Bayesian Health and Johns Hopkins have announced ground-breaking results showing that many lives have been saved with a new clinically deployed AI platform called Targeted Real-Time Early Warning System (TREWS). The AI platform activates state-of-the-art AI within the electronic medical record and tracks patients from the moment they are admitted to hospital until they are discharged. The early warning system is designed to send alerts to healthcare providers when there is cause for concern. A real world study - conducted in 5 hospitals - demonstrated that the TREWS AI system led to the detection of sepsis on average almost 6 hours earlier than traditional methods, with a sensitivity rate of 82%. This is significant because sepsis is responsible for 20% of all deaths globally and early detection could save over 11 million lives every year.

Hospitals and health systems are rolling out more tools that analyze and crunch data to try to improve patient care--raising questions about when and how it's appropriate to integrate race and ethnicity data. Racial data has grown more complicated as the U.S. becomes increasingly diverse, with a growing number of Americans identifying with more than one race or ethnicity. The number of Americans who identify with at least two races has doubled over the past decade, according to last year's U.S. census, which takes place every 10 years. The Census Bureau started letting people identify as more than one race in 2000, according to the New York Times. That's a demographic shift that executives should keep top-of-mind as the healthcare industry moves toward being more data-driven.

Imagine that a friend or loved one is in the hospital for a routine operation or procedure. It seems like they are on their way to recovery, but then, you learn that septic shock -- a widespread infection leading to organ failure and low blood pressure -- has set in. Your loved one needs immediate and urgent medical attention. Such an outcome is not out of the ordinary. According to the CDC, about 270,000 of the 1.7 million American adults that develop sepsis will die each year, and 1 in 3 hospital deaths are the result of sepsis.

Artificial intelligence's applicability in healthcare settings may not have lived up to corporate ... [ ] and investor hype yet, but AI experts believe we're still in the very early stages The "AI in healthcare: myth versus reality" discussion has been happening for well over a decade. From AI bias and data quality issues to considerable market failures (e.g., the notorious missteps and downfall of IBM's Watson Health unit), the progress and efficacy of AI in healthcare continues to face extreme scrutiny. John Halamka, M.D., M.S., is President of The Mayo Clinic Platform As President of the Mayo Clinic Platform, John Halamka, M.D., M.S., is "not disappointed in the least" about AI's progress in healthcare. "I think of it as a maturation process," he said. But can your three-year-old add a column of numbers?

I.S.K. is on the scientific advisory boards of Pulse Data and Medaware, both companies involved in predictive analytics. S.S. is a founder of, and holds equity in, Bayesian Health. The results of the study discussed in this publication could affect the value of Bayesian Health. This arrangement has been reviewed and approved by Johns Hopkins University in accordance with its conflict-of-interest policies. S.S. is a member of the scientific advisory board for PatientPing.