Empower healthcare and life sciences leaders to make decisions from disjointed healthcare data
Healthcare Data Engine builds on and extends the core capabilities of the Google Cloud Healthcare API to make healthcare data more immediately useful by enabling an interoperable, longitudinal record of patient data. Healthcare Data Engine can map over 90% of HL7v2 messages to FHIR across leading EHRs out of the box, enabling a path to better care, while reducing the total cost of ownership.
Make better real-time decisions around population health, resource utilization, optimizing clinical trials and accelerating research, identifying high-risk patients, and other critical needs with health insights.
Protect your healthcare data with security and privacy controls you can trust
Take advantage of the same secure-by-design infrastructure, built-in data protection, and global network that Google uses to ensure compliance, redundancy, and reliability. Healthcare Data Engine incorporates a cloud configuration for healthcare that extends our security and privacy even further with HIPAA and HITRUST best practices.
Leverage our multi-layered security approach to get peace of mind that your data is protected, by default, in transit and at rest.
Scale as quickly and extensively as you need
Healthcare Data Engine is backed by Google Cloud’s highly scalable and secure HIPAA-compliant managed services and leverages Google’s Cloud Healthcare API and BigQuery for robust processing. Healthcare Data Engine brings the power of Google BigQuery’s analytics and AI to the healthcare industry, enabling healthcare organizations to process petabytes of their patient data.
Scale quickly to meet the fluctuating needs across your systems and facilities to meet complex needs, like managing population health.
Emory University researchers predict sepsis in intensive care patients
“The reason why this algorithm is doing such a fantastic job is because it’s providing information in the actionable window when physicians can take meaningful actions for a patient."
Ashish Sharma, Assistant Professor, Department of Biomedical Informatics, Emory University
Harvard Global Health Institute develops COVID-19 forecasting model
"The COVID-19 Public Forecasts is an important public health tool for guiding the policy response to the COVID-19 pandemic. By providing an ‘early warning system’ of COVID-19 cases, hospitalizations, ICU admissions, ventilator utilization, and deaths, the COVID-19 Public Forecasts create the opportunity for public health officials and policymakers to move from a reactive to a proactive approach to suppress the pandemic."
Dr. Thomas Tsai, MD, MPH, Surgeon and Health Policy Researcher, Harvard T.H. Chan School of Public Health
Moderna uses the right dose of data to boost discovery
“Now that we can bring in more external data sources alongside our own data, we’re making a very conscious decision to increase diversity in our clinical trials, pursuing more accurate representation.”
Dave Johnson, VP of Informatics, Data Science, and AI at Moderna
Schrödinger expedites drug discovery timeline using the cloud
"Traditional drug discovery projects, when successful, take about five to six years to get into clinical trials. By rapidly identifying good molecules with properties that justify advancement into clinical studies, we believe our platform may yield a faster timeline, potentially in the range of two to three years to the clinic.”
Dr Ramy Farid, CEO, Schrödinger