AI Transforms Digital Health: From Data Recording to Continuous Care
Inteligencia artificial: la evolución pendiente de la salud digital Diario
Summary
This article discusses the evolution of digital health in Latin American healthcare systems. The focus has moved beyond simple electronic medical records (EMR) implementation, highlighting that information integration and knowledge creation are now key challenges. While AI offers great potential, issues like data quality and privacy protection must also be addressed.
Details
This article analyzes the current state and future direction of digital healthcare in Latin America. Initially, the primary goal was digitalization—moving from paper records to electronic ones (basic digitization). However, the focus has shifted to achieving 'information flow' and 'transformation into useful knowledge,' going beyond mere record-keeping. A major challenge identified is that many existing medical platforms were designed for isolated clinical episodes, failing to support modern continuous care models. To bridge this gap, efforts are advancing toward improving interoperability between institutions using standards like HL7 and FHIR. The next wave of transformation highlighted is the application of AI. AI is being applied in areas such as automatic clinical documentation generation and predictive models for clinical deterioration. However, maximizing its effectiveness requires ensuring data quality and responsible implementation concerning privacy and security. In conclusion, the progress of healthcare IT in Latin America hinges not merely on adopting AI, but on implementing it 'patient-centered,' 'interoperably,' and 'responsibly.'
Technology Note
FHIR（Fast Healthcare Interoperability Resources）は医療データ交換の国際標準。このエントリの関連技術: FHIR
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