Risk-bearing entities such as IPAs, MSOs, and health plans — especially those operating in the Medicare Advantage space — are facing unprecedented challenges. The implementation of CMS’s Hierarchical Condition Category (HCC) risk adjustment model Version 28 (V28) is already reshaping the industry. With regulatory changes that reduce risk scores and, consequently, reimbursements, Medicare Advantage Organizations (MAOs) must rethink their risk adjustment strategies. Traditional methods are proving inadequate, prompting a critical need for innovative solutions.
The Impact of V28 on Medicare Advantage
V28 isn’t just a minor update—it’s a seismic shift. CMS began phasing in this model in early 2023, and this year, V28 will be fully in effect.
What does this mean for Medicare Advantage Organizations?
CMS projects that the full implementation of V28 will lead to a decrease in risk scores, directly impacting reimbursements. Specifically, CMS estimated a 3.12% reduction in risk scores for the calendar year 2024, translating to approximately $11.0 billion in net savings to the Medicare Trust Fund. This reduction is largely attributed to the removal of over 2,000 diagnosis codes that previously contributed to risk adjustment calculations, thereby tightening the criteria for justifying reimbursement rates.1
The stakes are high. If organizations fail to capture patient conditions accurately, they stand to lose substantial revenue, making it harder to provide quality care. "The complexity of managing risk adjustment has grown exponentially. Traditional methods are no longer sufficient to meet the demands of the new model," notes Wes Stevenson, Executive Vice President at PromiseCare.
Why Traditional Risk Adjustment is Struggling
Historically, risk adjustment has been a labor-intensive process. It relies on manual data entry, fragmented electronic medical records (EMRs), and retrospective chart reviews. These methods have always been prone to errors and omissions, but under V28, the pressure is even greater. MAOs that fail to document conditions with complete accuracy will see lower risk scores and reduced payments.
Operational bottlenecks also contribute to these challenges. Manual chart reviews are time-consuming, and querying physicians for additional documentation often causes delays. The reliance on retrospective audits instead of real-time documentation leads to missed opportunities for accurate coding, increasing compliance risks and financial uncertainty.
AI as a Transformative Solution
Artificial Intelligence (AI) is changing the game in risk adjustment. Unlike manual methods, AI-driven platforms can process vast amounts of data in real time, identify patterns, and flag missing documentation. This not only improves accuracy but also ensures that MAOs can keep up with V28’s stricter coding requirements.
Wes Stevenson observes, "AI enables us to navigate the complexities of V28 by providing real-time insights and ensuring that our documentation reflects the true health status of our patients."
Generative AI takes this further by creating context-aware documentation, ensuring that all relevant diagnoses are captured. Instead of relying on retrospective audits, AI-powered tools use current data from EMRs and other sources, providing real-time guidance to clinicians. AI can also surface relevant suggestions at the point of care, improving workflow efficiency and minimizing documentation gaps.
Dr. Arun Hampapur, an AI thought leader and the founder and CEO of Bloom Value, emphasizes, "AI doesn’t replace human expertise—it enhances it. It helps us find what’s missing, ensuring we’re coding accurately and fairly."
The Case for Enterprise AI Platforms: Plugging the Leaky Bucket
Many Madicare Advantage organizations turn to point solutions for risk adjustment, but these can be fragmented and inefficient. An enterprise AI platform provides a more holistic approach. By integrating AI across multiple functions—risk adjustment, quality reporting, and population health management—organizations can drive better outcomes while staying compliant with evolving CMS regulations.
Dr. Arun Hampapur explains, "The example I often use is that of a leaky bucket. Imagine pouring water into a bucket, but there are small holes at the bottom. If those leaks aren’t plugged, much of the water is lost, reducing the overall financial benefit."
This analogy highlights why an enterprise AI platform is crucial. Risk adjustment efforts bring in revenue, but inefficiencies in claims processing, prior authorization processing and other administrative tasks can drain those financial gains. AI-driven enterprise platforms address these inefficiencies by streamlining processes, improving documentation, and minimizing revenue leakage.
Enterprise platforms also enable continuous learning, allowing the AI to improve over time, making it an investment in both immediate results and long-term sustainability.
The Need for AI Explainability and Compliance
One of the critical considerations in implementing AI for risk adjustment is ensuring transparency and compliance. AI models must be explainable so that clinicians and coding teams can understand the rationale behind each recommendation. Black-box AI models pose regulatory risks, making it essential to use solutions that provide clear, auditable outputs. Wes Stevenson advises, "While AI offers immense potential, its implementation must be thoughtful and aligned with our clinical workflows to truly enhance patient care."
Regulatory bodies require that coding and documentation decisions be defensible. This means AI recommendations must be traceable to clinical evidence. Ensuring that AI solutions align with compliance requirements will be crucial for long-term adoption and trust.
Scaling AI for Future Regulatory Changes
With V28 fully in effect by 2025, Medicare Advantage organizations must act quickly. The industry is moving towards more stringent documentation requirements, and traditional approaches are no longer sufficient. AI solutions must be designed to adapt to future CMS guideline changes, ensuring long-term viability.
As Arun puts it, "AI isn’t about doing our jobs for us—it’s about helping us do them better." Plans that leverage AI-driven risk adjustment will not only navigate V28 effectively but also position themselves for long-term success in value-based care.
The future of risk adjustment isn’t just about increasing revenue or dedicating more resources to patient care—it’s about transformation. And AI is at the heart of that transformation.
Reference:
Wolters Kluwer - “How CMS-HCC Version 28 will impact risk adjustment factor (RAF) scores”, Michael Stearns, MD, CPC, CRC, CFPC, Melissa James, CPC, CPMA, CRC, Kimberly Rykaczewski, RN, BSN, CPC, CRC, February, 2023 - [1]
