Search results for "AWS": 95 articles
This document explains how to manage subscriptions for data ingestion and event notifications using FHIR standards within AWS HealthLake. Users must create a SubscriptionTopic and then a Subscription, which requires validation by HealthLake before reaching an 'active' status.
This guide details the process of creating an FHIR subscription using AWS HealthLake. This allows users to receive notifications when specific healthcare events (e.g., Encounter creation) occur, enabling data integration and real-time event handling.
This article explains the functionality of FHIR subscriptions within AWS HealthLake. Users can search for Subscription and SubscriptionTopic resources using various custom parameters and standard fields, allowing detailed data stream identification.
AWS HealthLake provides a 'Subscription' feature, based on FHIR standards, to monitor events within a data store and send notifications when specific criteria are met. This mechanism requires managing an entire lifecycle, from topic creation and subscription setup to activation, error handling, and deactivation.
AWS HealthLake offers 'FHIR Subscriptions' to provide real-time notifications when specific healthcare data changes occur. This enables the building of event-driven healthcare applications, allowing immediate response to clinical data changes and enhancing workflows and care coordination.
This guide explains the process of setting up and managing event monitoring (Subscriptions) for FHIR data using AWS HealthLake. It covers the entire lifecycle, from topic creation to subscription setup, activation, error handling, and deactivation.
This article provides technical guidance for developers using AWS HealthLake, detailing the process of obtaining a FHIR Discovery document. It outlines how client applications can identify the correct authorization endpoints and supported resources for a given HealthLake data store.
This guide explains how to use the POST request method for searching FHIR resources within an AWS HealthLake data store. The use of POST is recommended as a security best practice when searching sensitive information, such as PII or PHI.
AWS HealthLake offers selectable consistency models, 'strong' or 'eventual', when searching FHIR resources. This allows developers to control the required certainty of search results based on data update status.
Data-Sleek, a data strategy consulting firm, has expanded its services into regulated industries, including healthcare. By building unified data warehouses compliant with standards like HIPAA and FHIR, the company aims to secure patient information while providing real-time clinical and operational insights.
This article provides developers with a detailed guide on how to import FHIR format healthcare data using AWS HealthLake. It explains the process by utilizing the StartFHIRImportJob function, detailing implementation examples using AWS CLI and Python SDK (Boto3).
AWS provides guidance on creating data archives compliant with the FHIR R4 standard using HealthLake. This allows developers to manage, search, and export electronic health records.
Developers can export FHIR data using AWS HealthLake. Data extraction is possible through both native operations and the FHIR R $export operation within HealthLake.
AWS HealthLake adopts OAuth 2.0 as its authorization protocol, utilizing the SMART on FHIR framework to enforce granular access control. This allows client applications to access only the specific data scopes (patient, user, or system) required for their function.
This guide details the procedure for reading the current state of specific FHIR resources using AWS HealthLake. It is a technical guide on how to retrieve information from a data store using GET requests and various authentication methods (SigV4 or SMART on FHIR).
This article details the technical procedure for creating new healthcare resources (e.g., Patient) using the FHIR R4 API within AWS HealthLake. It serves as a comprehensive guide for adding data to a HealthLake datastore.
CapMinds provides comprehensive solutions utilizing standards like FHIR and HL7 to facilitate complex healthcare data exchange and integration. By supporting everything from API development to server construction, they aim to improve interoperability in systems like Japanese EHRs and regional health networks.
Global Tech Teams (DBA Mindbowser) offers an AI-powered patient symptom analyzer running on AWS. It generates structured clinical inputs in FHIR format from unstructured data, supporting real-time triage and decision-making for care teams.
Mindbowser's solution uses AI-powered phone questionnaires to capture structured FHIR data from patient conversations. This enables seamless integration with EHR workflows, supporting pre/post-visit follow-ups and adherence checks.
AWS HealthLake now supports the $document operation for Composition resources. This enables users to bundle all referenced resources into a single, standardized clinical document, facilitating comprehensive record creation and exchange.