Data from: Sepsis surveillance: an examination of parameter sensitivity and alert reliability

Objective: To examine performance of a sepsis surveillance system in a
simulated environment where modifications to parameters and settings for
identification of at-risk patients can be explored in-depth. Materials and
Methods: This was a multiple center observational cohort study. The study
population comprised 14 917 adults hospitalized in 2016. An expert-driven
rules algorithm was applied against 15.1 million data points to simulate a
system with binary notification of sepsis events. Three system scenarios
were examined: a scenario as derived from the second version of the
Consensus Definitions for Sepsis and Septic Shock (SEP-2), the same
scenario but without systolic blood pressure (SBP) decrease criteria (near
SEP-2), and a conservative scenario with limited parameters. Patients
identified by scenarios as being at-risk for sepsis were assessed for
suspected infection. Multivariate binary logistic regression models
estimated mortality risk among patients with suspected infection. Results:
First, the SEP-2-based scenario had a hyperactive, unreliable parameter
SBP decrease >40 mm Hg from baseline. Second, the near SEP-2
scenario demonstrated adequate reliability and sensitivity. Third, the
conservative scenario had modestly higher reliability, but sensitivity
degraded quickly. Parameters differed in predicting mortality risk and
represented a substitution effect between scenarios. Discussion:
Configuration of parameters and alert criteria have implications for
patient identification and predicted outcomes. Conclusion: Performance of
scenarios was associated with scenario design. A single hyperactive,
unreliable parameter may negatively influence adoption of the system. A
trade-off between modest improvements in alert reliability corresponded to
a steep decline in condition sensitivity in scenarios explored.