Amazon HealthLake Documentation

Amazon HealthLake is a HIPAA-eligible service helping healthcare and life sciences companies securely store and transform their data into a consistent and queryable fashion. Using the HealthLake APIs, healthcare organizations can copy health data, such as medical reports or patient notes, from on-premises systems to a data lake in the cloud, and analyze it at petabyte scale. HealthLake uses machine learning (ML) models to understand and extract meaningful medical information from the raw data, such as medications, procedures, and diagnoses. HealthLake organizes and indexes the information and stores it in the Fast Healthcare Interoperability Resources (FHIR) format to provide a view of each patient's medical history. After exporting data, organizations can build ML models with Amazon SageMaker and use advanced Amazon QuickSight analytics to understand relationships, identify trends, and make predictions from the newly normalized and structured data.

With the Amazon HealthLake import API you can migrate FHIR files from Amazon S3 to the Amazon HealthLake Data Store including clinical notes, lab reports, insurance claims, and more. HealthLake supports data in the FHIR R4 industry standard. 

Amazon HealthLake helps index information so it can be queried. The Data Store creates a view of each patient’s medical history in chronological order and facilitates information exchange using the V4 FHIR specification. The Data Store also helps to keep your index up-to-date, offering you the ability to query the information using the standard FHIR Operations with durable primary storage and index scaling. 

Integrated medical natural language processing (NLP) transforms unstructured healthcare data in the Data Store to help you extract meaningful information. With integrated medical NLP, you can 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. 

Amazon HealthLake supports FHIR Create/Read/Update/Delete (CRUD) and FHIR Search operations. You can query records by performing a Create Operation for adding new patients and their information. 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 information on a patient.

Amazon HealthLake supports the bulk export of FHIR data from the HealthLake Data Store to an S3 bucket. After exporting, you can also build, train, and deploy your own predictive analytics using machine learning models with Amazon SageMaker. 

For additional information about service controls, security features and functionalities, including, as applicable, information about storing, retrieving, modifying, restricting, and deleting data, please see https://docs.aws.amazon.com/index.html. This additional information does not form part of the Documentation for purposes of the AWS Customer Agreement available at http://aws.amazon.com/agreement, or other agreement between you and AWS governing your use of AWS’s services.