Dental Data Exchange: The Interoperability Gap HIEs Rarely Address

Interoperability discussions usually focus on hospitals, certified EHRs, and advanced APIs. Behavioral health and social care enter later. Dental data often doesn’t show up at all.

That matters.

Oral health is tightly connected with whole person care — yet dental data exchange remains one of the least addressed interoperability challenges. This isn’t due to lack of relevance but because the work sits squarely in the last mile where real-world workflows, variable technology, and uneven standards collide.

Why Oral Health Data Belongs in the Interoperability Conversation

Oral health impacts chronic disease outcomes, surgical risk, and preventive health. Yet dental clinical data rarely flows into medical records or care coordination pathways in structured form.

Technical standards do exist to support bi-directional dental-medical data exchange using FHIR and other models. HL7’s Dental Data Exchange Implementation Guide defines profiles for dental referrals, consultation notes, and clinical content structured for interoperability among dental and medical providers. (FHIR Build)

Research in dental informatics underscores the need for interoperable systems — noting that while semantic standards exist, inconsistent implementation of dental vocabularies and structures leads to challenges in data sharing and reuse across platforms. (PMC)

Federally Qualified Health Centers: A Logical Starting Point

Dental services are not niche in safety-net settings. According to recent analyses, the proportion of FQHCs providing oral health services increased from about 76% in 2012 to over 81% as of 2021. (Center for Health Workforce Studies)

That makes FQHCs a substantial part of the U.S. oral health delivery ecosystem. These centers serve millions of patients annually and often integrate dental and medical care on the same campus — a rare example of “co-location” in safety-net medicine.

Many HIEs already partner with FQHCs for medical data exchange, quality reporting, immunization reporting, and care alerts. That existing relationship is a major strategic advantage. Where medical and dental services co-exist, data exchange pilots can leverage established governance, connectivity, and workflows.

Research examining HIE access from dental clinics in FQHC settings found that dentists and staff did access shared medical data when available, though overall usage remained low due to workflow and usability barriers. This suggests that when the infrastructure exists, clinicians will use it — but only if it fits into workflow. (PMC)

CareQuest Institute for Oral Health: Driving Integration

This interoperability gap is not just an IT problem. It reflects broader structural barriers that organizations like CareQuest Institute for Oral Health are actively addressing.

CareQuest is a national nonprofit focused on transforming oral health to improve health equity and integration. They work across policy, research, analytics, workforce development, and care transformation to ensure oral health is part of the broader health system rather than siloed apart.

Their analytics, grants, and programmatic efforts address why oral health inclusion matters at the population level.

Initiatives like Medical Oral Expanded Care (MORE Care) explicitly aim to strengthen coordination between medical and dental providers by improving referral networks and shared workflows that include data sharing. CareQuest’s involvement in national interoperability dialogues highlights that dental data exchange is central to advancing a truly integrated healthcare ecosystem.

Barriers to Dental Data Exchange

1. Dental Systems Often Lack Interoperability-Ready Architecture

Unlike certified medical EHRs with defined interoperability requirements, many dental practices — including some in FQHCs — rely on practice management systems or EDRs that do not natively support structured data exchange out of the box.

Even when EDRs like Dentrix, EagleSoft, or integrated modules exist, the degree to which they support standardized clinical content and exchange varies widely.

Dental data exchange standards like HL7 FHIR and CDA are emerging, but adoption remains optional. Without a certification floor and consistent vendor implementation, the data simply isn’t structured in a way that can be reliably shared across systems. (FHIR Build)

2. Lack of a Standardized Interoperability Baseline

Medical EHR vendors participate in certification programs and have a consistent baseline for interoperability. Dental vendors do not.

This means dental technology offerings vary wildly in features, structure, and exchange capability. Even when data could be shared, the lack of a common baseline makes it hard for an HIE to scale exchange across multiple dental practices.

Efforts such as the HL7 Dental Data Exchange Implementation Guide and ADA’s SNODENT terminology work are advancing standards that would make structured dental data exchange possible. SNODENT provides a standardized clinical vocabulary for dental diagnoses and findings, harmonized with broader medical terminology (SNOMED CT) and suitable for structured exchange. (Ada Developers Academy)

These are necessary technical foundations. But alone, they do not guarantee adoption.

3. Workflow Alignment Is Critical

Information must appear where clinicians already work or it will not be reliably used.

Even settings with technical connectivity struggle if clinicians must log into separate portals, or if the data adds cognitive burden without clear context.

In our discussions and broader research, workflow misalignment is cited as one of the top adoption barriers across medical, dental, and behavioral health care. Aligning exchange with clinician workflows — rather than requiring extra steps — is essential for use.

4. Data Quality and Usability Issues Persist

Structured terminology like SNODENT makes consistent encoding possible. But inconsistent use of codes, proprietary data models, and mapping gaps mean that even when dental data exists, it may not be usable for analytics, referral coordination, or clinical decision support without significant normalization.

This is a challenge echoed across other last-mile domains like behavioral health and social care data, where inconsistent data quality undermines trust and use.

5. Privacy, Security, and Capacity Concerns

Smaller dental practices and community clinics frequently lack dedicated privacy/security staff or data governance resources. This can make participation in exchange networks feel resource-intensive.

HIEs are positioned to provide shared services and governance frameworks. But that requires prioritization and investment.

Are Any HIEs Exchanging Dental Data Today?

The simple answer today is not broadly, at scale — but there are early examples.

Colorado’s CORHIO and the Colorado Dental Association launched a pilot program to connect dentists to the state’s HIE, reducing implementation fees to encourage participation. This demonstrates real-world interest by both HIEs and dental stakeholders to test data sharing mechanisms. (VBC Exhibit Hall)

On the standards side, the ADA worked with HL7 at the Connectathon level to demonstrate successful sharing of a full dental record using structured standards. This is a technical milestone pointing toward what interoperability could look like in real exchange environments. (ADA News)

Academic research also confirms that, even where infrastructure exists (such as query access from dental clinics to HIEs), dental clinicians will use it when it is accessible and integrated into workflow — reinforcing that adoption is a usability and design problem as much as a technical one. (PMC)

These are early signals, not yet production-level nationwide exchange of dental clinical data. They do, however, indicate that exchange is technically feasible and is beginning to be operationalized in pilots.

Why This Is a Natural Role for HIEs

Dental data exchange sits right where HIEs already operate.

HIEs support many FQHCs for medical data.

Dental services are embedded in many of those same organizations.

Standards work exists to make structured exchange possible.

Incorporating dental data strengthens whole person care, improves medical-dental referral coordination, enhances population health insights, and supports equity-focused initiatives.

Most importantly, this is classic last-mile interoperability: working with uneven systems, engaging providers with variable technical maturity, aligning data to workflow, and enabling governance that builds trust.

Conclusion

Dental data exchange is not a future concept. It is a present gap hiding in plain sight.

Many FQHCs already provide dental care. HIEs already partner with them for medical data. Early pilots show the potential for dental exchange. CareQuest and standards organizations are championing integration. But adoption remains limited because the work is difficult, contextual, and requires intentional design.

For HIEs dedicated to whole person care, tackling dental data exchange is not optional. It is the type of unglamorous, high-impact interoperability that meaningfully improves outcomes. And yes, it is hard — but that is exactly how you know it matters.