The Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By utilizing this API, users can ingest industry-standard data formats—FHIR, HL7v2, and DICOM—and connect them to advanced capabilities like BigQuery and machine learning engines.
This article outlines the criteria healthcare leaders must evaluate when selecting a suitable implementation partner based on the FHIR standard, which is the backbone of modern healthcare interoperability. It emphasizes that comprehensive perspectives are needed, including technical capabilities, EHR integration experience, resource modeling, and security design.
Facing an explosion of global medical data, organizations are shifting focus from simple record retrieval to ensuring 'data structure and liquidity.' The AI-powered model utilizing the Philippines has demonstrated high efficiency and regulatory compliance through FHIR-compliant workflows.
This article explains how to achieve true interoperability beyond simple data exchange by leveraging the HL7 FHIR standard. By using services like Azure Health Data Services, clinical data is centralized into a unified Lakehouse in FHIR format, building a foundation with high 'data liquidity.'
Advanced AI model Claude has expanded its capabilities for use in healthcare and life sciences. Through the introduction of HIPAA-compliant tools and various connectors, it aims to improve operational efficiency in clinical settings, particularly enhancing the accuracy of prior authorization and claims processing.
Anthropic announced Claude for Healthcare, aiming to automate processes like prior authorization and integrate with EHR systems. The author reviews this technology, discussing its potential efficiency gains and the broader implications for medical practice.
Peking University Resources, through its health division ResoHealth, has formed a strategic partnership with Trivitron Healthcare to launch a digital health plan called “Trivitron Digital AI.” This platform aims to revolutionize healthcare services in India's second and third-tier cities, addressing the lack of advanced digital infrastructure.
Anthropic has released 'Claude for Healthcare,' an AI assistant designed for healthcare providers and insurance organizations. The tool operates in a HIPAA-compliant environment, supporting complex medical tasks such as verifying insurance coverage and medical coding.
Anthropic announced the launch of 'Claude for Healthcare,' an AI tool compliant with HIPAA. This provides new functionalities for healthcare providers, payers, and consumers, while also expanding support into life sciences.
Anthropic officially launched 'Claude for Healthcare,' a specialized AI tool compliant with HIPAA. The tool supports connections to CMS databases and ICD-10 coding systems, adding new features like FHIR development capabilities and pre-authorization review agent skills for providers, payers, and consumers.
Researchers at Isik University developed a real-time patient monitoring dashboard compliant with FHIR R4. This platform tracks vital signs and manages clinical observations, aiming to facilitate personalized care delivery by integrating with existing Electronic Health Record (EHR) systems.
Anthropic's 'FHIR Developer Agent skill' improves interoperability between healthcare systems via Claude Code. This skill provides specialized knowledge based on the HL7 FHIR R4 standard, assisting in clinical data validation and REST API construction.
Modern data architecture is necessary to effectively utilize the massive amounts of data generated by hospitals and health systems. The goal is to overcome siloed environments and build a reliable information foundation based on standards like FHIR.
The next-generation medical AI platform, MAIVE, enables advanced reasoning from complex clinical data using a large context window and multimodal understanding. Designed with interoperability standards like FHIR, it is expected to have high compatibility with Japanese EHR systems.
This page is a reference defining the ValueSet for 'Cardiac Arrest,' which is based on ICD-10-CM codes. The set includes multiple specific codes covering various causes, such as those related to underlying conditions and pregnancy.
This work proposes EHRSummarizer, a privacy-aware, FHIR-native reference architecture. It retrieves targeted high-yield FHIR R4 resources from electronic health records (EHRs) and normalizes them into a consistent clinical context package to generate structured summaries that support chart review.
This page captures a response from the HAPI FHIR test server, displaying multiple healthcare resources (Basic, Task) in Bundle format. It confirms the change history and status of these resources. Specifically, it demonstrates concrete examples of using the FHIR API, such as deleting resource history using the DELETE method and creating new Task resources via POST.
Computable Publishing LLC provides a 'Resource Viewer' as part of the FEvIR® platform. This tool allows users to view specific medical resources using an FHIR Linking Identifier.
This article explains how to browse the contents of an imported FHIR profile package. It details access methods in both project and standalone environments, and describes how to view segments, elements, and especially the customizable 'Extensions' within a resource.