Interoperability in Healthcare: More Than Just Data Exchange

How To Architect Integrative IT Systems that Think and Reason, Before They Suggest 

In healthcare IT, we often talk about interoperability as though it's synonymous with data exchange—passing a payload from one system to another using a standard API. While that’s certainly a part of the picture, it’s far from the whole story.

This narrow view is common—and understandable. Much of the regulatory and industry focus to date has emphasized basic data exchange as the foundation for interoperability. But to build healthcare systems that actually work together to improve care, reduce burden, and scale innovation, we need to move beyond just data.

True interoperability has multiple layers. Understanding these dimensions—and the maturity levels within them—is key to solving the right problems early and designing systems that support a modern, learning health system.

While each dimension of interoperability seems like its own layer, they are interconnected.

Dimensions of Interoperability

Data Interoperability

Most healthcare organizations are familiar with data interoperability through the FHIR^® standard. It has increasingly been adopted across the globe and is mandated by many regulatory bodies as the standard for healthcare data exchange.

Data interoperability is essential, but it is just a foundation; an enabler that knowledge and process interoperability is built upon.

Knowledge Interoperability

Knowledge interoperability goes beyond data to address how decisions are made in healthcare.
It’s the ability to represent clinical knowledge—rules, logic, algorithms—in a standardized, shareable format that’s external to the system implementing it. Rather than hardcoding clinical rules into software, knowledge interoperability supports the reuse and exchange of logic across systems and organizations.

Knowledge Interoperability includes two components:

1. Syntactic interoperability: where data follows a consistent format or model, like a FHIR resource, enabling reliable and meaningful computation
2. Semantic interoperability: where clinical interpretation of data is based on shared terminologies and ontologies (like SNOMED CT, LOINC etc.). 

This is where standards like Clinical Quality Language (CQL) along with FHIR create a powerful engine that enables the meaningful sharing of clinical logic. CQL is used to express clinical logic in a computable, human-readable format that can be shared, tested, and reused across different platforms. This democratizes clinical reasoning and makes it possible to maintain consistency in decision support across a fragmented healthcare system.

Knowledge interoperability supports workflows like CRD (Coverage Requirements Discovery) and DTR (Documentation, Templates and Rules) where knowledge that maintains clinical context is exchanged back and forth between payers and providers. 

Process Interoperability

Process interoperability enables systems to understand and coordinate how care is delivered—not just what the data says or what the logic recommends. Robust process interoperability allows business workflows to define sequences of events, decisions, triggers, inputs, and outputs in a computable format.

Workflows like prior authorization, or expressing CPGs (Clinical Practice Guidelines) for clinical decision support or running quality measures can be standardized and executed to improve care coordination. 
Many healthcare organizations have made significant strides in data interoperability, but have yet to meaningfully engage with knowledge or process layers. That leads to systems that can exchange information, but not act on it intelligently or consistently.

Blog Take Aways

Understanding these distinct dimensions is crucial to identifying which gaps need to be addressed next and for directing modernization efforts to support value-based care effectively and cost-efficiently. Smile Digital Health believes that to truly transform healthcare, we should advance not just our ability to move data, but our ability to share logic, coordinate processes, and build systems that support our ability to reason and act proactively.

Understanding these distinct dimensions is crucial to identifying which gaps need to be addressed next and for directing modernization efforts to support value-based care effectively and cost-efficiently. To recap:

• Data interoperability is essential, but it is just a foundation; an enabler that knowledge and process interoperability is built upon.
• Knowledge interoperability is how clinical knowledge is exchanged back and forth between payers and providers. It supports workflows like CRD and DTR.
• Process interoperability enables systems to understand and coordinate how care is delivered. It supports workflows like PriorAuth, CDS and quality measures.