What 50 State RHTP Applications Reveal About Rural Health Data Infrastructure

Every state’s path to rural health transformation is unique, but one thing is clear: data infrastructure is the cornerstone of reinventing rural healthcare. To better understand how states are approaching this challenge, our team at Gainwell Technologies LLC conducted an in-depth analysis of all 50 state grant applications for the Rural Health Transformation Program (RHTP).

This analysis was driven by a mission to uncover patterns, best practices, and shared strategies that can help states learn from one another as they move from ambitious plans to operational reality. Far from a one-size-fits-all solution, our findings distill the collective wisdom of states’ approaches, offering a roadmap of possibilities for building the data infrastructure needed to transform rural healthcare.

An Undeniable Consensus: Data is Foundational

While each state’s application reflects its unique situation, states agree on a core principle: Connecting fragmented systems, providers, and data is more than an operational goal. It’s critical for improving how people in rural communities access quality care. However, not all approaches to data infrastructure and exchange are equal.

Our analysis also shows that states are developing this data foundation around key elements:

• Infrastructure: Defining a distinct approach that adds strategic initiatives to existing investments to deliver measurable outcomes.
• Interoperability: Investing in modern data standards to share data across clinical, behavioral, and community systems.
• Actionable Intelligence: Prioritizing analytics platforms, dashboards, AI, and predictive tools for insights providers and decision-makers can actually use.
• Flexibility: Choosing models that match readiness with modularity that makes it possible to scale over time.
• Cybersecurity: Defending against cyber threats and elevating cybersecurity to a shared service to protect rural facilities.

Five Data Infrastructure Models

States’ RHTP applications share these foundational elements, but their infrastructure strategies vary. This isn’t surprising given the need to balance technical maturity, investments, and resources with transformation ambitions. Some states are centralizing the approach. Others are adapting existing networks. Still others are prioritizing specialized capabilities.

While each state’s situation is different, there are common themes across data infrastructure. Our analysis reveals five distinct models that reflect the range of strategic choices states are making to create a data-driven foundation for rural health transformation.

1. Centralized Statewide Integration

There are states planning to centralize the development of a statewide data backbone that eliminates data silos and supports whole-person care. Here, state agencies are taking the lead role in this comprehensive statewide integration. This ambitious approach goes beyond integrating health information exchange (HIE) and electronic health record (EHR) data. Instead, it integrates all data types (such as clinical, claims, behavioral, emergency medical services, pharmacy, social determinants of health, vital records, and more) for true cross-sector interoperability that enables a 360-view of a person’s health needs. For example, states can harmonize EHR information and public health or track disease management programs to get the full picture in a geography while also accessing individual needs at the point of care. These data backbones can integrate or augment existing investments where necessary. 

2. Regional Hubs and Networks

Other states are developing regional hub-and-spoke models. Shared service hubs and regional networks share investments to deliver infrastructure, analytics services, and technical support to rural facilities. This model centralizes support for EHR integration, IT modernization, and system maintenance. Many of these states plan to open grants to community providers to participate in networks or value-based care initiatives. Pooling resources and expertise create economies of scale and makes it possible to provide rural health facilities with critical supports more cost effectively.

3. HIE-led Statewide Data Integration

Some states are prioritizing the enhancement of existing HIE infrastructure for clinical data exchange infrastructure. They are focusing on upgrades and expansions of existing clinical data exchange networks. The HIE entities will play a key role in building out the infrastructure. The goal is to improve clinical interoperability by strengthening and expanding HIE connectivity, EHR interoperability, and point-to point exchange between hospitals, clinics, or regional partners. States can generate integrated insights in real-time to target health initiatives while leaving room to develop statewide utilities that could broaden data types for a complete whole-person perspective. 

4. Specialized Shared Platforms

Several states plan to create specialized platforms to address specific, high-priority use cases in their rural communities, including bed registries, closed-loop referrals, predictive analytics for chronic diseases, and coordination of emergency medical services and non-emergency medical transportation services. This includes a small group focused on building an EHR-forward network. These initiatives often layer advanced capabilities on existing data infrastructure. This approach highlights a move toward sophisticated, multi-data type interventions tailored to address unique rural health needs.

5. Initiative-led Infrastructure

Some states are intentionally designing their data infrastructure to accelerate specific rural health initiatives, including workforce, maternal health, behavioral, and value-based care (VBC) for payment transformation. Providing analytics, attribution, and reporting capabilities makes it possible for states to participate in CMS’s States Advancing All-Payer Health Equity Approaches and Development (AHEAD) models. States are also emphasizing improved interoperability, integrated dashboards, telehealth networks, and cybersecurity at scale to support alternative payment models, global budgets, clinically integrated networks, and ACO-like structures.

Building a Data Foundation for Lasting Success

RHTP funding creates an opportunity to develop a data infrastructure that does more than support focused data. By building now toward a foundation that integrates data related to all the factors that influence rural health—including claims, social determinants of health, and public health—states are in the best position to respond to rural health challenges for years to come.