Search results for "FHIR": 1,661 articles
npj Digital Medicine reported a method for real-time prediction of next generation sequencing (NGS) results using machine learning via the Heme-STAMP project. This system demonstrates potential clinical application by integrating with Electronic Health Record (EHR) data and utilizing the FHIR API.
A developer has released a cross-platform CLI tool to solve the challenges of bulk resource updates using FHIR APIs. This tool eliminates the manual effort and error risk associated with creating JSON Patch (RFC6902) payloads from spreadsheets.
The article addresses the difficulty of information exchange in large hospitals due to coexisting standards (HL7 v2, FHIR) and numerous subsystems (PACS, LIS). It presents a case study detailing the implementation of smart clinical decision support (CDS) using an MCP architecture.
This article explains advanced operations in JSONata for the data transformation tool FUME. It focuses on functions like $keys(), $lookup() (object manipulation), and advanced features such as $merge(), $map(), and $zip(). These techniques allow for more flexible and efficient structuring of input data and mapping to FHIR resources.
The integration of Artificial Intelligence (AI) with the FHIR standard is significantly advancing how healthcare data is shared and utilized. This combination enables advanced patient care, including improved diagnostic support, personalized treatment planning, and predictive risk assessment.
John Moehrke has provided a ValueSet (AuthPurposesVS) defining 'Authorization purposes for delegation access' for FHIR v4.3.0. This serves as a standardized code system detailing the scope of information access granted by a patient to family members.
Microsoft Azureを利用し、PowerShellコマンドレットを用いてFHIRサービスリソースの更新方法が示されている。この機能は、医療データ交換のための標準規格であるFHIRに対応したサービスの管理に役立つ。
This article is a technical guide for managing and deleting the FHIR destination of an IoT Connector within a Microsoft Azure environment. Developers learn how to use the `Remove-AzHealthcareIotConnectorFhirDestination` PowerShell cmdlet to remove this connection from specific resource groups.
A Master Patient Index (MPI) is crucial for eliminating duplicate patient records across multiple systems, maintaining a single, accurate patient identity. Integrating this with FHIR enables EHRs and telemedicine providers to instantly access the latest data, thereby improving data reliability and interoperability.
HL7 has released the specification for a ValueSet called 'Diagnostic Service Section ID,' which is used to identify the observation site of diagnostic services. This code set includes 45 concepts covering diverse medical fields, such as blood gases and imaging.
This article provides a sample data set defining a fictional practitioner, 'JohnMoehrke,' based on the FHIR v4.3.0 specification. This resource demonstrates the basic structure for personal information and contact details within an electronic health record system, aiding understanding of standard medical information representation.
openFHIR is an engine that implements the FHIR Connect specification, enabling bidirectional mapping between openEHR and FHIR. This enhances interoperability across different healthcare systems and promotes data utilization.
The Global Alliance for Genomics and Health (GA4GH) has developed the Phenopacket Schema, a standard for sharing disease and phenotype information. This schema can comprehensively describe an individual's clinical data, including rare diseases, offering more detail than just a list of HPO terms.
John F. Moehrke is an architect contributing to global healthcare data exchange and privacy protection. He has led standards like HL7 and IHE, providing expertise on FHIR Consent management and handling sensitive data.
This article details how to retrieve the properties of a specified IoT Connector's FHIR destination using the `Get-AzHealthcareIotConnectorFhirDestination` cmdlet from the Az.HealthcareApis module. It explains checking configuration details for healthcare data linkage within an Azure environment.
This article provides a technical explanation of the FUME Mapping Language, which combines JSONata and FLASH. It introduces how structure description is handled by FLASH and data manipulation is performed, demonstrating practical implementation methods for mapping data into FHIR resources.
FHIR is an international standard developed by HL7 that defines the structure for electronically exchanging health data between IT systems. It enables the open and transparent aggregation of data from diverse sources—such as medical institutions, apps, and wearables—making it available in a format suitable for analysis.
FHIR offers a modern solution to the challenge of data fragmentation in electronic medical records and billing systems. The article explains how FHIR has become a global standard for data exchange, improving patient care and data access through its future evolution (such as R6).
The Lowy Institute highlighted the critical need for AI-driven tobacco control solutions across Southeast Asia, given its high smoking rates. It proposed that effective deployment requires a unified digital infrastructure and common data models to enable cross-border data sharing among member states.
Outcome Healthcare offers automatic conversion of CCD/CCDA documents into FHIR Bundles, maintaining message traceability and provenance. The platform ingests diverse data formats (HL7V2, V3, FHIR, CCDA) in real-time or batch, standardizing them into FHIR v4 for processing and secure storage.