Beyond buzzwords: Why semantic interoperability is the holy grail of digital health

Entrepreneurs entering the healthcare space often identify inefficiencies and start companies to solve them. Whether optimizing care transitions, streamlining billing or empowering home health teams, most health tech startups inevitably deal with digital health information. But solving these problems doesn’t just mean building a great product, it also means ensuring your solution speaks the same language as the rest of the healthcare continuum.

Healthcare data exchange involves multiple formats and standards such as HL7, FHIR, X12, NCPDP, etc., which are used by different organizations for various purposes. This complexity can make the critical task of sharing health data cumbersome and unwieldy. This is where interoperability comes into play. Although it has become a buzzword, true interoperability is a prerequisite for patient-centric, efficient, and scalable digital health solutions. Among the different types of interoperability, semantic interoperability is a goal that many people strive to achieve.

Understand the various levels of interoperability

It's easy to think of interoperability as a technical issue. But it's really a question of trust and translation – making sure the data has the same meaning wherever it goes. Interoperability in healthcare can be divided into three key levels: foundational, structural and security.Mantic.

1. Basic interoperability: getting data from point A to point B

This is the most basic level – think of it like mailing a letter in any language. The infrastructure exists to pass information from one system to another, but there is no guarantee that the recipient will be able to interpret it.

This is where ubiquitous tools like fax machines come into play. DIRECT messaging also typically operates at a base level, although it can carry structured data when used with CDA or other rich add-ons. While basic interoperability ensures that data can be shared, it does little to ensure availability. The system may receive messages, but someone usually has to manually interpret the information and enter it into the appropriate fields. These manual processes can lead to inaccuracies and inefficiencies, placing additional administrative burden on an already overloaded healthcare system.

Basic interoperability may check the “data exchange” box, but it contributes little to the automation, analytics, or timely clinical decision-making required in today's healthcare ecosystem.

2. Structural interoperability: standardized format, non-standardized meaning

Structural interoperability takes a step forward by using standard formats to organize data. This is similar to everyone agreeing to speak English but having different regional dialects and expressions. You can understand the structure of what is being said, but not always the intent.

In healthcare, standards such as HL7 v2, CDA, and CCD establish a common structure for how information such as patient demographics or discharge summaries are organized and exchanged. These formats simplify data parsing and transmission but do not guarantee a common understanding of the data's meaning. One system might record “myocardial infarction,” another might call it “heart attack,” and a third might use a proprietary internal code. This lack of semantic consistency creates errors, duplication, and extra layers of translation. Although CDA and CCD are primarily structural standards, they can incorporate coding vocabularies, bringing implementations closer to true semantic interoperability when used effectively.

Custom integrations, data mapping, and middleware are often used to bridge these gaps, resulting in a process that is costly and time-consuming and does not scale well.

3. Semantic interoperability: speaking the same language and having a common meaning

Semantic interoperability goes one step further – not only does the data arrive in a structured format, but both sender and receiver use the same codes and terminology to define the data. To make this level of understanding possible, both the public and private sectors are actively promoting initiatives to develop and adopt standardized data exchange protocols. These efforts are critical to ensuring that healthcare data can not only be exchanged, but can be interpreted consistently and used meaningfully across disparate systems and organizations. Examples include SNOMED for diagnostics, LOINC for lab results, and RxNorm for drugs—all referenced through APIs such as FHIR.

This level of interoperability enables machines to read, interpret and act on data with minimal human input. Standardized diagnosis codes for ICD-10 I21.9 (acute myocardial infarction) can be instantly integrated into patient records, trigger clinical decision support tools, or automatically inform discharge planning.

This is why semantic interoperability is the gold standard: it enables automation, increases accuracy, and reduces friction between systems. It enables features like real-time medication reconciliation, predictive analytics, and patient-facing applications that truly understand your medical history.

Why this matters for your health tech company

If your platform interacts with patient data—whether clinical, financial, or operational data—your long-term viability depends on how integrated you are with the healthcare ecosystem. Solutions that rely solely on foundational or structural interoperability are often brittle, require custom workarounds, and limit scalability.

Striving for semantic interoperability is more than just compliance—it's a strategic differentiator. It allows your solution to:

• Eliminate redundant documentation.
• Increase provider satisfaction by reducing manual workflows.
• Enable richer analytics and insights.
• Provide real-time care coordination and decision support.

Recent federal initiatives, such as ONC's USCDI v4, TEFCA, and CMS' interoperability and prior authorization rules, are accelerating the industry's move toward standardized, machine-readable health data. Alignment with these frameworks not only supports compliance but also ensures long-term relevance as payers and providers adopt semantically consistent data exchange models.

takeout

Interoperability is not just a technical requirement; This is a business imperative. Foundational and structural interoperability may help you with early integration, but to unlock scale, automation, and true clinical impact, semantic interoperability should guide your long-term architecture.

Photo: DrAfter123, Getty Images

This article appeared in Medical City Influencers program. Anyone can share their thoughts on healthcare business and innovation on MedCity News through MedCity Influencers. Click here to learn how.