Amazon’s cloud division rolled out a new tool to make it easier for healthcare organizations to search and analyze data.
Amazon HealthLake is a HIPAA-eligible service for healthcare and life sciences organizations that aggregates an organization’s complete data across various silos and disparate formats into a centralized Amazon Web Services (AWS) data lake and automatically normalizes this information using machine learning, the tech giant announced Tuesday.
The tool makes it easier for customers to query, perform analytics and run machine learning to derive meaningful value from the newly normalized data, the company said. Organizations such as healthcare systems, pharmaceutical companies, clinical researchers and health insurers can use this service to help spot trends and anomalies in health data so they can make much more precise predictions about the progression of disease, the efficacy of clinical trials and the accuracy of insurance premiums, AWS executives said.
The service identifies each piece of clinical information, tags and indexes events in a timeline view with standardized labels so it can be easily searched, and structures all of the data into the Fast Healthcare Interoperability Resources (FHIR) industry-standard format for a complete view of the health of individual patients and entire populations, according to Taha Kass-Hout, M.D., director of machine learning and chief medical officer at AWS, while speaking at the company’s virtual AWS re:Invent event Tuesday.
Healthcare organizations are making strides to apply analytics and machine learning to improve care, analyze population health trends and improve operational efficiency. But clinical data are complex and renowned for being siloed, incomplete, incompatible and stored in on-premises systems spread across multiple locations, the company said.
Most organizations resort to manual data entry by medical professionals, which adds expense to the digitization process. Even if organizations are able to aggregate and structure their data, they still need to build their own analytics and machine learning applications to uncover relationships in the data, discover trends and make precise predictions. The cost and operational complexity of doing all this work is prohibitive to most organizations, according to Kass-Hout.
Amazon HealthLake allows organizations to easily copy health data from on-premises systems such as electronic health records (EHRs) to a secure data lake in the cloud and normalize every patient record across disparate formats automatically. Upon ingestion, Amazon HealthLake uses machine learning trained to understand medical terminology to identify and tag each piece of clinical information, index events into a timeline view and enrich the data with standardized labels such as medications, conditions, diagnoses and procedures so all this information can be easily searched, AWS said.
The information stored in Amazon HealthLake can be easily and securely shared between health systems and with third-party applications, enabling providers to collaborate more effectively and allowing patients unfettered access to their medical information, the company said.
“There has been an explosion of digitized health data in recent years with the advent of electronic medical records, but organizations are telling us that unlocking the value from this information using technology like machine learning is still challenging and riddled with barriers,” said Swami Sivasubramanian, vice president of Amazon Machine Learning for AWS, in a statement.
“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,” he said.
EHR company Cerner has deepened its partnership with AWS to tap into its cloud and machine learning technologies and is working with AWS on artificial intelligence projects focused on readmissions and clinician burnout.
“At Cerner we are committed to transforming the future of healthcare through cloud delivery, machine learning, and AI. Working alongside AWS, we are in a position to accelerate innovation in healthcare. That starts with data. We are excited about the launch of Amazon HealthLake and its potential to quickly ingest patient data from various diverse sources and transform the data to perform advanced analytics to unlock new insights and serve many of our initiatives across population health,” said Ryan Hamilton, senior vice president, population health at Cerner, in a statement.
Health technology company Ciox Health also is working with AWS to make better use of its health data.
“Much of the health information that we ingest is unstructured, like notes and handwritten PDFs, and it is a challenge to find solutions that allow us to realize the full analytic value of that data. With 60 percent of the market share in risk adjustments, this is a huge opportunity. We are excited about getting started with Amazon HealthLake and its potential to help us meet this need and deliver better risk adjustments, predictions, billing, and much more, all informed by health data,” said Sasidhar Mukkamala, senior vice president of data management at Ciox Health.