Leaning Into Advanced Technologies to Support State Implementation of New Federal Medicaid Requirements

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, enacted by Congress in July, introduces substantial reforms to the Medicaid program, including new eligibility and enrollment requirements and restrictions on state financing methods. Implementing these changes poses significant challenges and will require states to modernize Medicaid IT systems, including enhancing data matching for eligibility determinations, streamlining communications between consumers and eligibility workers, and improving healthcare access through advanced, more efficient technology solutions.

The White House and the Centers for Medicare & Medicaid Services (CMS) recently a partnership with health care and technology companies aimed at modernizing health care technology infrastructure to boost health outcomes and data interoperability, encompassing Medicaid as part of this vision. Changing Medicaid IT systems has historically been difficult due to the complexity of integrating multiple legacy systems, the costly and time-consuming process of implementing change orders, and the long timeframes for making upgrades. As such, many observers remain cautious about the potential to leverage advanced technologies, including artificial intelligence (AI), to support the implementation of evolving Medicaid program changes in the tight timeline required.

This article focuses on areas of potential opportunity in the application of technology in Medicaid as a result of the passage of H.R. 1. We specifically focus on the application of advanced technologies and AI for: (1) supporting Medicaid work reporting requirements, (2) strengthening rural health care services through the new $50 billion Rural Health Transformation Fund, and (3) improving access to health care services despite reductions in available Medicaid funding.

Medicaid Work Reporting Requirements

H.R. 1 requires that states implement work reporting requirements for adults ages 19 through 64 who are enrolled under Medicaid expansion authority or expansion-like coverage through a section 1115 demonstration. Implementation is set to begin January 1, 2027. States may also request to delay implementation for up to two years, through December 31, 2028, with Secretary approval.

At a minimum, states must verify that individuals have completed 80 hours of qualifying activities for at least one month prior to application. Once enrolled, individuals must verify work for at least one month within every six-month period. The law outlines several categories of individuals who must be exempted and allows states to exempt certain individuals experiencing “short-term hardships.” States are required to verify compliance as well as mandatory and short-term exemptions using available, reliable data (e.g., payroll or claims or utilization data) without requesting information from beneficiaries.

Because of the significant lift in implementing new program requirements and the need to ensure eligible individuals are able to enroll in and maintain their coverage, states have begun to explore the ways they can leverage advanced technologies and AI. The following are specific examples of use cases to support the implementation of work reporting requirements.

• Verifying Compliance or Exemptions.
  • Enhanced data verification for identifying compliance with work reporting requirements.  States can look to advanced technologies to expand the use of “back-end” data matching and linkage processes to enable automatic review of working hours and/or participation in other public programs that require work, such as Supplemental Nutrition Assistance Program (SNAP) and Temporary Assistance for Needy Families (TANF). States may also wish to explore new data offerings and tools that are emerging to mine and integrate data into the eligibility process. This is particularly important in states that currently leverage a limited number of earned income data sources and/or have bifurcated eligibility systems with other public programs.
  • Claims-based exemption classifiers. States could use algorithms to automatically classify members based on medical claims and utilization data to assist in identifying individuals who meet exemptions, such as those classified as “medically frail” (e.g., have a substance use or disabling mental disorder or participate in a drug addiction or alcohol treatment program).
  • AI-powered document ingestion and review. AI-powered tools could be used to extract information from uploaded documents or photos such as timesheets or school letters to reduce or eliminate manual data entry and document review delays that trigger denials or terminations and increase burden on eligibility workers. For example, unrelated to work reporting requirements, Utah, Florida, and Texas use , to: read and categorize uploaded documents; extract key data fields from scanned or uploaded forms; match those documents with the appropriate case or individual; and reduce manual review time.
• Supporting Outreach and Education.
  • Conversational agents. States could use multilingual chat bots to answer administrative questions such as “How do I report hours?” and meet basic enrollment and eligibility verification information needs to cut call-center wait times and increase accessibility for low-literacy users and across multiple languages. For example, unrelated to work reporting requirements, the Louisiana Department of Health has deployed a Frequently Asked Questions (FAQ) chatbot called to respond to FAQs for call centers in English, Spanish, and Vietnamese.
• AI-supported outreach and nudges. AI-based tools can efficiently create outreach materials with quicker design and more languages and modalities to increase personalized outreach to remind individuals to respond to requests for information and complete the renewal process.

