AI and Interoperability: The Technical Foundation Driving Healthcare Transformation

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AI has moved beyond being a futuristic concept and is already implemented in hospitals and clinics globally. In Brazil, the adoption of AI is considered urgent due to structural challenges such as rising morbidity rates and data fragmentation. The core technical foundation for this advancement is interoperability, specifically enabled by standards like HL7 FHIR. Since any machine learning model requires integrated, clean, and structured data, investment in a robust 'data infrastructure' is crucial. This allows AI applications to move beyond simple diagnosis support to enabling predictive public health risk modeling across entire regions and facilitating highly individualized precision medicine. Future developments include using generative AI to reduce the documentation burden on healthcare professionals and combining telemedicine with intelligent triage to provide equitable care. These advancements are positioning interoperability not merely as an 'innovation,' but as an 'operational necessity' within the healthcare IT industry.