Developing the surveillance algorithm for detection of failure to recognize and treat severe sepsis.

ABSTRACT:

Objective

To develop and test an automated surveillance algorithm (sepsis "sniffer") for the detection of severe sepsis and monitoring failure to recognize and treat severe sepsis in a timely manner.

Patients and methods

We conducted an observational diagnostic performance study using independent derivation and validation cohorts from an electronic medical record database of the medical intensive care unit (ICU) of a tertiary referral center. All patients aged 18 years and older who were admitted to the medical ICU from January 1 through March 31, 2013 (N=587), were included. The criterion standard for severe sepsis/septic shock was manual review by 2 trained reviewers with a third superreviewer for cases of interobserver disagreement. Critical appraisal of false-positive an

SUBMITTER: Harrison AM 

PROVIDER: S-EPMC6571011 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature