Amazon Launches HealthLake for Healthcare Orgs to Aggregate & Structure Health Data

AWS Announces Amazon HealthLake

What You Should Know:

– Amazon today announced the launch of Amazon HealthLake,
a new HIPAA-eligible service enables healthcare organizations to store, tag,
index, standardize, query, and apply machine learning to analyze data at
petabyte scale in the cloud.

– Cerner, Ciox Health, Konica Minolta Precision Medicine,
and Orion Health among customers using Amazon HealthLake.

Today at AWS re:Invent, Amazon
Web Services, Inc. (AWS),
an company today announced Amazon HealthLake, a
HIPAA-eligible service for healthcare and life sciences organizations. Current
Amazon HealthLake customers include Cerner, Ciox Health, Konica Minolta
Precision Medicine, and Orion Health.

Health data is frequently incomplete and inconsistent, and is often unstructured, with the information contained in clinical notes, laboratory reports, insurance claims, medical images, recorded conversations, and time-series data (for example, heart ECG or brain EEG traces) across disparate formats and systems. Every healthcare provider, payer, and life sciences company is trying to solve the problem of structuring the data because if they do, they can make better patient support decisions, design better clinical trials, and operate more efficiently.

Store, transform, query, and analyze health data in

Amazon HealthLake aggregates an organization’s complete data across various silos and disparate formats into a centralized AWS data lake and automatically normalizes this information using machine learning. 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.

Benefits for Healthcare Organizations

As a result, Amazon HealthLake makes it easier for customers to query, perform analytics, and run machine learning to derive meaningful value from the newly normalized data. Organizations 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 so they can make much more precise predictions about the progression of the disease, the efficacy of clinical trials, the accuracy of insurance premiums, and many other applications.

How It Works

Amazon HealthLake offers medical providers, health insurers,
and pharmaceutical companies a service that brings together and makes sense of
all their patient data, so healthcare organizations can make more precise
predictions about the health of patients and populations. The new
HIPAA-eligible service enables organizations to store, tag, index, standardize,
query, and apply machine learning to analyze data at petabyte scale in the

Amazon HealthLake allows organizations to easily copy health
data from on-premises systems 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
(e.g., medications, conditions, diagnoses, procedures, etc.) so all this
information can be easily searched.

For example, organizations can quickly and accurately find
answers to their questions like, “How has the use of cholesterol-lowering
medications helped our patients with high blood pressure last year?” To do this,
customers can create a list of patients by selecting “High Cholesterol” from a
standard list of medical conditions, “Oral Drugs” from a menu of treatments,
and blood pressure values from the “Blood Pressure” structured field – and then
they can further refine the list by choosing attributes like time frame,
gender, and age. Because Amazon HealthLake also automatically structures all of
a healthcare organization’s data into the FHIR industry format, the information
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.

“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. “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. 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.”

Ciox Health Acquires Biomedical NLP Company Medal

Ciox Health Acquires Biomedical NLP Company Medal

What You Should Know:

– Ciox Health has acquired Medal, Inc., a biomedical
Natural Language Processing (biomed-NLP) technology company.

– The acquisition will lead Ciox to better and more
quickly enable real-world data in support of research that advances patient

, a leading health technology company, today announced its acquisition
of San Francisco-based biomedical Natural Language Processing (biomed-NLP)
technology company, Medal, Inc., a leader
in the application of AI techniques to the interrogation of unstructured
medical record data. The acquisition accelerates capabilities to enable
real-world data (RWD) in support of research that advances patient care.

The Real-World Data Advantage

As more pharmaceutical and research organizations look to real-world data to accelerate clinical research, reliable identification, and interpretation of phenotypic data from deep inside medical records are becoming paramount. The most relevant information resides in the unstructured data: the surgical reports, pathology reports, imaging reports, discharge summaries, and other clinician-scribed narrative text. Medal’s software helps identify, contextualize, and interpret narrative-based medical notes, leading to the creation of research-grade data sets at scale. The company’s approach to biomed-NLP and deep learning AI is guided and informed by consensus from clinical expert reviewers across therapeutic areas.

“More than 100 million medical records are retrieved and reviewed by Ciox each year from the vast majority of U.S. providers, presenting an unprecedented opportunity to actually bring a true longitudinal perspective to clinical investigation. Ciox works at the first and last mile of U.S. healthcare data,” says Andy McMurry, Ph.D., Chief Science Officer of Medal. “Using Medal AI, Ciox will reduce human expert time and increase the utility of patient data to support biomedical discovery and clinical trials research across many disease areas, including COVID-19. Combining vast biomedical knowledge sources with clinically trained Artificial Intelligence enabling human experts, we are reinventing real-world data for clinical investigation.”

Acquisition Benefits for Ciox Health

This acquisition is the third major recent announcement from
Ciox’s growing Real World Data business, following two prior announcements of
strategic collaborations with LabCorp and Merck. As health data remains
fragmented throughout the U.S. healthcare ecosystem, Ciox is attracting
interest in its RWD division from medical research organizations and other
partners. This additional feature of the Ciox DataFit Platform through the
acquisition of Medal will enable faster and more consistent translational

Why It Matters

“We’re proud to bolster the Ciox Real World Data offering with Medal’s technology and team,” says Pete McCabe, CEO, Ciox. “The team and the biomed-NLP product, combined with Ciox’s technology-enabled ability to create longitudinal records across EHRs and provider systems, remove the friction related to medical records-based clinical research.  We will consistently supply consented, HIPAA-compliant, de-identified, research-grade RWD for complex clinical use cases to commercial researchers in pharma and biotech, as well as government sponsored researchers. The need is particularly highlighted in the COVID-19 research questions being asked by agencies like the FDA, CDC and NIH.”