3,748 FHIR-related articles (latest first)
A new study demonstrated that combining CDISC standards with HL7 FHIR enhances data for Alzheimerβs Disease (ADRD) research. This synergy increases the usability of real-world data from electronic health records, accelerating the bridge between clinical care and research.
The Mount Sinai Tisch Cancer Center implemented an automated system that seamlessly transfers clinical data from electronic health records directly into clinical trial platforms. This eliminates manual entry errors and inefficiencies, accelerating cancer research.
Google Cloud provides technical 'Reference Patterns' utilizing the Cloud Healthcare API to convert data, such as HL7v2 messages and FHIR resources, into standard models like OMOP. This allows structured organization of data obtained from Electronic Health Records (EHR).
This page provides information regarding the External Validation Service Front-end, promoted by IHE (Integrating the Heathcare Enterprise). The platform aims to enhance healthcare interoperability and connectivity, demonstrating continuous development efforts.
This tutorial guides researchers and data scientists on how to use Google Cloud's Cloud Healthcare API to remove or modify Personally Identifiable Information (PII) and Protected Health Information (PHI) from FHIR clinical data. This process protects patient privacy while preparing the data for research, data sharing, and machine learning.
HealthTrixss, built by industry veterans with over 20 years of experience, offers programs for risk adjustment, revenue management, and advanced analytics. They utilize FHIR-compliant platforms and AI tools to solve complex healthcare challenges.
FUME provides a real-time data interceptor that captures and transforms healthcare data streams. This ensures immediate compliance with FHIR standards, preventing interruptions in critical workflows like clinical alerts or monitoring updates that rely on rapid data exchange.
This service addresses the difficulty developers and clinical informaticists face when dealing with raw JSON payloads. By using the FHIR Viewer, complex FHIR JSON data is converted into a human-readable format, simplifying validation and sharing.
A new process has been established for clinicians and standards experts. This allows stakeholders to propose changes to the International Patient Summary (IPS) suite of standards, ensuring their continued accuracy and global applicability. Proposed changes can include corrections or improvements to existing standards, scope enhancements, or the addition of entirely new standards.
Outburn has introduced 'FUME,' a proprietary real-time data conversion engine. It enables non-intrusive, bidirectional data exchange between legacy formats like HL7 v2 and the modern FHIR standard.
Outburn has implemented a solution using embedded FUME Community Edition to establish seamless, standardized communication between healthcare organizations and insurance providers. This automates the payment authorization process that previously required patients to wait upon arrival, enabling real-time eligibility checks before medical care.
HL7 has released a code system for 'Religion' in the v2+ format. This CodeSystem includes identifiers for various denominations, such as Atheist, Catholic, and Hindu, helping to standardize faith information within medical data.
CSIRO is advancing the transformation of Australiaβs healthcare system using technologies like AI and FHIR. This effort aims to improve electronic health record sharing, enhance data accessibility, and advance sophisticated disease risk assessments.
InterSystems emphasized that realizing the full potential of AI in healthcare requires a reliable and interoperable data foundation. The company aims to implement clinically useful AI by providing platforms that integrate and govern data from diverse systems based on open standards like HL7 and FHIR.
This course teaches methods for ingesting and processing data in industry standard formatsβFHIR, HL7v2, and DICOMβusing the Cloud Healthcare API. Furthermore, it includes practical training on building prediction models with FHIR data and de-identifying datasets.
This article introduces a method to eliminate complex authorization logic in FHIR-based applications. By utilizing SMART on FHIR V2 scopes combined with Keycloak's composite roles, it is possible to achieve a system where a single API endpoint dynamically provides different data based on the calling user type, all without custom code.
Firely provides FHIR-based products and services to payers, providers, and digital health innovators, helping solve complex challenges related to sharing and utilizing healthcare data. This aims to enhance the overall connectivity and innovation within the healthcare ecosystem.
HL7 released the ValueSet 'hl7VScalendarAlignmentV100' to specify the alignment between repetition cycles and calendar dates. This helps clearly distinguish between expressions like 'the 5th of every month' and simple period specifications like 'every 30 days.'
At HIMAA 2025, the Australian e-Health Research Centre (AeHRC) showcased innovative use cases leveraging Sparked FHIR. They demonstrated how a single calculator was built by extracting data from GP records using FHIR APIs, highlighting its potential for clinical decision support at the point of care.
The Japan Association for Medical Data Utilization Infrastructure (IDIAL) will hold a specialized modeling training seminar starting November 2025. The seminar aims to teach practical skills, including information model construction using UML and mapping to HL7 FHIR.