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THE HIDDEN THREAD CONNECTING H.R. 1
For state Medicaid directors and health and human services leaders, the clock is already ticking on H.R. 1 timelines. The act presents a sweeping set of requirements that touch almost every corner of your agency.
On one side, there is the Rural Health Transformation Program (RHTP), demanding sustainable solutions for fragmented rural health systems and infrastructures. On the other, there are strict new penalties for Supplemental Nutrition Assistance Program payment errors. Simultaneously, you must implement rigorous community engagement verification (CEV) standards without breaking your administrative budget or losing eligible members in the process.
It is easy to view these as separate challenges to solve. You might be tempted to stand up a task force for rural health, a separate team for SNAP integrity and a third for workforce verification.
While the mandates are distinct, the solution is singular. The thread that connects every requirement of H.R. 1 — and the key to moving from reactive adherence to proactive modernization — is data.
Every mandate in the act ultimately converges at the same operational point: eligibility determination, enrollment and ongoing renewal. Whether states are stabilizing rural hospitals, reducing SNAP error rates or verifying community engagement, success depends on how accurately and efficiently eligibility decisions are made and maintained over time. If those workflows are fragmented or manual, each new requirement compounds risk, cost and member churn.
If you look at H.R. 1 holistically instead of as a checklist of disparate mandates, you will see it for what it truly is: a catalyst to unify your data ecosystem in a cost-effective way.
RURAL HEALTH: SUSTAINABILITY STARTS WITH ANALYTICS
Rural hospitals are the lifeblood of their communities, and H.R. 1 provides critical funding through the RHTP to stabilize these vital institutions. This funding creates an incredible opportunity to address challenges and reimagine operational models for long-term success. Achieving true transformation requires a clear understanding of what is happening on the ground and moving beyond simple claims data to create a comprehensive view of the rural health landscape.
This is where the Centers for Medicare and Medicaid Services (CMS) RHTP intersects with advanced analytics. To fix the system and maximize federal funding, it’s important to understand the social determinants of health, health conditions and community factors driving costs and outcomes in these areas.
Consider the power of a longitudinal health record (LHR). Moving beyond siloed data sets reveals that a rural hospital’s emergency room is overcrowded not because of clinical failures, but because of a lack of local primary care or transportation barriers. More importantly, the LHR will provide actionable data about which individual members need primary care or transportation services.
The power of a fully connected network is transformative. Integrating and processing all types of health-care data into a single network can meet the needs of the stakeholders in the rural health ecosystem. Providers gain access to whole-person-care insights at the point of care; administrators benefit from cross-program insights; care managers coordinate more effectively with other entities; and agencies receive real-time, comprehensive CMS reporting. All of this becomes possible with a unified and interoperable data backbone.
With the right data partners, you can:
- Use predictive intelligence to assess health risks before they become emergencies.
- Unify diverse data sources — from clinical records to social needs — into a single source of truth.
- Measure program effectiveness in real time, ensuring that RHTP funds are actually improving outcomes.
H.R. 1 asks you to save rural health care. Data tells you how to do it.
SNAP INTEGRITY: THE COST OF DISCONNECTED DATA
The pressure on SNAP performance is immediate and severe. Under H.R. 1, states that do not reduce error rates below 6 percent by FY 2026 face significant financial penalties.
The current reality is stark. According to the U.S. Department of Agriculture, SNAP payment errors averaged 10.93 percent nationally in FY 2024, including $9.3 billion in overpayments.
If your state is one of the more than 40 with error rates above the 6 percent threshold, the financial risk is significant. It is costly to rely on retrospective audits or slow-moving verification processes. You need speed, and you need accuracy. And you need it now.
This is a data issue. High error rates often stem from a lag in information — a change in income or household status that current systems didn’t catch in time.
Many states still rely on periodic file exchanges and retrospective reviews to manage eligibility and payment accuracy. H.R. 1 exposes the limits of that approach. When verification happens weeks or months after a change occurs, overpayments accumulate and compliance risk grows. Meeting H.R. 1 thresholds requires moving from periodic checks to real-time or near-real-time data orchestration embedded directly into operational workflows.
This isn’t just about avoiding penalties — it’s about safeguarding the integrity of SNAP. Leveraging data to prevent $9.3 billion in waste ensures that vital funds are preserved for the families who need them most.
COMMUNITY ENGAGEMENT: VERIFICATION WITHOUT FRICTION
Perhaps the most operationally complex requirement of H.R. 1 is the mandate for CEV in which states are required to verify that Medicaid beneficiaries are meeting work or volunteer requirements.
The risk here is twofold. First, there is the administrative burden for staff to process millions of documents. Second, and more importantly, there is the risk of “churn” — eligible members losing coverage simply because they couldn’t navigate the paperwork.
You need a system that verifies status automatically, minimizing the need for member outreach and reducing the burden on members.
Achieving this level of precision requires a next-generation approach to data matching — one that avoids reliance on a single data point. By applying advanced algorithms across multiple relevant data sources, the need for members to search for and scan pay stubs is eliminated, enabling instant status verification. This reduces the burden for caseworkers and ensures that coverage continues for those who follow the rules.
THE STRATEGY: DON’T JUST COMPLY — MODERNIZE
H.R. 1 is undoubtedly a mandate. But viewing it solely as a compliance exercise risks missing the bigger picture — and jeopardizing significant federal funding.
Every requirement in this act is designed to drive toward a single destination: creating a modern, data-driven enterprise. Investments made to satisfy the RHTP requirements can also power a broader population health strategy. Predictive models built for SNAP integrity can be adapted to prevent fraud in other programs. Interoperability established for community engagement can improve care coordination across the board.
With H.R. 1 deadlines fast approaching, time is limited, but the opportunity for strategic action remains. Rather than scrambling to piece together disparate solutions for each mandate, a more effective approach is to address immediate compliance needs while laying the groundwork for long-term transformation.
The key lies in the data.
H.R. 1 can be a catalyst for change and an opportunity to drive innovation, unify systems and create a more efficient, connected and impactful approach to serving communities.
About the Author
Gainwell Technologies LLC is the trusted leader in digital and cloud-enabled solutions for health and human services programs. With over 50 years of proven expertise, we help modernize Medicaid and public health programs with innovative solutions to improve operational efficiency and enhance provider experiences, while also safeguarding program integrity with HMS verification and cost containment services. Combining cutting-edge technology with an unwavering commitment to service excellence, Gainwell delivers scalable, impactful solutions that advance public health and create transformational results. Learn more at gainwelltechnologies.com
