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The Role of AI in Reducing Denials in Radiology
By: admin
Monday, January 6, 2025
The Role of AI in Reducing Denials in Radiology
The world of radiology has seen significant advancements over the years, shifting the landscape of healthcare costs and accessibility. Traditionally, interventional radiology procedures such as biopsies and catheter placements were considered some of the more expensive imaging services. However, with the increasing sophistication of diagnostic radiology, this balance has shifted. Advanced diagnostic imaging procedures such as CT scans, MRIs, PET scans, and nuclear medicine studies have become increasingly costly and, consequently, more prone to denials by payers. These denials not only create administrative burdens but also delay critical care for patients. At Clavis Health, we believe that artificial intelligence holds the power to transform this cumbersome process, ensuring patients receive the care they need—free from unnecessary delays or administrative hurdles.
The Growing Costs and Denials in Diagnostic Radiology
Diagnostic imaging is a cornerstone of modern healthcare, enabling precise diagnosis and monitoring of conditions such as cancer, cardiovascular disease, and neurological disorders. However, as these technologies advance, so do their costs. An MRI, for example, can range from $500 to $3,000 depending on the area being scanned, while PET scans, which are vital for detecting cancers and other serious conditions, can cost upwards of $5,000.
Unfortunately, these high costs have resulted in a greater tendency for insurers to deny claims for diagnostic imaging. While these issues are primarily administrative, they have significant downstream effects. Patients may face delays in treatment, rescheduling imaging appointments, or bearing out-of-pocket costs while disputes between providers and payers are resolved. Reasons for these denials can include:
The Human Error Factor
A substantial portion of denials arises from preventable human errors in documentation and coding. Consider a scenario where a radiologist orders a CT scan for suspected pulmonary embolism, but the documentation fails to clearly outline the patient’s clinical symptoms and history. Without these details, the payer might deny the claim on the grounds of insufficient medical necessity. Similarly, a simple coding error—for instance, using the wrong ICD-10 code for a specific diagnosis—can result in an outright rejection, requiring appeals that add time and cost to the process. These errors add time to the process, delay patient care, and can potentially increase costs for both patients and providers.
How AI Bridges the Gap
Recognizing these challenges, Clavis Health has developed innovative AI-driven solutions to address the root causes of radiology denials. Our technology is designed to minimize human error, reduce administrative burdens, and ensure patients receive the care they deserve. This solution automates validation of pre-authorization requirements, cross-references clinical documentation with payer policies, and alerts staff to missing or incomplete data in real time.
Key Features of Clavis Health’s AI Solutions:
Automated Compliance Checks: AI evaluates payer-specific policies in real-time, ensuring all preauthorization requirements are met before submission and reducing first-pass denials.
Error-Free Documentation: Our platform identifies gaps in clinical documentation, such as missing patient history or symptoms, and prompts providers to include the necessary information before submission.
Accurate Coding Assistance: By leveraging natural language processing (NLP), our AI suggests the most appropriate diagnosis and procedure codes, significantly reducing coding errors.
Proactive Denial Prevention: Clavis Health's system analyzes historical claims data to identify patterns that commonly lead to denials. With this information, providers can address potential issues before submission.
Streamlined Appeals: In the event of a denial, our platform automates the creation of appeal letters, referencing payer-specific guidelines and radiology best practices to improve success rates.
Primary care medical services are provided by physicians, physician assistants, nurse practitioners, or other health professionals who have first contact with a patient seeking medical treatment or care. These occur in physician offices, clinics, nursing homes, schools, home visits, and other places close to patients. About 90% of medical visits can be treated by the primary care provider. These include treatment of acute and chronic illnesses, preventive care, and health education for all ages.
The Patient Impact
For patients, the benefits of reducing radiology denials are immense. Timely imaging can mean earlier diagnosis and treatment, better outcomes, and reduced financial strain. For instance, a patient suspected of having a tumor can receive MRI results promptly when authorizations go through seamlessly, helping guide swift treatment decisions. By streamlining the prior authorization process and minimizing errors, Clavis Health ensures that patients can focus on their health rather than navigating the complexities of insurance approvals.
The Future of Radiology with AI
As diagnostic imaging continues to evolve, so too must the systems supporting it. Additionally, as AI matures, advanced algorithms will further refine imaging protocols, personalize patient follow-up, and integrate seamlessly with electronic health record (EHR) systems. Denials are a symptom of an outdated, fragmented process that struggles to keep pace with modern healthcare demands. Clavis Health’s AI-powered solutions represent a new era of collaboration between providers and payers, where technology bridges gaps and ensures that care remains at the forefront of radiology. With AI driving efficiency, accuracy, and collaboration, Clavis Health is reducing denials, improving patient outcomes, and setting a new standard for radiology workflows
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