Data Infrastructure Should Top Every State’s RHTP Spending List

March 30, 2026

Freedman HealthCare (FHC) has supported multiple states in developing and implementing their Rural Health Transformation Programs. FHC specializes in integrated health data systems, healthcare measurement and benchmarking, and workforce data infrastructure and reporting.

By Margaret Tiedemann, MA, PMP, Consultant, and Chad MacLeod, Senior Consultant

The Problem: Rural Health Data Is Fragmented

Across rural America, critical health data sits trapped in silos. A patient’s claims history lives in one system, their clinical records in another, and their social services interactions in yet another. Without the ability to connect these data, states will continue to struggle to understand community health needs, coordinate care, or measure whether their programs are working. In December 2025, the Centers for Medicare and Medicaid Services (CMS) awarded $10 billion in first-year funding for the Rural Health Transformation Program (RHTP) across all 50 states. Over the course of the next five years, a total of $50 billion will be used to improve healthcare access, delivery, and outcomes in rural America guided by five strategic goals: (1) Make Rural America Healthy Again, (2) Sustainable Access, (3) Workforce Development, (4) Innovative Care, and (4) Tech Innovation.

One of CMS’s five strategic goals – Tech Innovation – seeks to modernize rural healthcare through enhanced IT infrastructure, telehealth, data sharing, and emerging technologies.[1] Several states are already planning to use their RHTP funds to develop or enhance Integrated Data Systems (IDS), and for good reason.

What is an Integrated Data System and Why Does it Matter?

An IDS connects data systems that have traditionally been siloed due to technological, governance, financial, or other restrictions. By establishing a longitudinal record across healthcare, social services, and community-based systems, an IDS recognizes what everyone working in rural health already knows: an individual’s needs, risks, conditions, and outcomes are interconnected, as are the programs and policies designed to address them.

Every state’s IDS will look different, but the core principle is the same: bring together the data sources most relevant to a community’s needs to support whole-person care and population health. Examples of data sets that may feed into an IDS include the following:

Data Sets	Example Systems	Why it matters for rural health
Claims and billing	APCD, MMIS	Reveals health insurance utilization patterns, cost drivers, and access gaps
Clinical records	HIE, Hospital Discharge Data, EHR	Tracks patient outcomes, care transitions, and clinical quality
Eligibility and enrollment	Medicaid E&E	Identifies coverage gaps and eligible-but-unenrolled populations in underserved areas
Social services and community resources	Dept of Corrections, HMIS, case management	Connects housing, healthcare, food, and justice system interactions
Public health and vital records	Immunization registries, lab databases, birth/death records	Supports disease surveillance, maternal health monitoring, and health equity reporting
Education	State Dept. of Education	Links school-based health services and outcomes

How States are Already Putting IDS to Work

Several states have already identified concrete IDS applications in their RHTP proposals:

What the IDS enables	State Example
Real-time care coordination Remote patient monitoring, care coordination, and bed monitoring	Massachusetts – Combining cross-agency data to track service and bed availability in real time[2]
Population health monitoring Public health surveillance across rural communities and chronic disease registries	Utah – Creating a statewide chronic disease monitoring system[3]
Predictive analytics Identifying high-risk patients to avoid preventable hospitalizations and ED visits	Connecticut – Launching a Rural Predictive Analytics and Care Coordination Platform (CR-PACP) to predict and help avoid unnecessary care[4]
Performance and quality reporting Dashboards and metrics for quality, cost, and outcomes – the data CMS will want to see	Vermont – Developing a suite of dashboards to support transparency and decision making[5]

Where to Focus: Five Key Milestones for Building an IDS

The roadmap to a fully-functional, robust IDS includes several key milestones, including:

Stakeholder engagement: Facilitate conversation and coordination across a multi-stakeholder group, commonly including individuals with lived experience, clinical providers, health insurance payers, program leads, State agencies, and other subject matter experts to ensure alignment and buy-in on how to operationally achieve the objectives of the RHTP strategic goal.
Data Governance: Develop appropriate safeguards, including data governance and data security requirements, to ensure data sets are properly submitted to, stored within, and disseminated from the IDS platform.
Technology infrastructure: Establish interoperability across identified data systems (e.g., HIE, EHR, APCD, etc.) in alignment with data governance requirements to ensure the successful ingestion and integration of the selected data sets into the IDS platform.
Onboarding: Ensure the entities sharing data with the IDS are empowered to use, support, and maintain the sharing of information with the IDS over time while meeting data quality standards.
Applications: Apply data from the IDS to support a variety of end users, such as patients, providers, and policy makers, through reports, dashboards, and other data products.

Why This Matters for State Leaders

The RHTP is a cooperative agreement, which means CMS will be evaluating state performance throughout the five-year grant period. Funding in Years 2 through 5 is not guaranteed. States that can demonstrate measurable progress – showing they can track outcomes across programs, identify high-risk populations, and report on quality and cost – will be in a stronger position to secure continued funding. An IDS provides exactly this capability.

Building an IDS takes sustained effort, but the payoff is substantial. States hoping to build an IDS or with newer systems can look to mature models for guidance. Two leading examples show what’s possible:

The Massachusetts Department of Public Health operates the State’s Public Health Data Warehouse, which combines 30 data sources to support public health reporting on priority areas as identified by DPH, such as substance use, maternal health, and health and racial equity.
The Rhode Island Office of Data, Analytics, and Evaluation manages the State’s Data Ecosystem, which brings together data from more than 10 State agencies to enable advanced reporting about the health-related experiences of Rhode Island residents

Freedman HealthCare understands the complexity of IDS platforms and has deep experience supporting states through each stage of the IDS lifecycle – from stakeholder engagement through ongoing operations.

Have questions about how your state can use RHTP funding to build or strengthen an Integrated Data System? We’d love to hear from you.

Reach out to us at [email protected] or [email protected].

Footnotes:

[1] Rural Health Transformation Program. Centers for Medicare & Medicaid Services. https://www.cms.gov/priorities/rural-health-transformation-rht-program/overview#:~:text=Providing%20payments%20to%20health%20care,services%2C%20and%20mental%20health%20services.

[2] MA HRTP Application (p. 17). https://www.mass.gov/doc/rural-health-transformation-program-application/download

[3] Utah RHTP Application (p.39). https://dhhs.utah.gov/wp-content/uploads/Rural-Health-Transformation-Plan.pdf

[4] CT RHTP Application (p. 36) https://portal.ct.gov/dss/-/media/departments-and-agencies/dss/health-and-home-care/rural-health-transformation-program/cms_project_narrative_20251105.pdf?rev=67df88dd07554e4f86bda4eaa901aeaf&hash=2C6F53F10A4D46641E4423A7C5C2957F

[5] VT RHTP Application (p. 15) https://healthcarereform.vermont.gov/sites/hcr/files/documents/Vermont%20RHT%20Program%20Application%20Project%20Narrative%2002-11-26.pdf