1,676 FHIR-related articles (latest first)
This page is a reference defining the FHIR ValueSet for 'Transmission of Visit Record' in electronic healthcare information exchange. This ValueSet structures a dataset that includes specific procedure codes, facilitating interoperability between medical institutions.
No specific organization or initiative was identified in the snippet.
Computable Publishing LLC has published a clinical variable definition,
Google announced that its next operating system, Android 16, will enhance the Health Care service. This update is expected to store users' electronic medical records in FHIR format, improving data exchange efficiency and healthcare information management.
EHR systems are transforming modern healthcare by improving clinical workflows and redefining patient care quality. By adopting interoperability standards like FHIR, data exchange is streamlined, leading to enhanced diagnostic accuracy and efficiency through remote monitoring.
本ページは、レジオネラ属菌の検出に関する複数の臨床検査項目をまとめたFHIR ValueSetの定義を示す。具体的には、喀痰や尿など様々な検体タイプにおける培養・同定法による陽性反応を含む9つのLOINCコードが網羅されている。
Michael Lawley from the Australian e-Health Research Centre (AEHRC) attended a Digital Health Interoperability Bootcamp held in Manila, Philippines. The event gathered diverse participants with a common goal: improving how health data is stored and exchanged. A key focus was placed on implementing FHIR terminology.
A joint project between universities aims to enhance healthcare security and utilize AI-driven data analysis techniques using the HL7 FHIR standard. The focus includes identifying vulnerabilities in FHIR servers, improving treatment pathways via process mining, and performing automatic mapping to codes like SNOMED-CT.
Microsoft Azure's FHIR servers are forgiving regarding non-conforming data because resource creation and update validation is off by default. However, some validation still occurs for specific elements, and enabling profile validation requires explicit header settings, necessitating caution about potential operational surprises.
Smile Digital Health, a provider of FHIR-based solutions, secured a $15 million credit financing agreement with FirePower Capital. This funding will enable the company to accelerate the development and expansion of its market-leading health data platform and innovative solutions for the healthcare sector.
Because HL7 FHIR is structured using nodes and edges, it is highly compatible with graph databases. This enables advanced analysis of complex medical data relationships (e.g., disease traceability, fraud detection) that were difficult to achieve with traditional relational databases.
MedTech company Posos, specializing in medical data structuring, and vendor InterSystems announced a partnership. This collaboration aims to improve the accuracy and safety of drug prescriptions using AI, facilitating integration into hospital software.
This article introduces how to utilize the 'Examples' tab found on FHIR resource documentation pages. This feature provides sample resources, including complete test data for various use cases (e.g., Encounter, Observation), available in raw JSON format.
Medtech expert Posos and data technology provider InterSystems announced a technological partnership. This collaboration aims to enhance the performance of Posos' AI-assisted medical prescription solutions in France and internationally.
DrapCode enables the construction of healthcare applications and functional data exchange using HL7 FHIR standard data stored on Google Cloud, without requiring backend development. This facilitates real-time information sharing of patient records and lab results between hospitals and clinics.
Computable Publishing LLC has published data on 'Participants Excluded from PARACHUTE Study' using the FEvIR platform. This resource is linked to the original 'PARACHUTE trial participant flow report,' providing specific details and counts regarding exclusion reasons and numbers for study participants overall.
優れたFHIR開発者は、SDKに頼るだけでなく、生のFHIRデータ構造を深く理解している。この知識は、予期せぬ拡張や複雑なリソース間の関連性など、実務で遭遇する問題の解決に不可欠である。
By combining HAPI FHIR, an open-source HL7 FHIR server, with the no-code platform DrapCode, healthcare organizations can build applications capable of standardized data exchange without writing backend code. This enables the secure and real-time sharing of patient records and clinical data.
This article explains how companies can utilize DrapCode to integrate Microsoft FHIR APIs, enabling real-time healthcare data exchange and workflow streamlining. It facilitates the construction of secure systems compliant with FHIR standards.
AI startup Affineon Health announced it raised $5 million in a funding round. The company aims to simplify provider workflows and reduce administrative burdens by offering an AI-powered inbox, using the funds for product development and market expansion.