HIMSS 2026 Recap: How Data Standards Power Rural Health Transformation

By: Emily Anders, Director, Payments Strategy 

Earlier this month at HIMSS, I had the opportunity to represent the Gravity Project at the HL7 International exhibit, presenting alongside Katie Keating, Vice President of Solutions Engineering, on the role shared data standards play in powering rural health transformation. 

From Activity to Impact: Shifting How We Think About SDOH Data

For the past decade, there’s been a meaningful shift in how we think about health. Community-based services that address social drivers of health (SDOH)— or the non-medical factors that impact our health like food access, housing support, transportation, and maternal health services—are no longer seen as adjacent to healthcare, but as essential components of it.

We’ve also worked with our customers to build a growing body of evidence showing that when these needs are addressed, we see real outcomes: reduced total cost of care, fewer ED visits, and improved clinical measures like A1C and blood pressure control.

But one of the biggest challenges has remained: proving ROI consistently and at scale.

Moving from activity tracking (“a referral was made”) to outcome attribution (“this intervention improved this person’s health and reduced cost”) requires more than programs and partnerships. It requires a shared language.

Why Data Standards Matter

That’s where SDOH data standards come in.

Standards-based infrastructure,  like the work advanced through the Gravity Project and enabled through HL7 FHIR, allows clinical providers, community-based organizations, payers, and states to speak the same language. It creates consistency in how we:

• Capture social risk and needs
• Send and receive referrals
• Document services delivered
• Track outcomes and close the loop

Without that shared foundation, even the most well-designed programs struggle to demonstrate impact in a way that is measurable, repeatable, and scalable.

What This Looks Like in Practice

We’re now seeing leading states operationalize data standardization in meaningful ways.

In North Carolina’s Healthy Opportunities Pilots (HOP), the state built a first-of-its-kind program to pay for evidence-based, non-medical services for Medicaid members. In its interim evaluation, the program demonstrated $85 PMPM savings for enrolled members.

That result didn’t happen by chance. It required the ability to connect data across many different stakeholders like managed care plans, clinically integrated networks, and community-based organizations, and to consistently track services delivered and outcomes. 

Similarly, Missouri’s Transformation of Rural Community Health (ToRCH) initiative is showing how a hospital-led, community-based model can improve care coordination while also reducing administrative burden. Connecting hospitals and community organizations through shared, standards-based infrastructure, show the program is enabling more timely follow-up, better visibility into services, and HEDIS gap closures. 

In both cases, standards-based infrastructure t makes it possible to link actions to outcomes, with proven results. 

Why Data Standards Matter for Rural Health

This conversation is especially timely as states begin preparing for the Rural Health Transformation Program (RHTP), a significant, time-bound federal investment aimed at strengthening rural health systems.

At its core, the opportunity is not just to fund new programs, but to build systems that are sustainable. 

That means:

• Supporting rural providers under financial strain
• Expanding workforce capacity, including community health workers and doulas
• Investing in infrastructure that connects clinical and community care
• Demonstrating measurable improvements in cost and outcomes

But across all of these priorities, one requirement stands out: the ability to measure impact.

And in rural communities, where care often involves a complex network of providers, community organizations, and support services, that measurement challenge is even more pronounced.

Bringing It Back to the Individual: A Maternal Health Impact Story

Maternal health is a key priority across many states’ RHTP strategy. During our session, we used this as a lens to illustrate why standards-based infrastructure is critical to achieving meaningful, measurable outcomes.

Pregnancy-related mortality is up to 50% higher for rural individuals compared to their urban counterparts, and in some analyses, rates are nearly twice as high in rural areas. We also see higher rates of severe maternal morbidity, infant mortality, and complications like preterm birth in rural communities.

At the same time, access to care is declining. Over two-thirds of rural counties lack hospital-based obstetric services, and many patients are traveling 30–50+ minutes to reach care, if it’s available at all.

Imagine a pregnant patient in a rural community. She may be enrolled in Medicaid and receiving clinical care from a provider located over an hour away, without access to transportation and fresh produce. So when states set goals like improving maternal health outcomes as part of their rural health strategies, this is the reality they need to help individuals overcome. 

States may employ strategies to meet the pregnant mom where she is – connecting her to a community health worker to navigate access to transportation and food, and a doula to provide important prenatal education, supportive services, and advocacy. These non-clinical supports might be approved to be reimbursed by Medicaid within their state. Meanwhile, her provider is documenting in an EHR, the birthing hospital is documenting in another system, and the CHW/doulas in a third system, or using spreadsheets. At the policy level, a state Medicaid analyst who has never met the member, is trying to answer a critical question:

What actually improved outcomes for this patient, and what should we scale in order to positively impact more pregnant individuals?

That’s where standards-based infrastructure becomes essential. By understanding the social risk data the individual was experiencing (LOINC, snomed), what referrals were sent and what supportive services the individual was able to access and what outcome occurred (FHIR), what billable services were provided and reimbursed (Z-codes, HCPCs codes, X12 EDI), and enabling all of these stakeholders to be able to support this pregnant individual on their journey to receiving care (FHIR APIs), the analysts at the policy level are able to understand how programs on the ground are running and whether those interventions are making the impact they need. Without a shared language across all of these actors, it’s incredibly difficult to connect interventions to outcomes. This is why the work the Gravity Project does to create shared language and exchange is fundamental for programs to be scalable, replicable, and sustainable.

The Path Forward: Leveraging Data Standards to Power Better Rural Health Outcomes

Rural health transformation isn’t just about funding or new programs. It’s about building the infrastructure to enable providers to coordinate care across the continuum through secure data exchange, speak the same language through shared terminology, and measure the impact of programs in order to ensure sustainability. Standards are the foundation of that work, turning fragmented data into coordinated systems, and uncovering insights on impact.

Thanks to the important work done by the Gravity Project, technology infrastructure can adopt these shared standards and leverage interoperable exchange through HL7 FHIR to connect clinical care, community services, and policy analysis. This is what makes it possible to measure, scale, and sustain interventions.

When everyone is speaking the same data language, we don’t just track one-off activities. We can see what works and expand it to improve care for more people in rural communities.

Learn more about partnering with Unite Us for rural health transformation