Over 50% of the eligible population is currently enrolled in a Medicare Advantage (MA) plan. The continuous, increasing growth of MA enrollees highlights the importance of MA plans in ensuring access to care and effective benefits offerings for our senior population.

Expanding access to and ensuring equitable care is a key focus for Centers for Medicare & Medicaid Services (CMS). One of the most recent updates, the proposed rule for Contract Year (CY) 2026, includes proposals such as expanding coverage to anti-obesity medication and behavioral health services, streamlining prior authorization, enforcing AI guardrails to ensure health equity, and enhancing transparency and oversight.

To meet these needs, health plans will face increasing utilization and costs in the years ahead. Risk adjustment efforts tailored to MA plans play a key role in understanding population risk, planning care interventions, and supporting long-term financial sustainability. But these efforts can be dauntingly complex—ensuring data accuracy and streamlining operations, while connecting stakeholders in an ever-evolving landscape requires expertise.

In this white paper, we offer strategies to prepare your risk adjustment programs for these upcoming changes, focusing on learning to improve data quality and accuracy, enhancing documentation accuracy, and building member trust.

Encourage alignment with providers to address documentation challenges

Payer-provider alignment is critical for accurate coding, capturing the chronic conditions that are prevalent among MA enrollees and addressing significant documentation challenges. Consider the following tactics to increase payer-provider alignment for better documentation:

• Leverage technology and EHR systems: Use electronic health records (EHR), health information technology, and interoperability to streamline documentation and data exchange processes.
• Standardize documentation practices: Establish standardized documentation and training protocols across payers and providers to ensure consistency in capturing chronic conditions. Health plans should proactively communicate with providers about the importance of documentation, including specific coding requirements, the transition to ICD-10, and the impact of documentation on risk adjustment payments.
• Implement regular audits and feedback loops: Determine a system of regular audits to review documentation practices not only to identify any gaps, but also to provide feedback to providers about areas for improvement and to understand the nuances of coding in their patient population.

Payer-provider alignment is critical for accurate coding, capturing the chronic conditions that are prevalent among MA enrollees and addressing significant documentation challenges.

Review reporting efforts regularly

Long-term chronic illnesses can be notoriously complex, leading to a host of documentation challenges. To combat these challenges, plans should consider implementing a comprehensive year over year evaluation framework for risk adjustment programs. The framework should include key metrics such as risk score, retrieval rate, coding completion rate, coding accuracy, and others. Consider integrating a trend analysis over multiple years to identify patterns in performance, such as improvements or declines in coding accuracy, retrieval rates, and overall risk scores.

Build team expertise and effective workforce management

A dedicated coder team with in-depth expertise is well-equipped to understand complex cases and the nuances of diagnosis codes, hierarchical condition categories (HCCs), and other risk adjustment elements in this market. Consider some of the ways to keep your coder team up to date, such as:

• Make sure your coder team participates in ongoing training to stay on top of the latest coding guidelines, risk adjustment methodologies, and best practices in documentation.
• Check that staff are well-informed about new regulations and equipped to interpret complex medical records accurately, as well as maintain compliance with the changing regulatory landscape.
• Monitor daily and weekly audit trends to course- correct quickly as necessary, with additional clarifications and regular tests to drive improvements.
• Integrate coder training and quality assurance, as seamless integration fosters a continuous feedback loop for coder education and improved accuracy.
• Establish a culture that prioritizes accuracy and thoroughness in all aspects of their risk adjustment programs, including an environment where coding staff members feel comfortable raising concerns and asking questions.

Stay current on data and reporting requirements for accurate, thorough reviews

Requirements are constantly changing. Monitor guidelines and additional resources made available by governing bodies and associations, such as CMS’s ICD-10 CMS code set, the CMS ICD-10 mapping files, and key resources including the Department of Health and Human Services’ OIG Toolkit to help decrease improper payments in Medicare Advantage through the identification of high-risk diagnosis codes. Consider, too, working with a partner to help your plan implement updates automatically. Keeping analytics current with the latest reporting recommendations and submission changes can speed accuracy and help ensure data accuracy with the latest regulations, especially considering the specificity of some of these changes.

For example, CMS has increased scrutiny of in-home health risk assessments (HRAs) due to concerns about potential misuse for inflating risk-adjusted payments to Medicare Advantage (MA) plans. The CMS-HCC model V28 introduced changes that affect the use of in-home HRAs for risk adjustment purposes. Certain diagnosis codes commonly identified during in-home HRAs have been removed from the risk adjustment model as they are considered less predictive of costs. These codes include diagnoses related to conditions that may not require ongoing treatment or significant healthcare costs and diagnoses prone to overreporting during HRAs (e.g., mild chronic conditions or conditions based solely on patient-reported symptoms).

Keeping analytics current with the latest reporting recommendations and submission changes can speed accuracy and help ensure data accuracy with the latest regulations, especially considering the specificity of some of these changes.

To meet this increased scrutiny, MA plans should shift to more robust documentation practices, since diagnoses captured during in-home HRAs must have clear, robust documentation to withstand audits. The focus should be on using HRAs as a tool for care coordination and identifying well-specified diagnoses that reliably predict future healthcare costs rather than simply increasing risk scores.

Balancing the right technology and guardrails to drive a positive impact and ROI

While long-term trends point to leveraging technology to improve efficiency, it’s important to implement new technologies and AI responsibly to meet transparency standards. Natural language processing (NLP) have been increasingly integrated into medical record coding, automating first-level and second-level reviews of medical records to improve efficiency and results. While enthusiasm for innovation efforts in this space remains high, there’s increasing recognition of the need to combine automation with human expertise and decision-making to optimize impact and respond to increasing coding complexity, regulatory scrutiny, and financial and reputational risk associated with non-compliance.

As suggested by the MA proposed rule, MA organizations should understand and limit the impact of biased data within any AI system and must regularly review any automated systems for discriminatory practices. Leveraging healthcare interoperability with strong expertise, effective partnerships, and data management can help health plans reduce provider abrasion and improve data quality across key areas such as risk adjustment, quality, and payment integrity.

While long-term trends point to leveraging technology to improve efficiency, it’s important to implement new technologies and AI responsibly to meet transparency standards.

 Health plans should assess how certified coders and expert quality assurance processes interact with the NLP engine and how evolving regulatory guidelines, clinical trends, and health plan priorities are integrated in the coding quality framework, from program design to ongoing monitoring and optimization. For example, Cotiviti Second Level Review solution is designed to add an NLP-driven second layer of review of first-pass coding results. Certified coders then review 100% of the charts—not just the ones already flagged by NLP—helping ensure a comprehensive review of population trends and needs.

Build a stronger risk adjustment program

These are just a few of the ways that MA plans can consider improving efforts to prepare for success in the coming years. Key takeaways include:

• Enhancing collaboration with providers to improve payer-provider care coordination and ensure accurate documentation
• Establishing a year-over-year evaluation framework to closely map trends
• Maintaining a dedicated team of coders or leveraging vendor expertise supported by rigorous training and quality assurance processes
• Staying abreast of data and reporting requirements for documentation accuracy
• Invest in the right solution partner for better results