AWS HealthLake expands to Canada, enabling healthcare organizations to store, transform, and standardize patient data using FHIR standards while maintaining data residency within the country.

Starting today, European healthcare and life sciences customers can use AWS HealthLake to store, transform, and analyze their health data in FHIR (Fast Healthcare Interoperable Resources) standards while maintaining data residency within the EU. AWS HealthLake is a fully managed FHIR storage, transactional, and analytics service. Customers can normalize and store health data from disparate raw data sources into a FHIR data store, and leverage HealthLake FHIR-based APIs to build interactive applications and interoperability workflows. Next, customers can leverage the HealthLake Analytics module to automatically transform FHIR data into an analytics-ready format for population health analytics, build patient cohorts, or train predictive models to improve quality of care. HealthLake data stores easily integrate with AWS AI and analytics tools such as Amazon Athena for SQL queries, Amazon QuickSight for visualization, and Amazon SageMaker for training and drawing inferences from ML models. In addition to Europe (Ireland), AWS HealthLake is available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Europe West (London), and Asia Pacific SouthEast (Sydney) Regions. Visit the AWS Region Table to see all the regions. To learn more, see the AWS HealthLake product page.

In this post, we show you how to build an automated claims processing pipeline using two key Amazon Bedrock capabilities: Amazon Bedrock Data Automation for intelligent document extraction from healthcare claim forms, and Amazon Bedrock AgentCore for hosting an AI agent that validates and transforms the extracted data into FHIR (Fast Healthcare Interoperable Resources) resources in AWS HealthLake. You will learn how to combine these services to create an end-to-end workflow that reduces manual processing while maintaining accuracy through automated validation checks.

In this post, we show you how to build an automated claims processing pipeline using two key Amazon Bedrock capabilities: Amazon Bedrock Data Automation for intelligent document extraction from healthcare claim forms, and Amazon Bedrock AgentCore for hosting an AI agent that validates and transforms the extracted data into FHIR (Fast Healthcare Interoperable Resources) resources in AWS HealthLake. You will learn how to combine these services to create an end-to-end workflow that reduces manual processing while maintaining accuracy through automated validation checks.

Managing healthcare infrastructure is complex and challenging — HIPAA compliance, server ops, and secure networking slow teams down before any product work begins. AWS HealthLake eliminates that overhead with a fully managed, FHIR R4-compliant service. This guide walks you from zero to a live endpoint: provisioning a HealthLake data store, testing with Postman via AWS Signature V4, and integrating into a Node.js app — so you can ship faster and stay compliant.

Starting today, European healthcare and life sciences customers can use AWS HealthLake to store, transform, and analyze their health data in FHIR (Fast Healthcare Interoperable Resources) standards while maintaining data residency within the EU. AWS HealthLake is a fully managed FHIR storage, transactional, and analytics service. Customers can normalize and store health data from disparate raw data sources into a FHIR data store, and leverage HealthLake FHIR-based APIs to build interactive applications and interoperability workflows. Next, customers can leverage the HealthLake Analytics module to automatically transform FHIR data into an analytics-ready format for population health analytics, build patient cohorts, or train predictive models to improve quality of care. HealthLake data stores easily integrate with AWS AI and analytics tools such as Amazon Athena for SQL queries, Amazon QuickSight for visualization, and Amazon SageMaker for training and drawing inferences from ML models. In addition to Europe (Ireland), AWS HealthLake is available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Europe West (London), and Asia Pacific SouthEast (Sydney) Regions. Visit the https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ to see all the regions. To learn more, see the https://aws.amazon.com/healthlake/.  

AWS HealthLake enables multi-tenant FHIR data management through two primary architectures: full tenant separation with unique encryption keys or a single data store with logical tenant isolation using application-level security controls.

AWS HealthLake MCP Server is an open-source tool that enables developers to build AI agents that interact with healthcare data using natural language, simplifying FHIR operations and reducing complexity in healthcare data management.

A security flaw in the AWS HealthLake MCP Server allows an attacker to steal sensitive credentials. This could enable unauthorized access to AWS resources.

We’re excited to announce the expansion of AWS HealthLake to the EU (Dublin) Region, marking a significant milestone in our commitment to supporting healthcare organizations across the European Union (EU). Read this post to learn more.

Starting today, healthcare organizations can now transform legacy clinical documents into queryable FHIR resources in AWS HealthLake in days instead of months, unlocking use cases such as longitudinal patient record generation, population health analytics, and clinical data exchange. AWS HealthLake data transformation agent (preview) is an AI-powered capability that converts Consolidated Clinical Document Architecture (CCDA) files into Fast Health Interoperability Resources Release 4 (FHIR R4)-compliant resources without requiring specialized FHIR expertise, through an integrated experience that combines real-time conversion testing, AI-assisted template customization, and scalable bulk import. The data transformation agent includes ready-to-use templates for CCDA 2.1 to FHIR R4 data conversion. Developers can submit individual CCDA files through a synchronous conversion API or console workflow and receive transformed FHIR Bundles in seconds. They can preview results, interactively validate conversion quality, and sign off on templates before production use. An enhanced import workflow automatically detects uploaded CCDA files, applies the active template, matches and reconciles patients based on identifiers, and ingests the resulting FHIR resources into the target AWS HealthLake datastore with detailed logs. All capabilities are available both on the AWS console and programmatically via API for seamless integration into existing workflows. When default templates need adjustment, the data transformation agent offers an AI-powered experience to customize them directly in the console. Users can describe changes such as "skip medications with status entered-in-error" or "map procedure dates to performedDateTime instead of performedPeriod" in natural language, and the AI agent modifies the underlying template automatically. Manual curation is also available for power users who wish to make targeted template edits. Users can then immediately test against sample files, iterate conversationally, and publish once satisfied. AWS HealthLake is available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Europe West (London), Europe (Ireland), and Asia Pacific SouthEast (Sydney) Regions. Visit the AWS Region Table to see all the regions. To learn more, see the AWS HealthLake product page.

Groups Conversations All groups and messages Sign in     CVE-2026-15643 - AWS HealthLake MCP Server SSRF via Unvalidated Pagination URL (2026-054-AWS) 0 views Eyal Estrin unread, 9:07 AM (1 hour ago)    to https://aws.amazon.com/security/security-bulletins/2026-054-aws/ Eyal Estrin Author | Cloud Architect | AWS • Azure • GCP Insights Social: @eyalestrin Connect: https://linktr.ee/eyalestrin Blog: https://security-24-7.com Reply all Reply to author Forward

AI agents built on Amazon Bedrock AgentCore help clinical trial teams make fast, accurate enrollment decisions while keeping clinicians in control. This post shows how to architect an eligibility and safety screening agent using AWS HealthLake, AgentCore, and AgentCore Evaluations.

Evidence suggests that adverse consequences of heart disease, such as stroke and heart attack, can be prevented by appropriate lifestyle and medical management. Leveraging standards-compliant services, such as Amazon Web Services (AWS) HealthLake, the People Heart Study team has built a system that allows it to collect and analyze health data relevant to the study. [...]

Healthcare applications are different from typical applications. In this Article I explain about what are the Healthcare Services and How AWS help to implement those to me.

api-change:healthlake: New HealthLake API, RestoreFHIRDatastore, providing the capability to restore active datastores to a point in time within the last 30 days or recover a deleted datastore from the delete snapshot.; api-change:cognito-idp: Adds two new operations - GetClientToken which allows…