Search results for "FHIR": 109 articles
This project aims to create standardized FHIR specifications for the public health service in Wiesbaden, Germany. The goal is to establish interoperability requirements for various specialized applications and platform solutions.
The ePA (Electronic Patient File) provided by gematik enables secure and user-friendly access to insured individuals' medical data. This guide explains the core, FHIR-based foundational services supporting the ePA, such as the Audit Event Service and Medication Service.
A mechanism for electronically sending patient prescription information to pharmacies using the RED telematik API communication service was observed. This process involves retrieving unread messages via a GET request and returning patient data and access codes in an XML dataset.
kv.digital announces the discontinuation of its communication service, "KV-Connect," in October 2025. Many applications have already successfully migrated to KIM (Kommunikation im Medizinwesen), which is established as the standard for secure communication in healthcare, and new FHIR-based interfaces are being implemented.
The German Medical Association (KBV) has warned that the communication platform 'KV-Connect' will be completely discontinued by October 2025. Consequently, related systems and data providers must urgently transition to its successor standard, 'KIM' (Kommunikation im Medizinwesen).
The BfArM (Federal Institute for Drugs and Medical Devices) is building a central terminology server to support electronic patient records (ePA) and digital medication processes. This initiative aims to establish the foundation for German healthcare data interoperability by providing standardized code systems and mappings.
eCovery's app for lower back pain has been listed as a DiGA (Digital Health Application) by the BfArM (Federal Institute for Drugs and Medical Devices). This makes it the only specialized app for back complaints that can be prescribed by doctors and reimbursed by all statutory health insurance funds, establishing a new standard for digital rehabilitation.
German research teams have developed new methods to solve the 'black box' problem—the lack of clarity in how Artificial Intelligence (AI) systems reach decisions. This aims to visualize and improve the reliability of AI judgments, particularly in the medical field.
BSI published a study concerning hospital information systems (KIS) and medical security.
A lab medicine expert points out the difficulty of integrating test data into electronic patient records (ePA). Although HL7 and FHIR are used in practice, true unified digitalization requires deep semantic standardization using standards like LOINC and SNOMED CT.
BSI published a study concerning hospital information systems (KIS) and medical standards like DICOM and HL7.
The Fraunhofer Institute, leading the 'FHIR-Starter' research project, has begun efforts to automatically structure unstructured medical text using LLMs and NLP. This aims to convert non-structured data, such as PDF clinical reports, into standardized formats, thereby improving the efficiency of utilizing healthcare data.
The Fraunhofer research project 'FHIR-Starter' is developing a software service that automatically analyzes and structures unstructured medical texts using LLMs and NLP. This aims to solve key challenges in utilizing medical data within Germany.
Insiders Technologies is participating in the 'FHIR-Starter' project, a collaboration with Fraunhofer Institute and Charité. They are developing technology to extract data from unstructured medical documents (like PDFs) using AI and convert it into the standardized FHIR format.
The 'FHIR-Starter' project, led by Fraunhofer IESE, aims for the automated structuring of medical data using LLMs and NLP. It seeks to utilize non-structured data scattered across Germany's electronic patient records (ePA) in FHIR format, significantly improving efficiency for clinical care and research.
The Fraunhofer IESE is developing 'FHIR-Starter,' a research project that uses AI and Natural Language Processing (NLP) to automatically convert unstructured medical documents, such as PDFs, into standardized data formats. The goal is to improve the efficient use and utilization of electronic health records and clinical notes.
A workshop hosted by Gefyra GmbH provided an in-depth explanation of HL7 FHIR, covering its technical foundations and applications in the medical field. Participants learned about FHIR mechanisms and differences from other standards, acquiring practical skills in resource creation and Search API usage.
The 'FHIR-Starter,' involving entities like Fraunhofer IESE, structures medical data using Artificial Intelligence (AI) to unlock new possibilities for research and practice. It aims to advance the digitization of electronic patient records (ePA), ensuring safe and GDPR-compliant data utilization.
The FHIR-Starter project, led by Fraunhofer IESE, is developing a software service that uses LLMs and NLP to extract medical information from unstructured electronic records (like PDFs) and convert it into standardized data formats. This aims to solve challenges in German healthcare, such as manual data entry and difficulty comparing historical patient findings, ultimately striving for the complete digitalization of the ePA.
Fraunhofer Institute launched the 'FHIR-Starter' project to automatically extract and standardize data from free-text medical documents (like PDFs) using Large Language Models (LLMs) and Natural Language Processing (NLP). This aims to solve key challenges in German healthcare data utilization.