Amazon HealthLake aggregates an organisation's complete data across various silos and disparate formats into a centralised AWS data lake and automatically normalises this information using machine learning, the company said the AWS re:Invent conference on Tuesday.
The service makes it easier for customers to query, perform analytics, and run machine learning to derive meaningful value from the newly normalized data.
Organisations such as healthcare systems, pharmaceutical companies, clinical researchers, health insurers, and more can use Amazon HealthLake to help spot trends and anomalies in health data.
This can help them make much more precise predictions about the progression of disease, the efficacy of clinical trials, the accuracy of insurance premiums, and many other applications, AWS said.
"With Amazon HealthLake, healthcare organizations can reduce the time it takes to transform health data in the cloud from weeks to minutes so that it can be analyzed securely, even at petabyte scale," said Swami Sivasubramanian, Vice President of Amazon Machine Learning for AWS.
"This completely reinvents what's possible with healthcare and brings us that much closer to everyone's goal of providing patients with more personalized and predictive treatment for individuals and across entire populations."
AWS said that Cerner, Ciox Health, Konica Minolta Precision Medicine, and Orion Health are among the customers using Amazon HealthLake.