Search results for "SNOMED": 314 articles
HeyDonto AI Technology announced the close of a seed funding round at a $200 million valuation, aiming to accelerate the deployment of 'Conduit,' a standards-based interoperability platform connecting dental systems to the broader healthcare ecosystem. The platform aims to bridge the structural gap of integrating dental data into the national health information infrastructure.
The HIMSS 2026 event highlighted that while Artificial Intelligence (AI) remains a central focus, the discussion has shifted beyond mere technological disruption toward operational efficiency and patient-centered care.
An expert in healthcare APIs points out that while FHIR is the standard, significant inconsistencies exist in implementation and data quality. The article warns that even for the same patient data, information varies depending on the API pathway, making mere 'compliance' insufficient.
Successful FHIR implementation requires a combination of healthcare domain knowledge, interoperability engineering, and system-level architecture expertise. It is not merely an interface development task but aims to build a governed interoperability layer supporting clinical workflows and regulatory compliance.
The article addresses complex data integration challenges in healthcare, advocating a 'contracts-first' approach. It aims to reduce operational risk and build reliable pipelines by implementing data quality assurance (DQ) and schema evolution management.
This article details how to build advanced, compliant medical AI applications by integrating the Fast Healthcare Interoperability Resources (FHIR) standard with the large language model MedGemma. It provides specific code examples and data formatting procedures for structuring patient information, medical history, and lab results into usable prompts.
A team of Taiwanese medical research institutions has developed and released a template using the international FHIR format for recording and exchanging antibiotic resistance data. This system aims to standardize clinical data and facilitate long-term trend analysis.
This article introduces Kodjin, an analytics platform designed for the healthcare industry undergoing a profound data revolution. Built on HL7 FHIR standards, it integrates diverse medical data to provide actionable clinical and operational insights.
クラウドヘルスオフィスは、メディケアアドバンテージなどの支払者プラットフォーム向けに、標準化されたFHIR R4 APIとCMS-0057-Fへの準拠を提供する。これにより、事前承認やデータアクセスが改善され、2027年1月1日までに義務付けられる規制に対応する。
AI tools can automate repetitive mapping tasks and detect errors in complex HL7/FHIR integration projects, significantly reducing development time. However, the article stresses that human expertise remains essential for clinical judgment and system-level design.
While data exchange has advanced, true healthcare system interoperability requires consistently interpreting the 'meaning' of data. FHIR plays a crucial role not only by enabling structured data exchange but also by facilitating semantic interoperability through standardized coding and terminology.
Researchers proposed 'Infherno,' an end-to-end, agent-based framework for synthesizing FHIR resources from unstructured clinical notes. This system aims to enhance generalizability and accuracy in clinical data integration by utilizing LLMs and external tools.
This study aimed to establish methodologies for effective healthcare data utilization, addressing technical and systemic challenges associated with FHIR adoption. By referencing USCDI, the research proposed multi-faceted approaches, including resolving discrepancies between diagnostic and insurance diagnoses, and integrating standards (Standard) with AI.
Healthcare institutions can eliminate data silos and improve clinical visibility by connecting medical devices with EHRs and analytics platforms. This integration, utilizing standards like HL7 and FHIR, prevents manual entry errors and forms the foundation for AI-driven predictive healthcare systems.
Led by the IDB and PAHO, and supported by Japan, the Pan-American Digital Health Route (PH4H) is an initiative aiming to build interoperable infrastructure for secure clinical data sharing across Latin American and Caribbean countries.
Shen AI is a measurement technology that captures physiological signals from a camera and outputs structured vital signs like heart rate and blood pressure. This SDK provides stable JSON output, enabling integration into existing systems without managing data persistence or clinical workflow orchestration, thus simplifying FHIR mapping.
Researchers proposed 'BlockIoT,' a unified framework designed to securely integrate decentralized health data from IoT devices into FHIR-compliant electronic health records. The system leverages semantic web and blockchain technology to build a reliable bridge between real-time personal data and clinical systems.
New York State is advancing interoperability efforts for behavioral health records.
This page introduces the search and management functionality for code systems, combining large medical knowledge bases like UMLS (Unified Medical Language System) with standards such as FHIR (Fast Healthcare Interoperability Resources). Users can systematically reference various types of codes and terms to acquire necessary information for building Value Sets.
Researchers emphasize that systematic data modeling is crucial for efficient, future-proof healthcare information sharing. They recommend that while HL7 FHIR excels in data exchange and interoperability, the appropriate standard must be chosen based on specific goals, such as analysis or organizational structure.