Improving Sepsis Diagnosis and Reducing Cost with Big Data

Sepsis is one of the leading causes of hospital readmissions and death in the United States, impacting some 750,000 patients per year at a cost of $16.7 billion annually to the healthcare system. Reducing the impact of sepsis cases even slightly would significantly enhance patient outcomes and reduce unnecessary expenses.

While the understanding and treatment of sepsis is improving, early detection and diagnosis of the condition continues to be an issue. In the above video, see how Cerner developed  a solution to the sepsis challenge – the St. John Sepsis Agent, which uses Intel technology and to date has helped save more than 2,700 lives by identifying sepsis in the early stages. According to Cerner, organizations can achieve $5,882 in medical savings per treated patient, a 21 percent reduction in length of stay, and a 24 percent reduction in in-hospital patient mortality rates by implementing the St. John’s Sepsis Agent.

Also in the case study video, see how Cerner aggregates big data and utilizes analytics to enable population health, and how Intel and Cloudera allow Cerner to provide a technology platform to support massive amounts of storage capacity, scalable parallel processing with near real-time alerts,  as well as high levels of security.

How is your organization using big data to enable population health?

 

by Steve Leibforth, Intel Americas

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