Pangaea’s Novel AI Predicts Length-of-Stay & Risk of Mortality for Patients in the ICU

Pangaea Data, provider of a novel Artificial Intelligence (AI)-driven product for characterizing patients by mapping their journey and disease trajectories in a privacy-preserving and scalable manner, announces the publication of their product capabilities for characterizing patients to accurately predict length-of-stay and risk of mortality in the intensive care unit (ICU) with 85% precision.

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These clinically validated findings and novel AI capabilities are critical for clinicians to visualize patient journeys and trajectories, which can be applied in real-time to prospective patient records for patient monitoring, early diagnosis and treatment

These results have been published in the British Medical Journal (BMJ) Health & Care Informatics (Volume 29, Issue 1).

Pangaea’s outputs and new insights were validated by clinicians. These findings and novel AI capabilities are critical for clinicians to visualize patient journeys and trajectories, which can be applied in real-time to prospective patient records for patient monitoring, early diagnosis, and treatment. This is essential for hospitals to efficiently manage resources, such as ICU beds, staff and supplies, and for improving patient outcomes.

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Dr. Rick Sax, Former Senior Vice President at IQVIA, AstraZeneca and Merck, said: “The results of this publication highlight the efficacy of Pangaea’s novel product in utilizing existing patient records to capture clinically validated insights, including comorbidities, and accurately mapping patient journeys and predicting prognosis. This capability is an important step forward for improving patient outcomes, reducing healthcare costs, and enhancing the overall quality of patient care, especially in a critical care setting.”

Dr. Vibhor Gupta, Founder at Pangaea, said: “These findings demonstrate how novel AI can actively improve patient outcomes and help hospitals recognize quick wins through improved resource management, based on existing data.”

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