Quantiphi is a launch partner for Google Cloud’s Healthcare Data Engine, an end-to-end solution facilitating the harmonization of clinical and operational data, enabling new models of collaboration across health care systems, health insurance organizations, and life sciences organizations.
Quantiphi, an AI-first digital engineering company, announced that it has been named a launch partner for Google Cloud’s new healthcare solution, Healthcare Data Engine—an intelligent end-to-end solution designed to harness the power of digital data to help healthcare and life sciences operational leaders, researchers, and clinicians gain real-time, holistic views of patient longitudinal records in a secure, compliant, and scalable cloud environment.
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Quantiphi has already been leveraging Google Cloud to enable digital transformation for healthcare organizations and being a Google Cloud launch partner for Healthcare Data Engine allows Quantiphi the freedom to innovate and test the solution further in real world customer environments. Over the past few months, Quantiphi has been pressure testing the solution in pilot customer engagements to harmonize rapidly evolving digital data to extract relevant insights and improve business outcomes.
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“We’re delighted to be a launch partner with Google Cloud on this exciting initiative”, said Bruno Nardone, Global Head of Healthcare and Life Sciences at Quantiphi, “This gives us a purpose built solution to assist forward looking HCOs with taking full advantage of the increase in digital health information, from seemingly more disparate sources daily, to delivery value to patients and other stakeholders across their ecosystems. The pendulum is shifting from expecting monolithic applications to do it all, to applying investments into strategic enterprise health information management solutions that curate myriad digital sources in support of organization goals. Healthcare Data Engine is perfectly designed to support this shift and allow us to more easily support our clients with realizing the full promise of digital innovation”
“Google is excited to partner with Quantiphi as a launch partner for our new healthcare solution, Healthcare Data Engine.” said Marianne Slight, Healthcare Product Manager at Google Cloud. “This accelerates innovation for use cases such as health equity, population health, and real world evidence that rely on analytics and AI on top of harmonized healthcare data – at scale. We are excited to explore the possibilities with our partners like Quantiphi, on how far we can accelerate our customers’ innovation with Healthcare Data Engine.”
With the exponential rise of data challenges in the healthcare industry, it is becoming imperative for healthcare and life sciences organizations to modernize their application-centric infrastructure to better manage and align healthcare data residing in loosely connected data stores. Google Cloud’s Healthcare Data Engine enables advanced information management and facilitates in-depth real-time analytics to efficiently close clinical care gaps.
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Google Cloud’s Healthcare Data Engine combines a host of cutting-edge GCP services with new technology for harmonization and analytics on FHIR, and allows for easy and standardized data exchange between an organization’s multitude of healthcare applications and solutions. The solution complies with healthcare safety and data privacy regulation like the Health Insurance Portability and Accountability Act (HIPAA) standard and enables deploying a fully managed, highly scalable, enterprise-grade environment for building data-driven clinical and analytics solutions securely on Google Cloud.
Quantiphi, alongside Google Cloud, has emerged as a go-to partner for introducing ground-breaking healthcare solutions to the market that augment healthcare operations and alleviate medical institutions’ pain areas. Quantiphi has also recently earned 2X Google Cloud Partner of the year awards for 2020 – Data Analytics Specialization and Public Sector – US Education, and is a premier partner for Google Cloud holding advanced specializations in machine learning, data analytics, and marketing analytics.
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