title: Rule base system for identification of patients with specific critical care syndromes: The "sniffer" for acute lung injury.
abstract: Early detection of specific critical care syndromes, such as sepsis or acute lung injury (ALI)is essential for timely implementation of evidence based therapies. Using a near-real time copy of the electronic medical records ("ICU data mart") we developed and validated custom electronic alert (ALI"sniffer") in a cohort of 485 critically ill medical patients. Compared with the gold standard of prospective screening, ALI "sniffer" demonstrated good sensitivity, 93% (95% CI 90 to 95) and specificity, 90% (95% CI 87 to 92). It is not known if the bedside implementation of ALI "sniffer" will improve the adherence to evidence-based therapies and outcome of patients with ALI.
authors.affiliation: Mayo Clinic College of Medicine, Rochester, MN, USA.
authors.forename: V
authors.initials: V
authors.lastname: Herasevich
authors.forename: M
authors.initials: M
authors.lastname: Yilmaz
authors.forename: H
authors.initials: H
authors.lastname: Khan
authors.forename: C G
authors.initials: CG
authors.lastname: Chute
authors.forename: O
authors.initials: O
authors.lastname: Gajic
mesh_terms: D003422:Critical Care; D016638:Critical Illness; D006801:Humans; D016347:Medical Records Systems, Computerized; D017010:Reminder Systems; D012128:Respiratory Distress Syndrome / Q000175:diagnosis*; D012680:Sensitivity and Specificity; D013813:Therapy, Computer-Assisted