Healthcare Data for the AI Era: Interoperability through FHIR and SNOMED
AI? Eerst FHIR, SNOMED, kwaliteit en vooringenomenheid bespreken - ICT&health
Summary
A digital health expert stresses that solving data interoperability is prerequisite to widespread AI adoption in healthcare. The core challenge lies in the fragmentation of structured clinical text data, making international standards like FHIR and SNOMED CT essential.
Details
This article features a discussion with a digital health expert regarding the critical importance of interoperability for implementing AI in healthcare. Currently, medical data is siloed within individual institutions, presenting significant fragmentation challenges—especially concerning structured clinical data (diagnoses, procedures, etc.). The expert highlighted that FHIR offers necessary flexibility while allowing data structuring, and SNOMED CT provides over 360,000 detailed medical concepts crucial for AI research and personalized care. Furthermore, the article suggests that implementing these international standards requires tangible incentives, such as financial drivers. The discussion also emphasized structural improvements needed to foster innovation: strengthening links between academic research and clinical practice, and building collaborative frameworks with industry. These insights provide a multi-faceted view of developing medical information systems for real-world application.
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