Rule base system for identification of patients with specific critical care syndromes: The "sniffer" for acute lung injury

V Herasevich; M Yilmaz; H Khan; C G Chute; O Gajic

Rule base system for identification of patients with specific critical care syndromes: The "sniffer" for acute lung injury

AMIA Annu Symp Proc. 2007 Oct 11:972.

Authors

V Herasevich¹, M Yilmaz, H Khan, C G Chute, O Gajic

Affiliation

¹ Mayo Clinic College of Medicine, Rochester, MN, USA.

PMID: 18694072

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.

Publication types

Validation Study

MeSH terms

Critical Care
Critical Illness
Humans
Medical Records Systems, Computerized*
Reminder Systems
Respiratory Distress Syndrome / diagnosis*
Sensitivity and Specificity
Therapy, Computer-Assisted*