The Centers for Medicare & Medicaid Services (CMS) has introduced what it calls an “aggressive” approach to Medicare Advantage Risk Adjustment Data Validation (RADV) audits, aiming to review every Medicare Advantage (MA) contract annually and expedite the backlog of audits for payment years 2018 through 2024. This shift, following up on CMS’s previous goal to recover $4.7 billion from MA plan overpayments, represents a significant escalation in oversight, compelling MA plan leaders to reassess and fortify their coding and compliance strategies.
Here, we explore CMS’s new audit methodology, its implications for MA plans, and actionable strategies driven by technology, analytics, and strategic partnerships to prepare for and thrive under this increased scrutiny.
Previously, RADV audits were limited, with only approximately 60 contracts undergoing scrutiny for each payment year. This newly expanded scope stems from mounting concerns over unsupported diagnosis codes, which have led to overpayments in the Medicare Advantage program. The elimination of the fee-for-service (FFS) adjuster in the final CMS rule adds further financial implications, increasing the burden on plans to ensure coding accuracy, data completeness, and compliance with HCC reporting requirements. With penalties potentially reaching billions of dollars, MA plans should act swiftly to bolster their audit readiness, considering these four strategies:
CMS’s intensified audits underscore the need for meticulous coding practices. Health plans should leverage advancements in advanced analytics, artificial intelligence (AI), and natural language processing (NLP) tools to monitor coding quality and identify high-risk diagnosis codes. These technologies can help meet increased auditing volume and tight deadlines by prioritizing critical documentation and ensuring coders focus on the most relevant sections of medical records.
AI tools can highlight potential gaps and inaccuracies within lengthy charts, enabling coders to navigate complex medical records more effectively. Machine learning can quickly identify discrepancies and common errors such as HCCs reported by the wrong specialty—or conditions primarily diagnosed in hospital or inpatient settings being reporting in the outpatient or clinic settings—allowing humans to focus on coding accuracy and subsequent steps. MA plans should also have an ongoing commitment to evaluating the performance of AI tools with dedicated efforts including regular reporting and data auditing.
Integrating tech innovations with expert processes and oversight remains essential to driving consistent performance and improving accuracy. Health plans should invest in establishing a robust and proactive compliance framework, including coding guidelines, documentation alignment, and sophisticated quality assurance and coder training programs, to continuously monitor and ensure data quality.
Continuous clinical coder training is essential to address ambiguities or errors and improve the specificity and accuracy of submitted diagnoses. By integrating AI-enabled solutions into their workflows, MA plans can improve efficiency without sacrificing quality and compliance.
Comprehensive provider collaboration is a cornerstone of successful audit preparation. MA plans must engage their provider networks to ensure accurate and compliant documentation while informing them about upcoming audits and the rationale behind them. Health plans should work closely with providers to align their practices with hierarchical condition category (HCC) reporting requirements and ensure all conditions evaluated, monitored, or treated during encounters are properly documented.
Best practices include building strategic partnerships, direct connections, and dedicated education efforts. Achieving interoperability through national exchanges and direct connections to large providers will be invaluable. Given the short timelines of RADV audits, plans need to have swift access to as many records as possible.
Another effective approach is to conduct health risk assessments (HRAs) and follow up with primary care physicians to address diagnoses identified in HRAs. This proactive strategy not only closes care gaps but also improves the completeness of medical records, reducing the likelihood of unsupported codes during audits. Proactive follow-up with the member’s primary care provider is critical, especially as the Office of Inspector General (OIG) has issued numerous reports questioning payer practices around how HRA data is used.
Help ensure that every member of your plan’s audit response team undergoes comprehensive RADV training using the latest CMS materials and subscribes to updates and tools available through the CMS Registration for Technical Assistance Portal (REGTAP).
Leverage and integrate in your processes resources such as the toolkit provided by OIG, which compiles the high-risk groups OIG has identified in its audits for diagnosis codes that were consistently submitted incorrectly to CMS. This toolkit also contains the SQL codes used by CMS to conduct audits, enabling payers to create a list of members to perform chart review and validate that codes are correct.
To address CMS concerns over unsupported diagnoses, MA plans should leverage capabilities such as prospective and retrospective analytics. Prospective analytics help ensure that documentation is complete and accurate at the point of care. Retrospective analytics remain critical for validating previously submitted chronic conditions and identifying coding errors. By combining these analytical strategies, health plans can optimize their documentation processes, mitigate risk, and improve audit outcomes. Prioritizing charts with the highest risk of coding gaps allows health plans to maximize their resources and achieve greater ROI in audit preparation efforts.
Introducing a second-pass review of coding results can further improve accuracy. This additional review of coding results has increasingly become an industry standard amid increased audit scrutiny and coding complexity. As previously noted, health plans should ensure integration of technology-powered efficiency with expert oversight to ensure this solution creates value and streamlines their ability to improve results.
CMS’s new RADV audit strategy presents a formidable challenge for MA plans, emphasizing the importance of coding accuracy, provider collaboration, key industry resources, and strategic use of analytics. By adopting these four strategies, health plans can not only navigate the heightened audit environment but also enhance member care delivery and operational efficiency.
In the face of greater regulatory oversight, MA plans must view RADV audits as an opportunity to refine their processes, strengthen compliance, and invest in technologies and human expertise. Preparing for annual contract audits and expedited reviews of prior payment years requires foresight, collaboration, and a commitment to continuous improvement. With the right tools and strategies, MA plans can rise to the occasion, ensuring their risk adjustment programs meet the highest standards of accountability and care.
To build on these critical steps to prepare for RADV audit success, read our recent white paper by my colleague Amanda Liu, product strategy solution director, to help you: