Amazon HealthLake removes this heavy lifting by using highly accurate machine learning to automate the extraction and transformation of unstructured health data so organizations can apply advanced analytics and customized machine learning models to their information. Using Amazon HealthLake, organizations can easily move their FHIR-formatted health data from on-premises systems to a secure data lake in the cloud. Amazon HealthLake uses specially tuned machine learning models that understand medical terminology to identify and tag each piece of clinical information. The service then enriches data with standardized labels (e.g. medications, conditions, diagnoses, etc.) so the data can be easily searched and analyzed. Amazon HealthLake also indexes events like patient visits into a timeline, giving medical professionals a holistic, chronological view of each patient’s medical history. Once this heavy lifting is completed, customers can apply analytics and machine learning on top of this newly normalized and structured data. For example, customers can apply analytics using Amazon QuickSight to understand patient and population-level trends, as well as build powerful machine learning models with Amazon SageMaker to help make accurate predictions about the progression of disease, the efficacy of clinical trials, the eligibility of insurance claims, and more. Amazon HealthLake also stores data in the FHIR format to facilitate the exchange of information so that it is easy for organizations, researchers, and practitioners to collaborate and accelerate breakthroughs in treatments, deliver vaccines to market faster, and discover health trends in patient populations. Customers who do not already have data in the FHIR format can work with AWS Connector Partners, such as Diameter Health, InterSystems, Redox, and HealthLX, who have built validated Amazon HealthLake connectors to transform existing healthcare data into FHIR format and move it to Amazon HealthLake.

Amazon HealthLake’s purpose-built analytics and machine learning capabilities are also now available to customers under AWS for Health, a growing portfolio of solutions that simplifies how healthcare, biopharma, and genomics organizations discover, assess, and deploy cloud solutions to achieve better business and patient outcomes. For example, solutions offered in AWS for Health are helping customers create holistic Electronic Health Records to help clinicians make data-driven care plans, accelerate research and discovery to bring new therapies to market faster, and powering population genomic initiatives to expand precision medicine accessibility.

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