A Laboratory-Based, Hospital-Wide, Electronic Marker for Nosocomial Infection

Abstract

Faced with expectations to improve patient safety and contain costs, the US health care system is under increasing pressure to comprehensively and objectively account for nosocomial infections. Widely accepted nosocomial infection surveillance methods, however, are limited in scope, not sensitive, and applied inconsistently. In 907 inpatient admissions to Evanston Northwestern Healthcare hospitals (Evanston, IL), nosocomial infection identification by the Nosocomial Infection Marker (MedMined, Birmingham, AL), an electronic, laboratory-based marker, was compared with hospital-wide nosocomial infection detection by medical records review and established nosocomial infection detection methods. The sensitivity and specificity of marker analysis were 0.86 (95% confidence interval [CI 95], 0.76-0.96) and 0.984 (CI 95, 0.976, 0.992). Marker analysis also identified 11 intensive care unit-associated nosocomial infections (sensitivity, 1.0; specificity, 0.986). Nosocomial Infection Marker analysis had a comparable sensitivity (P > .3) to and lower specificity (P < .001) than medical records review. It is important to note that marker analysis statistically outperformed widely accepted surveillance methods, including hospital-wide detection by Study on the Efficacy of Nosocomial Infection Control chart review and intensive care unit detection by National Nosocomial Infections Surveillance techniques.

Nosocomial Infections and their Surveillance in Veterinary Hospitals

“…The Surveillance system used in human health care centres includes laboratory diagnosis (Emori and Gaynes, 1993;Brossette et al, 2006). Many researchers in veterinary nosocomial infections also included laboratory diagnosis for confirmation (Biertuempfel et al, 1981;Mathews et al, 1996;Lobetti et al, 2002;Smarick et al, 2004;Marsh-Ng et al, 2007;Bubenik and Hosgood, 2008;Jones et al, 2009) and some researchers have not included laboratory confirmation (Nicholson, 2002;Eugster et al, 2004;Ahern et al, 2010).…”

Incidence rates of hospital-acquired urinary tract and bloodstream infections generated by automated compilation of electronically available healthcare data

“…6,12,18,23 As highlighted by Venable and Dissanaike, an electronically defined algorithm would increase reliability and reduce the variation between PPS observers. 18 Differences between potentially subjective judgements and an objective evaluation of infections in patients may also explain discrepancies seen in the present comparison of the PPSs and HAIR, e.g.…”

Reducing Hospital-Acquired Infections Among the Neurologically Critically Ill

“…This automated, algorithm-driven approach allows for identification of hospital-acquired infections without requiring systematic chart review [10,11], and has been shown to be more accurate than administrative data. Case identification begins with microbiology laboratory findings; excludes (a) infections present on admission, (b) organisms usually present as a result of contamination, and (c) duplicate specimens; and has been validated particularly as a measure of urinary and pulmonary infections.…”