Objective
Sepsis is the leading cause of preventable death in U.S. hospitals with mortality from sepsis increasing 8% for every hour that treatment is delayed. As many as 80% of sepsis deaths could be prevented with rapid diagnosis and treatment according to Johns Hopkins Armstrong Institute for Patient Safety and Quality. Diagnosing sepsis can be difficult because its signs and symptoms can be caused by other disorders and there are no reliable biomarkers before onset. Doctors often must order a battery of tests to try to pinpoint the underlying infection which further delays treatment.
Outcome
AI is particularly suited to situations where the signals of an issue are hidden by “noise” that obscures the actual problem from clinicians. Diagnosing Sepsis is one of those situations. AI driven early diagnosis based on routine vital signs and metabolic levels from electronic medical records can highlight patients at risk for Sepsis before they are admitted to the ICU where it may already be too late. AI can even be used to predict courses of treatment or dosage levels that are likely to be most effective based on patient history. Though early detection and more precision care, the patient is able to receive less aggressive and less costly treatments which improves patient outcomes and is better for payers and providers.
Why H2O.ai
The mission at H2O.ai is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. The healthcare industry is a key focus for the company with an initiative to help develop AI healthcare solutions including dedicated, experienced resources for customers, driving healthcare AI events and meetups for healthcare professionals, and membership in Health IT Now, the leading coalition of patient groups, provider organizations, employers, insurers, and other stakeholders. H2O.ai is already working with top healthcare companies including Change Healthcare, Armada Health, Kaiser Permanente, and HCA, and its products include industry leading features for machine learning interpretability required by the healthcare industry for compliance purposes.
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H2O has been the driver for building models at scale. We are talking about billions of claims. You can't do this with standard off the shelf open source techniques.”
Adam Sullivan, Director, Change Healthcare
With H2O we are building models to improve the patient experience in our hospitals and improve the nursing and doctor workflows as well.”
Allison Baker, Data Scientist, HCA
