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

Vitaly D Herasevich, M. Yilmaz, H. Khan, C. G. Chute, Ognjen Gajic

Research output: Contribution to journalArticle

12 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)972
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2007

Fingerprint

Patient Identification Systems
Acute Lung Injury
Critical Care
Electronic Health Records
Critical Illness
Sepsis
Therapeutics

ASJC Scopus subject areas

  • Medicine(all)

Cite this

@article{0b67f84059de4c57a7651bc3b474820e,
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.",
author = "Herasevich, {Vitaly D} and M. Yilmaz and H. Khan and Chute, {C. G.} and Ognjen Gajic",
year = "2007",
language = "English (US)",
pages = "972",
journal = "AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium",
issn = "1559-4076",
publisher = "American Medical Informatics Association",

}

TY - JOUR

T1 - Rule base system for identification of patients with specific critical care syndromes

T2 - The "sniffer" for acute lung injury.

AU - Herasevich, Vitaly D

AU - Yilmaz, M.

AU - Khan, H.

AU - Chute, C. G.

AU - Gajic, Ognjen

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=56149114223&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=56149114223&partnerID=8YFLogxK

M3 - Article

C2 - 18694072

AN - SCOPUS:56149114223

SP - 972

JO - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

SN - 1559-4076

ER -