1,676 FHIR-related articles (latest first)
Canvas Medical updated its SDK and FHIR API for the EMR system. Key improvements include bug fixes regarding care team membership organization IDs for external providers, removal of character limits for background fields in Diagnose and Assess Condition commands. Additionally, events were added for various review commands (Imaging, Lab, Referral, Uncategorized Document), and database import functionalities were expanded.
The FHIR Department has established itself as a community dedicated to utilizing the Fast Healthcare Interoperability Resources (FHIR) standard. This department aims to unlock FHIR's transformative potential in healthcare through collaboration and knowledge sharing.
VCare Health has partnered with WTT Solutions, a software development company, to launch a next-generation digital healthcare platform. The system aims to improve clinic efficiency by automating tasks like scheduling and enhancing patient engagement using AI.
Wolters Kluwer Health released a report predicting deeper adoption of artificial intelligence (AI) in healthcare for 2026. The report emphasizes that successful AI implementation requires integration into existing workflows and strong governance structures.
FHIR Adaptive Forms enhance clinical data collection by dynamically assembling questionnaires based on context. This allows for more efficient and personalized data gathering, ensuring that only relevant information is collected from patients and clinicians.
FHIR (Fast Healthcare Interoperability Resources), developed by HL7 International, utilizes modern web technologies to enable the international exchange of structured medical data. This facilitates seamless interoperability between diverse systems and contributes to the advancement of digital healthcare.
The PanCareSurPass Project has published mappings for the Chemo therapy logical model. These detailed mappings are based on FHIR R4 and describe associations with multiple resources, including MedicationAdministration.
This webinar introduces how to revolutionize the healthcare sector by combining MongoDB, the FHIR standard, and Artificial Intelligence (AI) for advanced data management. A practical application is demonstrated using Leafy Hospital, tracking the entire data lifecycle of an oncological patient from prevention through follow-up.
This article introduces the trends and capabilities of major IT solution development companies in the accelerating field of healthcare digitalization. These firms contribute to solving global healthcare challenges through advanced technologies, such as building FHIR-compliant platforms and modernizing Electronic Health Records (EHR).
Maria Ryzhikova of Aidbox demonstrates how AI can significantly improve FHIR Structured Data Capture (SDC) workflows. She highlights the ability to convert clinical PDFs into structured Questionnaires and achieve multilingual support from a single definition.
Multiple training courses covering major healthcare data exchange standards such as FHIR, HL7 V2, and HL7 V3 are offered. These range from advanced implementation to foundational messaging concepts.
Fast Healthcare Interoperability Resources (FHIR), developed by HL7, has emerged as the leading standard to address interoperability barriers and data inconsistencies. This review comprehensively analyzes FHIR's role and challenges in global digital health strategy through integration with EHRs and AI.
Firely offers 'Firely Server Scale,' a robust server product compliant with the HL7 FHIR standard for healthcare institutions and IT companies. This product can be used across development and production stages, featuring core FHIR API functionalities alongside Smart on FHIR and MongoDB/SQL support.
This article explains that HL7 FHIR is available as a standard for handling medical information such as electronic health records and clinical notes. It emphasizes the importance of utilizing FHIR to solve challenges in data exchange between different systems.
HAPI FHIR provides a dedicated module for Android developers, enabling the use of FHIR model classes and client functionality. The client is optimized to request only JSON responses, requiring caution when integrating with servers that support only XML encoding.
This service offers comprehensive training to clinical research professionals, enabling them to build a data pipeline that seamlessly integrates electronic health records (EHRs) with sponsor's clinical trial databases. This addresses the challenges of evolving clinical trials and healthcare data management.
The emergence of Artificial Intelligence (LLMs) is shifting the handling of medical information from mere structure and syntax toward understanding 'meaning' and 'context'. Consequently, existing standards like FHIR are becoming essential not just as frameworks, but as foundational structures that provide 'semantic grounding' for AI.
Aidbox introduced OrgBAC (Organization-Based Hierarchical Access Control) and Topic-Based Subscriptions to address complex data management challenges in healthcare networks. This allows large hospital groups to exchange information safely and in real time, while ensuring each facility only accesses its own dedicated data.
The digital health sector is undergoing a 'digital renaissance,' requiring medical software development to evolve. This guide outlines the importance of AI, remote monitoring, and interoperability (FHIR/HL7) for startups and enterprises building solutions.
openFHIR is an engine that implements the FHIR Connect specification, facilitating bidirectional mappings between openEHR and FHIR. This documentation provides a comprehensive guide covering its overview, technical setup, and usage.