Introduction to a FHIR-Based Hepatitis C Prediction Application
This article introduces the 'Fhir HepatitisC Predict' application from InterSystems. The application predicts Hepatitis C based on input laboratory test results provided by the user.
1,676 FHIR-related articles (latest first)
This article introduces the 'Fhir HepatitisC Predict' application from InterSystems. The application predicts Hepatitis C based on input laboratory test results provided by the user.
HL7 Europe and Xt-EHR are collaborating on developing FHIR Implementation Guides (IGs) to support the European Health Data Space (EHDS). The discussion focuses specifically on technical progress in areas like electronic prescriptions and dispensations.
Healthcare organizations face pressure to share clinical data across disparate systems. This article explains how building a 'Central Interoperability Hub' by integrating multiple standards—including HL7 v2, FHIR, and CCD—can resolve data silos and improve decision-making.
This paper proposes 'Infherno,' an end-to-end framework that utilizes LLM agents and external tools to synthesize FHIR resources from unstructured clinical text. This approach addresses the limitations of conventional systems regarding generalizability and structural conformity.
Nuncius is a communication platform designed to balance security and interoperability in clinical settings. By adhering to the FHIR standard and providing AI analysis and advanced encryption, it aims to improve healthcare workflows while protecting patient data for clinicians.
The 'SNOMED on FHIR Working Session,' chaired by Peter G. Williams and Robert Hausam, is scheduled for October 19, 2025. This session aims to facilitate information exchange regarding the utilization of SNOMED CT within the FHIR standard.
Darren Devitt has released podcasts discussing technical challenges in healthcare data exchange, such as exposing data using FHIR or determining the necessity of adopting FHIR for a project. The content focuses specifically on 'FHIR Server Implementations' and 'The Business of FHIR.'
FHIR is useful when there are requirements for data sharing, regulatory mandates, or customer expectations. However, adopting it merely because of its status as a 'future standard' can increase unnecessary complexity and workload, risking project stagnation.
This system is a Model Context Protocol (MCP) server that enables seamless interaction between Large Language Model (LLM) agents and FHIR-compliant backends. This allows users to query and manipulate clinical data using natural language prompts.
A developer struggled to extract information from a FHIR Bundle Response using FHIRPath.API, encountering difficulties with syntax and application methods. The solution involved processing the JSON data as a dynamic object via QuickStream, successfully extracting target information such as MRN and names.
As the importance of healthcare data sharing grows, migrating from traditional HL7 to the more flexible and real-time FHIR standard is essential. This improves interoperability across diverse platforms like EHRs and telemedicine, contributing to better patient care.
While Electronic Health Record (EHR) systems face challenges in seamless data exchange, the SMART on FHIR framework enables plug-and-play app development, achieving seamless integration. This allows providers to access real-time, patient-centered data, improving care quality and efficiency.
This article provides a technical sample showing how a specific medical questionnaire, the 'New Patient Questionnaire,' is structured as an FHIR resource. The questionnaire includes items designed to collect basic patient information such as allergy status, gender, date of birth, and country of birth.
A Python-based MCP server simulates FHIR API interactions, enabling agent testing in the MedAgentBench environment without requiring a real FHIR endpoint. It supports rapid verification and complex scenario simulation during development and validation stages.
This article introduces the Model Context Protocol (MCP) based 'Agent Care' server. This server securely connects to major Electronic Medical Record (EMR) systems like Cerner and Epic using SMART on FHIR API, making FHIR data accessible. Its purpose is to facilitate clinical data analysis and research support through AI model integration.
This article demonstrates the procedure for sending a `Patient` resource to a specific API endpoint using the POST method. The request utilizes test data, including personal information such as names and dates of birth, confirming the handling of medical data based on the FHIR standard.
HAPI FHIR has published detailed class hierarchy information for the `ca.uhn.fhir.merge` package. This provides developers with technical structure details concerning resource and provenance merging processes.
This page is part of the implementation guide for 'Health Terminologies,' which is based on FHIR (HL7® FHIR® Standard) R4. It provides information regarding a resource set definition called 'ValueSet: JDV_J281_StatutsRessourcesMS - Demande,' noting that there are currently no specific requirements for this resource.
The page explains how to use Simplifier.net for FHIR resources that have a canonical URL. It clarifies that this tool makes it easy to reference these standardized URLs, which are otherwise inaccessible through regular web browsers.
Firely and HL7 International jointly released the '2025 State of FHIR' report. The findings reveal that while FHIR is becoming a global standard, significant challenges remain regarding regulatory enforcement, version control, and funding in various countries.