This article explains how to view the contents of a FHIR profile package in both project-based and standalone environments. It details the mechanism of 'Extensions,' which allows users to add user-defined data elements beyond the core structure.
This page provides an interface for searching and managing medical concepts and code systems through the Unified Medical Language System (UMLS). Users can reference diverse coding standardsβincluding FHIR, LOINC, and HCPCSβand view detailed definitions to create value sets.
HL7 has published the specification (ValueSet) for 'ActPriority,' a code set used to classify the urgency and necessity of services such as clinical procedures or tests. This code set defines 15 concepts, ranging from 'Stat' (highest priority) to 'Elective' (optional), accommodating various medical situations.
This project built an interoperability connector using NLP and AI, allowing non-specialists to gain insights from medical data simply by asking questions in plain English. The system automatically converts user queries into optimized SQL and displays FHIR-compliant data visually.
CareEvolution published detailed technical specifications for the Questionnaire Response resource within the HIEBus FHIR interface. This resource manages structured questions and answers, contributing to data standardization in healthcare information exchange.
MACH Orchestra provides FHIR templates, enabling healthcare organizations to leverage the FHIR standard and build an integrated clinical landscape without artificial barriers. This protects existing investments by reducing dependency on individual vendors.
This study developed DermaDashboard, an interactive dashboard built on a relational FHIR-compliant PostgreSQL database. This tool enables exploratory cohort building and data visualization in oncology by overcoming the analytical difficulties posed by complex FHIR structures, making it usable for nontechnical users.
Slovenian company Better has solidified its presence in international healthcare systems with its open digital health platform. Based on standards like FHIR and openEHR, the platform is used by over 1000 institutions across more than 28 countries, ensuring data accessibility and reusability.
InterSystems announced a new partnership with Google Cloud. This collaboration integrates InterSystems HealthShare to enhance healthcare data interoperability, enabling advanced analytics and decision support using generative and agentic AI.
This article introduces and evaluates multiple engineering teams trusted to shape digital healthcare. Each company is assessed based on critical criteria such as compliance (HIPAA, ISO 27001) and security, along with proven experience in developing complex systems like EHR, IoMT, and FHIR integrations.
Innovaccer offers a FHIR-enabled Data Activation Platform (DAP) that enables healthcare providers and payers to deliver transparent, real-time, and collaborative care based on unified patient records. The platform uses AI for data analytics and decision support, contributing to better patient-centered care by automating routine workflows and enhancing decision-making.
InterSystems announced a partnership with Google Cloud. This integrates InterSystems HealthShare with the Google Cloud Healthcare API, enhancing data harmonization and scalability. Healthcare providers can now implement generative AI and agentic AI using reliable data.
This study evaluates the feasibility of achieving semantic interoperability within FHIR resources by utilizing business meta-models. The research demonstrates the importance of meaning consistency and standardization in data exchange.
Users on Google Skills are sharing their experiences and evaluations regarding the topic 'Ingesting FHIR Data with the Healthcare API'. Multiple users posted reviews at various times, such as four months ago, noting that the process requires time for troubleshooting and internalization.
Google Cloud provides technical reference information on utilizing the Cloud Healthcare API to handle multiple standards, such as converting HL7v2 to FHIR and converting FHIR to OMOP. This allows EHR data and research data to be utilized in a unified format.
This article details how to build a semantic search-enabled vector repository for FHIR healthcare data using InterSystems IRIS as the foundation, leveraging Python libraries like IRIStool. It explains creating schemas for various FHIR resources (e.g., Patient) and storing embedding vectors to enable advanced natural language querying.
A review page on Google Skills introduces a method for streaming the conversion of HL7 data into FHIR format, utilizing Dataflow and the Healthcare API. This technique provides a concrete approach for migrating legacy medical data (HL7) to modern standard specifications (FHIR).
A FHIR ValueSet defining standard concepts for specific biopsy results. This ValueSet references SNOMED CT and includes codes such as 'Biopsy result normal (finding)' and 'Normal histology findings (finding)', representing normal pathological findings.
Dicom Systems offers the 'Unifier Medical Image Workflow Cloud Appliance,' strengthening data connectivity between medical imaging systems (PACS/MIMPS) and Electronic Health Records (EHR/EMR). The product supports major protocols like DICOM, HL7, and FHIR, achieving overall workflow automation and enhanced security.