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Prognos and Datavant partner to improve health data analytics

Combining Prognos software and Datavant data sharing, healthcare data analytics vendors intend to improve early detection of disease, decision-making and patient care.

Two healthcare analytics companies, Prognos Health Inc. and Datavant, are combining technologies in a partnership to bring personalized ecosystems of patient health data to customers.

Prognos uses AI-powered analytics to track patient data and predict disease, while Datavant specializes in breaking down silos and analyzing health data securely and privately. With this partnership, Prognos uses Datavant's health data analytics ecosystem technology to expand the data providers can easily access to inform clinical decisions, identify risk, improve care quality and improve overall patient outcomes.

According to Prognos, it has been a challenge for healthcare organizations to incorporate clinical lab insights for analytics because of every lab's individual data complexity. The Prognos software provides a standardized view of national and regional laboratory results in a registry of 24 billion records that covers 200 million patients and over 50 disease conditions.

In a blog post, Datavant notes the potential benefits of interconnected data, including faster and lower-risk drug development, better understanding of new diseases, better patient care and a cheaper health system that ties cost to value.

In addition to the importance of predicting patient health, data analysis is integral to business value. Gartner identifies health data analysis as a significant barrier to achieving CIO objectives and predicts healthcare organizations will emphasize AI and advanced analytics spending in 2019.

Datavant will acquire Prognos' diagnostic data de-identification product, Opal, to enable data sharing with other Datavant partners; Datavant is specifically designed to allow protected data sharing.

According to the vendors, readily available data and access to lab-based AI technologies and advanced algorithms enable better decision-making earlier in the patient journey, and the vendor partnership expands possibilities for early tracking and prediction of disease.

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