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Big Data Used to Predict Sepsis in NICU Newborns

June 10, 2014
by Gabriel Perna
| Reprints

Kaiser Permanente’s neonatal intensive care unit (NICU) doctors have begun using big data techniques to determine if newborn babies are at risk for sepsis.

The Oakland-based integrated care provider’s Division of Research has provided the NICU docs with an online calculator for analysis. Doctors can enter the gestational age, the highest maternal antepartum temperature, rupture of membranes (ROM) in hours, and other information related to the pregnancy and it will come up with a probability per 1,000 babies of sepsis in a newborn. The calculator uses years of information on the vital signs of mothers and babies who develop sepsis.

“Prior to the online sepsis calculator, a maternal fever of 100.4 or higher meant a trip to the NICU regardless of how a baby looked, or other risk factors. That meant separating the mother and baby, starting an IV, and putting the infant on intravenous antibiotics," stated research scientist Michael Kuzniewicz, M.D., MPH, in an interview on Kaiser Permanente’s website. “Now we can be smarter on which babies we identify to evaluate and treat for infection.”

“Now we can be smarter on which babies we identify to evaluate and treat for infection, - See more at:
“Now we can be smarter on which babies we identify to evaluate and treat for infection, - See more at:

Kaiser’s not the only provider organization that is using patient data algorithms to predict sepsis. Researchers at UC Davis Medical Center found that routine data found in an electronic health record (EHR) of a hospitalized patient can be used to reduce the risk of sepsis. Elsewhere in Kaiser, the organization is using big data sets to identify strategies for reduction of bowel infections in preterm infants, reduce the number of days spent in the NICU, and have fewer blood-stream infections associated with central intravenous lines.


neonatal intensive care units
neonatal intensive care units
neonatal intensive care units

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