Advocating for Equity and Accountability in Medicare Advantage Policies

At the Center for Telehealth and e-Health Law (CTeL), we are dedicated to shaping the future of digital health through thoughtful advocacy and research. Recently, we submitted comments to the Centers for Medicare and Medicaid Services (CMS) regarding their proposed policies for the Medicare Advantage (MA) and Medicare Prescription Drug programs for contract year 2026. These policies represent a critical opportunity to ensure that emerging technologies like artificial intelligence (AI) are deployed ethically and equitably within healthcare systems.

We applaud CMS for proposing to explicitly clarify that civil rights statutes apply to the use of AI in administering MA plans. Biases in AI can emerge at every stage of development, and if left unchecked, they risk exacerbating health inequities. By recognizing this issue, CMS is taking a vital step toward ensuring fairness and accountability in the use of advanced technologies in healthcare.

Our Recommendations to CMS

  1. Addressing Algorithmic Bias in AI
    Drawing on insights from the October 2024 Senate Permanent Subcommittee on Investigations report, we emphasized how AI misuse in patient care determinations can have serious consequences. For example, we noted instances where AI was used to determine patient lengths of stay or admission decisions in ways that were not always aligned with best practices. We urged CMS to finalize its proposal to collect prior authorization data by service category and to use that data to identify and address systemic issues.

  2. Strengthening Oversight and Regulation
    To ensure transparency and accountability, we recommended that CMS conduct targeted audits of MA plans, particularly those showing increases in adverse determinations following the adoption of AI technologies. Additionally, we encouraged CMS to issue new regulations for utilization management committees to prevent predictive technologies from unduly influencing human reviewers.

  3. Promoting Fairness and Community Engagement
    Through our Artificial Intelligence Blue Ribbon Collaborative, we’ve worked with experts across medicine, science, and law to study the intersection of AI and healthcare. From this work, we’ve learned that fairness-aware approaches and active community engagement are essential for building trust in AI technologies. These strategies are critical for ensuring that digital health tools are developed and implemented in ways that benefit all patients.

  4. Supporting Administrators with Technical Assistance
    We also called on CMS to work with the HHS Office of the Assistant Secretary for Technology Policy and the HHS Office for Civil Rights to develop resources that help administrators identify and mitigate biases in AI systems. This includes:

    • AI safety registries.

    • Tools to evaluate and improve training data completeness.

    • Model policies for AI governance.

    • Staff training materials for interpreting AI outputs.

    • A registry of AI tools with known risks of discrimination.

We strongly support CMS’ proposal to explicitly clarify that civil rights statutes apply to the use of artificial intelligence (AI) in the administration of Medicare Advantage (MA) plans.
— CTeL

Our Commitment to Advancing Digital Health

At CTeL, we believe that AI has tremendous potential to transform healthcare, but its use must be guided by principles of equity, transparency, and accountability. That’s why we’re proud to lead initiatives like the Artificial Intelligence Blue Ribbon Collaborative and to advocate for policies that safeguard patients while fostering innovation.

We thank CMS for the opportunity to provide feedback on these critical issues, and we look forward to continuing our work to ensure that digital health technologies are used responsibly and effectively to improve patient outcomes. Together, we can shape a future where telehealth and AI are tools for positive and equitable change.

For more on our advocacy efforts and ongoing initiatives, visit our website.

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