Search results for "LOINC": 168 articles
The article addresses critical issues in healthcare platform development, such as duplicate patient records and data inconsistencies across modules. It advocates that the FHIR 'Patient' resource must be treated not merely as metadata, but as the central, unifying identifier for all clinical encounters.
JijiHub has released an AI skill designed to assist in creating FHIR-compliant questionnaire definitions. This tool can structure medical information, such as conditions and medications, by utilizing official coding APIs like LOINC and SNOMED CT from plain requirement documents.
The pharmaceutical industry is advancing data integration using AI to cope with increasingly complex clinical trials. This significantly streamlines the previously challenging process of data harmonization, accelerating time-to-insight.
The 'FHIR Developer Skill' from anthropics is a comprehensive reference guide for accurately building FHIR R4 REST APIs. It enhances development efficiency by clearly separating required and optional fields, and providing proper mapping of HTTP status codes (e.g., 422, 412).
Service Points offers a comprehensive revenue cycle management solution combining HIPAA-compliant X12 transaction sets (837/835, etc.) with FHIR APIs. This automates everything from eligibility checking to payment processing, achieving faster billing cycles and improved claim accuracy.
The FHIR Observation resource is the primary structure for recording all types of measurements and assessment results related to a patient. This allows quantifiable clinical findings—such as lab results, vital signs, and lifestyle data—to be handled uniformly, forming a foundation for health information exchange.
本ガイドは、FHIRネイティブな問診票リマインダーや患者サーベイランスワークフローをFire Arrow Serverを用いて構築する方法を解説している。定期的な症状モニタリングが必要な慢性疾患プログラムなどにおいて、標準化された質問票（例：PHQ-9）のスケジューリングとデータ収集を一元管理できる。
Health Samurai and Databricks provide a unified foundation by standardizing diverse clinical data (e.g., HL7v2, C-CDA) into FHIR. This enables access to trusted data for all tools, including AI/ML, without requiring complex ETL processes, accelerating digital transformation in healthcare.
This article compares the technical differences between Australian (AU) and US FHIR implementations. While both use FHIR R4 as the base standard, significant variations exist at the Implementation Guide (IG) layer and in required data elements, indicating that simple configuration changes are insufficient.
The open-source JetBrains plugin, "FHIR Toolkit," significantly improves the FHIR R4 development workflow. It aims to eliminate the manual effort of validation and reference resolution that typically occurs when editing JSON in separate tools, allowing all processes to be completed within the IDE.
This material reviews the international trends of major health information standards like HL7 FHIR and SNOMED CT. It focuses particularly on the 'International Patient Summary (IPS),' highlighting that a standardized framework for sharing basic clinical data is crucial for cross-border care and disaster response.
West Coast Informatics (WCI) unveiled a managed FHIR terminology service, TermHub. This aims to fundamentally change how critical healthcare data is distributed by alleviating the technical burden faced by Standards Development Organizations (SDOs), such as those managing SNOMED CT and LOINC.
UNMIRI has released a free online validator to check the conformance of FHIR Genomics R4 Bundles. This tool aims to provide rapid diagnostic reports, particularly useful in development environments for Quality Assurance (QA) and Continuous Integration (CI) pipelines.
This page introduces an interface for searching and managing complex medical code systems based on multiple standards, including UMLS (Unified Medical Language System) and FHIR (Fast Healthcare Interoperability Resources). Users can cross-reference various coding schemes (such as LOINC, CDT, HCPCS) to view detailed definitions and remapping information.
ardle.orgは、FHIRのコードシステムやバリューセットなどの用語データを共有するための新しいオープン仕様「FTRM」（FHIR Terminology Container）を発表した。これは単一のSQLiteデータベースファイルとして、移植性と利用可能性を確保する。
A terminology server is a dedicated FHIR service that hosts code systems and value sets, exposing standardized APIs. This allows applications to resolve, validate, and look up clinical terminology at runtime.
This article details an architecture for utilizing Azure Health Data Services to convert and integrate data from legacy HL7v2 systems and various sources into FHIR R4. This enables complex medical data exchange and analysis.
This article details practical mapping techniques for translating legacy healthcare data into FHIR resources. It emphasizes that successful data model design requires structural, semantic, and operational considerations beyond simple field-to-field transformation.
This document details the technical specifications for exchanging 'clinical notes,' which are crucial for communicating a patient's current status. It defines how eight common clinical note types and three diagnostic report categories must be handled based on the HL7 FHIR standard.
This article explains how clinical laboratory results should be handled as digital reports using FHIR. By utilizing the DiagnosticReport resource, it standardizes comprehensive information—including not just numerical values but also text, images, and codes.