Search results for "SNOMED": 314 articles
The National Association of Private Hospitals (OSSP) proposed to the Ministry of Health the establishment of a social council dedicated to healthcare digitalization. This initiative aims to organize and guide the chaotic digitalization process by involving independent experts from the private sector.
本記事は、大規模言語モデル（LLM）を組み込んだシステムを用いて、非構造化データやFHIRの用語集を利用しながら臨床意思決定支援（CDS）クエリを実行する方法を紹介している。これにより、従来のCQLが苦手としていた領域での高度なデータ分析が可能となる。
Darren Devitt published a tutorial detailing 19 advanced search queries for FHIR servers, based on his DevDays presentation. These examples demonstrate complex data retrieval methods—such as filtering by specific conditions, timeframes, or related resources—providing valuable references for practical API development.
The Mobile Antepartum Summary (mAPS) has defined the critical clinical information, 'Prior Menses Date,' conforming to the FHIR standard. This enables data exchange in a unified format across healthcare institutions, contributing to improved continuous patient care.
The article argues that the true limitation of clinical AI is not the algorithm itself, but access to real-time clinical context. It introduces the Model Context Protocol (MCP), a new infrastructure designed to enable secure and transparent data exchange.
This page displays the definition of a SNOMED CT Value Set that aggregates various procedures related to hemodialysis, including those relevant during COVID-19. It contains codes covering multiple types of dialysis and maintenance care, serving as a resource for standardizing medical information.
This page aggregates and tracks the latest FHIR MCP (Master Client Provider) server information from various internet sources, showcasing highly popular resources used within the community. The services offered range widely, including reference data containing drugs and diagnoses, access to EMR systems, and integration tools with HL7/DICOM.
Model Context Protocol (MCP) は、機密性の高いFHIRデータを安全に利用しつつ、大規模言語モデル（LLM）による生成AIの活用を可能にする新しい標準プロトコルである。これは、AIが臨床情報を文脈的に取得するためのセキュアな仲介役となる。
本ポッドキャストでは、電子健康記録のデータ交換に関する様々なトピックを扱っている。特に、新しい通信標準であるFHIR（Fast Healthcare Interoperability Resources）について詳しく議論し、また、IHE（Integrating the Healthcare Enterprise）が定義するユースケースや役割についても解説している。
The Australian Digital Health Agency has published a concrete example of the 'RelatedPerson' resource using FHIR format. This case demonstrates how patient information and relationships (such as stepmother) can be represented in a standardized manner.
The Australian Digital Health Agency has published an 'FHIR Implementation Guide' based on FHIR version 4.0.1. This guide demonstrates the structure and use of medical data, such as immunization records, across various formats (JSON, XML, etc.).
本記事は、FHIR Terminology ServiceやSNOMED CT Terminology Servicesなど、医療情報における標準的な用語集サービスの具体的な利用方法について複数の動画コンテンツを提供している。データ構造化や相互運用性の向上に役立つ技術的知見がまとめられている。
A 'Menopause value set' has been defined to code physiological states across different life stages. This set references standard terminologies like SNOMED CT, providing a group of concept IDs corresponding to multiple phases (pre-menopause, during menopause, post-menopause).
In developing FHIR-based applications, the terminology layer is highlighted as playing an extremely critical role. Since major code systems like SNOMED CT and LOINC are used, performance and reliability are crucial to system success, requiring consideration during the design phase.
Mr. Rath Panyowat published video content explaining how to use HL7 FHIR Terminology Services. The article discusses the utilization of terminology services, such as SNOMED CT, for interoperability using FHIR.
The healthcare sector faces challenges in optimizing efficiency and reducing administrative burden. While data plays a key role in solving these issues, the diversity of its formats and sources makes interoperability essential.
Dr. Carina Vorisek, a digital health innovation leader, highlights 'data interoperability' as the primary obstacle to AI adoption in healthcare. She notes that LLMs struggle to structure unstructured text into standardized medical terminology, emphasizing that solving data standards and interoperability is crucial for practical AI deployment.
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.
No specific organization or initiative was stated; the content was a general discussion about the foundational role of FHIR and SNOMED in AI.
本記事は、電子カルテシステム間の情報共有を可能にするための主要な相互運用性（インターオペラビリティ）標準規格について解説している。特に、HL7やFHIRといった技術的な枠組みと、SNOMED CTやLOINCのような共通語彙の重要性を説明し、医療システムの連携がなぜ不可欠かを論じている。