· First, customer datasets – claims, EHR data, labs and other data types – are collected, organized and harmonized by Lumiata using the Fast Healthcare Interoperability Resources (FHIR) standard.
· Second, the data is run through the Risk Matrix deep learning models, rapidly generating insights for each individual. Once customer data is initially mapped into FHIR, the Risk Matrix output can be generated for over a million records in less than three hours.
· Finally, end users can access Risk Matrix analyses via an FHIR-compliant API, allowing them to incorporate the output into existing workflows to maximize adoption and action.
"One of the biggest challenges for any risk bearer, but certainly for large health plans, is the struggle to fully utilize the different data types that are available today," says Ed Cymerys, former Chief Actuary at Blue Shield of California. "More precise predictions are necessary, but not sufficient to fundamentally improve risk and care management in a value-based model. Strong predictions coupled with clinical evidence help overcome one of the industry's biggest challenges – giving providers the confidence to act."
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For more information on the Risk Matrix, please visit riskmatrix.lumiata.com
About Lumiata
Lumiata is a predictive analytics company that leverages medical artificial intelligence to enable health organizations to manage risk and prioritize care. The Lumiata Risk Matrix delivers precise, clinically-relevant predictions on individual risk over specific timeframes, with accompanying medical evidence. The company's core technological engine is the Lumiata Medical Graph, which analyzes hundreds of healthcare data sets within the context of clinical practice and the world's medical knowledge, and maps out insights on current and future health trajectories of individuals. Founded in 2013 and based in Silicon Valley, Lumiata's team is comprised of clinicians, data scientists, and experts in care delivery. For more information, visit www.lumiata.com or follow @lumiata.
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