It will be critical that states and technology companies establish guardrails when leveraging advanced technologies to protect against inappropriate coverage loss and to ensure access, privacy, and due process. For example, AI should not be the sole basis for terminating, denying, or reducing Medicaid coverage; all critical decisions must be reviewed and approved by a qualified human eligibility worker. Any chatbot or automated system interacting with applicants must clearly disclose that it is not a human, explain its role, be accessible to individuals with disabilities, and available in multiple languages. Live support for populations with low literacy and other barriers to engagement will still be needed, but with lower demand. Earning trust of those enrolled in Medicaid will be important to these efforts. Only the minimum necessary data should be collected and processed by AI systems and all AI systems must comply with federal and state privacy laws.

Rural Health Transformation Fund

The Rural Health Transformation Fund authorized under H.R.1 was to federal Medicaid funding. While the fund will not be enough to fill the estimated , it does provide some available resources that states can leverage to improve access to rural providers. Applications for the funds are expected to be released in the fall, and CMS is statutorily required to approve or deny state plans by December 31, 2025. Of the total funding available, $25 billion will be distributed by CMS “equally among all states with an approved application,” and CMS has discretion in determining how to allocate the remaining $25 billion.

While it is unclear what criteria CMS will use to approve or deny applications and distribute funds, a key area of focus in the statute is investment in technology platforms that enhance care delivery, particularly those that are consumer-facing, such as remote monitoring tools, telehealth, and AI-enabled systems. States must use program funds for three or more of the approved “use of funds" categories outlined in H.R.1. While many of the “use of funds” categories do not explicitly mention technology, their aims may be enhanced by it (e.g., opioid and mental health services, innovative models of care). Other fund utilization options directly address investing in rural hospital technology and infrastructure, such as:

• Promoting consumer-facing and technology-driven solutions for the prevention and management of chronic disease;
• Providing training and assistance for the development and adoption of technology-enabled solutions in rural hospitals, like remote monitoring, AI, or robotics; and
• Providing assistance for information technology to enhance cybersecurity and improve patient health outcomes or efficiency

States have an opportunity to build upon successes they have had in ameliorating rural health access issues and supporting rural hospital financing through telehealth, strategic health system partnerships, and technological investment. Innovative initiatives in other states can also serve as examples. For example, South Carolina has had great success among rural hospitals and larger medical centers. These partnerships, supported by considerable state investment and led by the Medical University of South Carolina (MUSC) provide rural patients with local access to specialized care, help rural hospitals retain patients to support their financial health, and give rural providers access to crucial support and mentorship.

Technology to Deliver the Same or Better Services at Lower Costs

Given the significant funding reductions for Medicaid in H.R. 1, adopting technology to help deliver services at lower cost but with the same or better outcomes will be a high priority for state Medicaid programs. The most promising examples include the following:

• Telehealth. Telehealth can improve access for rural individuals, many of whom are Medicaid-enrolled, and holds promise for . Lessons learned show that during the COVID-19 pandemic, telehealth may have helped Medicaid members maintain access to medications and care for ongoing conditions, and that telehealth did not drive overutilization or result in low consumer satisfaction. A recent from the Peterson Health Technology Institute found that physical therapist-guided solutions produced outcomes comparable to in-person physical therapy (i.e., improving pain and function) and reduced net spending relative to in-person physical therapy.
• Care coordination. Complex care coordination may also help drive down costs and improve outcomes by helping to identify and support Medicaid’s most complex and expensive members. Care coordination technology partners can improve outcomes by fostering a strong relationship with members and helping to manage complex care needs. Care coordination services can reduce expensive care, such as emergency department visits and inpatient stays, and improve health outcomes.
• Population health management. The practice of proactively helping people stay well by identifying illnesses before they worsen should be of great interest to payers and companies because the approach can reduce the odds of costly care. AI can be especially helpful for population health management by making effective use of large data to identify high-need and high-cost patients, automating proactive outreach to members, mitigating disparities by addressing language or other barriers to care, and reducing administrative burden and costs.

Looking Ahead

H.R. 1 significantly reduces federal funding for Medicaid while requiring states to maintain current operations and implement new, complex eligibility and enrollment rules. This creates a major administrative and financial burden for state Medicaid agencies. However, advanced technologies, including AI, offer promising solutions—if they are designed with a deep understanding of federal and state Medicaid program requirements and focused on helping eligible individuals enroll in and keep coverage, while improving access to physical and behavioral health care. This is a critical moment for states and technology partners to innovate by automating processes, easing administrative demands, and expanding access to high-quality care at lower costs.

Manat on Health subscribers can see this Manatt on Health for more on H.R. 1,

 Manat on Health subscribers can see this Manatt on Health for more on the Health Technology Ecosystem announcement

is looking to develop best practices for the use of AI to help individuals complete their Medicaid application and to help states decide if applicants meet the new Medicaid requirements.

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