Search results for "FHIR": 3,717 articles
This article covers a wide range of topics regarding the design and implementation of various medical forms within electronic health records (EHR) and clinical workflows based on the FHIR standard. Specific areas discussed include data collection methods tailored to specialized clinical domains such as pre-operative assessments (KOOS/WOMAC), oncology, cardiology, and pediatrics.
The eHealth Infrastructure, based on FHIR standards, has defined a new extension element called 'On behalf of'. This mechanism is designed to add supplementary information to resources and represents a technical specification that enables flexible and detailed information transfer in healthcare data exchange.
Large US healthcare organizations face challenges such as fragmented EHR environments across multiple facilities and difficulty integrating data for value-based care. The article outlines solutions that address these technical and operational issues using FHIR interoperability and HIPAA-compliant platforms.
Based on the challenges of structured reporting in 2026, this article compares and introduces five FHIR terminology servers capable of handling RadLex, a key ontology for radiology imaging workflows. These tools represent practical options that can manage large-scale data loading and complex hierarchical processing.
This study developed and implemented a SMART on FHIR application aimed at enhancing the clinical utility of quality indicators (QI) in residential long-term care. The approach demonstrated the ability to overcome traditional data collection and information sharing challenges.
eHealth Infrastructure in Denmark published the mapping specification for the 'ehealth-task-episodeOfCare' extension, based on FHIR v4.0.1. This is a technical reference designed to enhance the structuring and interoperability of the Episode of Care within medical records.
HealthClawは、FHIR操作Observation/$interpretを導入し、検査結果に標準的なHL7コードを用いた解釈と一般向けの説明を提供。単なるラベル表示ではなく理解促進を重視した設計が特徴である。
This study explored applying Reinforcement Learning (RL) to FHIR workflows, demonstrating the potential of 'World Feedback' for complex clinical decision-making. It identified structural limitations in existing models and proposed that a hybrid approach combining SFT and RL is optimal.
Germany is advancing the construction of a data-driven healthcare system based on the European Health Data Space (EHDS) and EU AI regulations. It aims to standardize and securely share data through the introduction of electronic patient records (ePA) and national data centers.
The National Health Authority (NHA) launched Aarogya Setu 2.0, utilizing Google’s Gemma 4 AI model to standardize and integrate India's fragmented paper-based medical records into a digital Personal Health Record (PHR) based on the FHIR standard.
This article summarizes a discussion on the US healthcare IT ecosystem. It focuses on structural and regulatory challenges, specifically addressing TEFCA's new auditing contract and the potential enforcement of information blocking rules.
SignalEDI introduces PA Bridge to address utilization management (UM) system challenges related to the CMS-0057 mandate. By creating a translation layer between FHIR and X12 278, it enables prior authorization API implementation without requiring changes to existing workflows or systems.
The Danish eHealth Infrastructure has published a technical specification for the 'period' search parameter, based on FHIR. This mechanism allows for searching communication records and other resources using specific time frames.
This content focuses on achieving interoperability of medical data using EHRs and APIs. Various presentations from experts are introduced, demonstrating that FHIR (Fast Healthcare Interoperability Resources) is crucial as a standard data exchange format in modern healthcare IT.
Medplumは、FHIR R4を開発者向けのバックエンドとして扱い、リソースタイプに基づいたRESTful APIを提供している。本記事では、単なるAPIの羅列ではなく、患者登録や観察記録の最終化といった意味のあるワークフローを「Arazzo」という形で定義し、その実装方法を解説した。
The author details a method for synthetically creating paired datasets of clinical notes and structured healthcare data in the FHIR format. This approach allows for the construction of necessary training data for fine-tuning small, private language models without relying on sensitive real patient records.
Modern healthcare AI is evolving beyond relying solely on Large Language Models (LLMs). By combining technologies like FHIR, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG), it enables accurate and explainable medical reasoning based on real-time clinical data.
CENS in Chile offers a comprehensive educational pathway to enable data sharing and continuous care within healthcare systems. This roadmap is designed for progressive learning, progressing from fundamental health information systems knowledge up to the practical application of international standards like HL7 FHIR®.
As AI adoption accelerates in healthcare, technology leader Vallikranth Ayyagari warns that the failure of many AI deployments stems not from the model itself, but from fundamental 'data plumbing.' Successful pilot programs often fail in real-world operation due to underlying data architecture issues.
HeartSciences, an AI-driven healthcare IT company specializing in electrocardiogram (ECG/EKG) technology, announced that its platform, MyoVista Insights™, has received certification from the Epic Toolbox for the ECG management system category. This enhances system integration within clinical workflows.