Evolution of Healthcare Interoperability
📌 Healthcare interoperability efforts began in the 1980s with HL7 Version 2, initially focused on connecting systems *within* a single hospital.
🏥 Today, interoperability means viewing all data for an individual or population in one place, in real-time, similar to how the general internet functions.
📈 The complexity of decisions has grown exponentially; the number of relevant facts per decision increased from about 10 in 1980 to 1000 in 2020.

Introduction to FHIR (Fast Healthcare Interoperability Resources)
💻 FHIR is fundamentally a Representational State Transfer (REST) API standard, the same technology underpinning services like Google and Twitter.
✈️ FHIR operates like a travel website: airlines agree on how to represent flight data (the resource/API) so any travel site can query it without downloading all schedules.
💡 The core challenge FHIR solves is making healthcare facts computable and machine-readable so humans are no longer hopelessly behind on data processing capacity.

Core FHIR Concepts
🔗 FHIR Resources are defined data elements (e.g., Patient, Medication) with a known location and defined meaning based on the FHIR specification (the data model).
⚙️ FHIR Profiles are crucial for interoperability; they are customizations of base resources for a specific use case, defining vocabulary, extensions, and rules, ensuring systems mean the same thing when exchanging data.
📄 Interoperability via FHIR is achieved by systems using the same FHIR Profile, allowing data exchange across messaging, FHIR Documents, or decision support without transformation.

FHIR Customization and Implementation
🧩 FHIR Extensions allow adding data elements not present in the base specification (which covers data found in only 80% of systems) by publishing the extension definition to a public URL for discovery.
📚 FHIR Terminology Servers store and manipulate value sets and code systems, allowing different implementations to reference the same shared terminology, enhancing consistency.
🛠️ The FHIR Implementation Guide bundles all necessary components for a specific use case—including profiles, value sets, and extensions—and is published with both human-readable descriptions and machine-readable content for validation.

Key Points & Insights
➡️ FHIR represents a major data innovation because its entire specification, profiles, and guides are machine-readable and downloadable, unlike previous document-based standards.
➡️ Interoperability success hinges on agreeing on FHIR Profiles; systems must use the same profile to ensure they "mean the same thing" in a machine-readable context.
➡️ While creating plug-and-play apps across all systems is challenging due to EHR customizations, FHIR greatly eases application creation and local innovation within an environment.
➡️ Extensions are deliberately used for data elements not present in 80% of systems to keep the base FHIR specification less complex and easier to implement initially.

📸 Video summarized with SummaryTube.com on Oct 09, 2025, 17:17 UTC