Predicting Sepsis Risk Using the "Sniffer" Algorithm in the Electronic Medical Record.
The Sepsis "Sniffer" Algorithm (SSA) has merit as a digital sepsis alert but should be considered an adjunct to versus an alternative for the Nurse Screening Tool (NST), given lower specificity and positive predictive value. The SSA reduced the risk of incorrectly categorizing patients at low risk for sepsis, detected sepsis high risk in half the time, and reduced redundant NST screens by 70% and manual screening hours by 64% to 72%. Preserving nurse hours expended on manual sepsis alerts may translate into time directed toward other patient priorities.
Sentara CarePlex Hospital, Hampton, Virginia (Dr Olenick); Phoebe Putney Memorial Hospital, Albany, Georgia (Dr Olenick); Quality Research Institute, Clinical & Business Intelligence, Sentara Healthcare, Virginia Beach, Virginia (Dr Zimbro); and Sentara Healthcare, Virginia Beach, Virginia (Dr D'Lima and Mss Ver Schneider and Jones).
Evelyn M
EM
Olenick
Kathie S
KS
Zimbro
Gabrielle M
GM
DʼLima
Patricia
P
Ver Schneider
Danielle
D
Jones
D000465:Algorithms; D016009:Chi-Square Distribution; D003661:Decision Support Techniques; D057286:Electronic Health Records / Q000295:instrumentation / Q000592:standards*; D005544:Forecasting / Q000379:methods*; D006801:Humans; D008403:Mass Screening / Q000379:methods / Q000592:standards; D018805:Sepsis / Q000175:diagnosis* / Q000401:mortality