them make decisions regarding care reimbursement. Providers could adopt AI methodologies similar to those of major insurers to speed the process, namely by making their claims as accurate and clean as possible before filing them.

Specifically, AI can empower providers to streamline claims processing and improve coding accuracy, while extracting critical information from medical records and payer contracts, addressing the underlying reasons for many claims denials.

Support for RCM Professionals
The experience of RCM professionals remains essential for avoiding denials, but AI can help support them as they navigate the complexity of the process. By integrating AI, RCM staff can overcome obstacles that trigger denials while boosting efficiency, which benefits providers. AI can help RCM pros do the following:

• Improve clinical data capture: AI, specifically large-language models that make use of unstructured data, identify improvement opportunities in clinical documentation. Large-language models have the ability to provide structure to raw text, compare to clinical guidelines, and serve as an accelerator for identifying gaps in documentation. Additionally, patient data holds the key to appeasing managed care plans, ensuring patients are delivered care based on their medical need and best practices.

• Automate clerical tasks: AI automates the extraction of essential data from sources like claims and medical records to speed workflows, such as drafting appeal letters for revenue cycle professionals. This reduces errors, enhances efficiency, and ultimately improves revenue outcomes without the need for manually searching through records.

• Avoid future denials: The reasons for issuing denials change—and predicting them—isn’t easy. AI helps RCM teams proactively adjust operations to prevent denials in real time as new trends emerge. This allows providers to deliver timely care while ensuring a steady revenue stream.

Whether we’re talking about hospitals, provider groups, or small practices, improving the efficiency of the revenue cycle is the only path forward as care costs rise and reimbursement rates diminish. Universally, denials are on the rise and the administrative expenses are following suit.

Regardless, in an era of consolidation and mergers—not to mention general economic uncertainty—stable revenue is critical to hiring staff, finding new patients, and creating a healthy hospital system. AI can offer a leg up and stabilize business operations so staff at provider organizations can focus on patient care.

Bridging Business Interests and Patient Care
Balancing business interests with patient outcomes is vital in modern healthcare. AI can significantly nurture this balance, but deploying these tools and technological advancements presents unique challenges. Providers must carefully select AI tools that meet their specific needs, as the effectiveness of machine learning models depends on the quality of data and precise application.

Interoperability, for example, continues to be one of the most pressing challenges in AI implementation. Effective AI systems require seamless access to diverse data sets, including claims, medical records, managed care contracts, and operational data. Achieving this necessitates strong integration with existing EHR systems and workflows, accompanied by thorough staff training.

The gradual adoption of AI can mitigate potential integration issues. Rushing into AI implementation can lead to complications, so it is imperative for providers to find AI solutions and partners that align with their unique requirements.

Despite the complexities, AI technology is no longer in its infancy. Leading health systems are leveraging AI to enhance network efficiencies, and many provider groups are training AI models to support various operational needs.

Providers often express frustration with prior authorization and Medicare Advantage plans; however, these systems are essential components of the health care landscape. They provide critical care options for patients and offer revenue opportunities that might not otherwise exist.

The challenges are significant, but AI's potential to transform health care delivery is immense. AI can streamline business operations, improve claims processing, and support RCM staff, ultimately strengthening the patient-provider relationship and driving better health care outcomes.

— Jim Bohnsack is the chief strategy officer for Aspirion, a technology-leading revenue cycle management company that addresses hospital denials, underpayments, and complex claims.