Search results for "FHIR": 1,661 articles
A research paper reports the successful implementation of automated video-based AVPU (consciousness level) assessment within a FHIR-enabled clinical decision support framework. This aims to improve and standardize the traditionally manual process of assessing consciousness levels, enabling more objective data collection.
This documentation explains the behavior of logical operators, 'AND' and 'OR', based on legacy documentation for a FHIR converter called FUME. These operators determine if both operands are true (AND), or if at least one operand is true (OR), after casting the data to Boolean type.
This study proposes a method to integrate diverse data from wearable devices, such as those from Garmin, into Electronic Health Record Systems (EHDS) using FHIR. The case study focuses on the technical feasibility and scalability of data linkage for applications like chronic disease management and clinical decision support.
本記事は、FUMEというツールにおけるデータマッピングの流れを詳細に解説している。特に、変数バインディングや括弧を用いたオーケストレーションブロックを活用することで、複雑な値の結合、計算、そして最終的なFHIRリソースへの構造化出力が可能となることを説明している。
MIRAという自律型AIエージェントは、仮想的な電子カルテ（EHR）環境内で臨床推論を行い、診断精度において経験豊富な医師を上回る結果を出した。これは、LLMが持つ知識を実際の医療現場のワークフローに落とし込む難しさを克服する可能性を示唆している。
The Danish eHealth Infrastructure has released the code system
欧州連合（EU）はGDPRを基盤に「データ不出本地」の联邦式データ空間を構築。一方、米国ではHIPAA準拠のもとTEFCAが医療情報ネットワークを推進し、金融分野ではFDX APIなどが標準化が進んでいる。これらの事例は、データの主権維持と安全な流通を実現する国際的な潮流を示す。
This study systematically reviewed scientific literature on the development process of FHIR Implementation Guides (IGs) in electronic health records. It proposes that IG creation is not merely a technical task but a complex process requiring the integration of software engineering, clinical semantics, and organizational governance through a
Firely, in collaboration with HL7, released a report indicating that global surveys show growing adoption of FHIR, expanding regulatory momentum, and an emerging 'AI paradox.'
本論文は、Fast Healthcare Interoperability Resources (FHIR) の実装ガイド（IGs）の作成プロセスについて包括的なレビューを実施した。研究結果から、FHIR IGsがどのように開発され、どのような標準やツールを用いて管理されているかが明らかになった。
HL7 Europe published a logical model for Radiotherapy. This model structures detailed information—including treatment duration and anatomical target—based on the FHIR standard, aiming to enhance interoperability of medical records.
eHealth Infrastructure has released an OperationDefinition (`Get Report Job Status`) to check the status of reports scheduled or executed by a user. This feature allows systems to centrally manage details such as report class, execution status, and references to binary data.
This service provides an end-to-end platform for pharmaceutical companies to author, validate, and distribute electronic package inserts (ePIL). By utilizing AI, it automates the conversion of existing paper media or PDFs into structured, FHIR R4 compliant data, significantly reducing manual effort.
This operation definition provides the technical means to invalidate or retract an invalidation status for a Measurement. It utilizes the ClinicalImpression resource to manage and track the validity status of measurements.
At HL7 FHIR DevDays 2026, participants focused on building solutions and solving real industry challenges. Key highlights included the progress of data analytics layers using SQL on FHIR and the development of tools for CQL (Clinical Quality Language).
Varist announced a detection engine supporting DICOM, HL7, and FHIR flows to combat malware. This system analyzes complex medical image metadata and legacy protocols in real time, significantly strengthening PACS protection.
Cybersecurity company Varist launched a 'DICOM Detection Engine' for medical imaging and Electronic Health Record (EHR) infrastructure. The product is designed to detect malware hidden within medical image files, which conventional scanners often miss.
SMART on FHIRは、FHIRを基盤とし、アプリケーションが電子カルテ（EHR）内で安全に起動するためのプラットフォーム層である。OAuth2やOpenID Connectに基づく認証プロファイル、および現在の患者情報からアプリアクセスを開始できるコンテキストを提供し、サードパーティ機能の組み込みを可能にする。
A healthcare client sought to manage FHIR data within their existing data lakehouse (Databricks). The article proposes an architecture using the Lakehouse//RT engine, demonstrating its high processing capability without needing a dedicated server.
Desha.aiは、GDPRやHIPAAなどの国際的な規制に準拠しつつ、HL7 FHIR R4という最新の相互運用性標準を採用することで、安全かつポータブルな医療データ交換環境を提供している。