Cerner, a provider of healthcare technology, is putting big data and analytics to work to get a more complete picture of people's health and predict potentially life-threatening risks.
Cerner's Enterprise Data Hub, which uses a big data platform from Cloudera, brings together data from an almost unlimited number of sources. By analyzing the petabytes of data available to them, data scientists can better understand patients, conditions or trends.
They're now better able to determine, for example, the probability of a bloodstream infection, such as the early onset of sepsis. Cerner developed what it calls the St. John sepsis agent, a tool that uses an algorithmic approach to detect cases of the infection. It's deployed in a cloud-hosted production system that actively monitors more than 1 million patients daily, says Bharat Sutariya, vice president and chief medical officer of population health at Cerner.
The system generates alerts that are integrated into the daily workflow of care providers, enabling them to take immediate action upon detection.
"The results have been nothing less than remarkable," Sutariya says. "The enterprise data hub handles scalability and heterogeneous data in near real time. With these capabilities today, we've helped clients achieve results, such as reducing sepsis mortality by 21%."
This story, "Cerner" was originally published by Computerworld.