Amazon HealthLake is a HIPAA-eligible service that enables healthcare providers, health insurance companies, and pharmaceutical companies to store, transform, query, and analyze health data in a consistent fashion in the AWS Cloud at petabyte scale. Using the HealthLake APIs, healthcare organizations can easily copy health data, such as imaging medical reports or patient notes, from on-premises systems to a secure data lake in the cloud. HealthLake uses machine learning (ML) models to automatically understand and extract meaningful medical information from the raw data, such as medications, procedures, and diagnoses. HealthLake organizes and indexes all the information and structures it in the Fast Healthcare Interoperability Resources (FHIR) industry standard format to provide a complete view of each patient's medical history.
Import: Quickly and easily ingest health data
Bulk import allows customers to easily migrate their on-premise FHIR files including clinical notes, lab reports, insurance claims, and more to a S3 bucket in their account, where their data can be used in further downstream applications. Currently, HealthLake supports data in the FHIR R4 industry standard. If your data is not in this format you can work with an AWS partner to convert legacy healthcare formats to FHIR.
Store: Store health data in the AWS Cloud in a secure, compliant, and auditable manner
Data Store helps you index all of your information so it can be easily queried. The Data Store creates a complete view of each patient’s medical history in chronological order and facilitates the exchange of information using the V4 FHIR specification. The Data Store is always running to keep your index up to date, offering you the ability to query the information anytime using the standard FHIR Operations with durable primary storage and index scaling. Amazon HealthLake meets rigorous security and access controls to ensure patients’ sensitive health data is protected and meets regulatory compliance.
Transform: Transform unstructured data using specialized ML models
Integrated medical natural language processing (NLP) transforms all of the raw medical text data from the Data Store using specialized ML models that have been trained to understand and extract meaningful information from unstructured healthcare data. With integrated medical NLP, you can automatically extract entities (e.g., medical procedures, medications), entity relationships (e.g., a medication and its dosage), entity traits (e.g., positive or negative test result, time of procedure), and Protected Health Information (PHI) data from your medical text. For example, HealthLake can accurately identify patient information from an insurance claim, extract laboratory reports, and map to medical billing codes like ICD-10 in minutes, rather than hours or weeks.
Query: Powerful query and search capabilities
Amazon HealthLake supports FHIR CRUD (Create/Read/Update/Delete) and FHIR Search operations. You can query records by performing a Create Operation for adding new patients and their information, like medications. You can read the most recent version of that record by performing a Read Operation. You can update a previously created record by performing an Update Operation. As per the FHIR specification, deleted data is only hidden from analysis and search results; it is not deleted from the service, only versioned. You can also search with predefined filters to find all the information on a patient.
Analyze: Identify trends and make predictions
Amazon HealthLake enables customers to bulk export their FHIR data from the HealthLake Data Store to an S3 bucket. With Amazon QuickSight developers can create dashboards on the exported and normalized data to quickly explore trends about their patients. Here is an example about how to use QuickSight for analytics and monitoring for population health analytics. Developers can also build, train, and deploy their own predictive analytics using machine learning models with Amazon SageMaker. Here is an example about building two predictive models with SageMaker and Healthlake.