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Electronic Surveillance for Infectious Disease Trend Analysis following a Quality Improvement Intervention

Published online by Cambridge University Press:  02 January 2015

Kari E. Peterson ,
Donna M. Hacek ,
Ari Robicsek ,
Richard B. Thomson Jr  and
Lance R. Peterson
Kari E. Peterson
Affiliation:
Department of Laboratory Medicine and Pathology, Division of Microbiology, NorthShore University HealthSystem, Evanston, Illinois
Donna M. Hacek
Affiliation:
Department of Laboratory Medicine and Pathology, Division of Microbiology, NorthShore University HealthSystem, Evanston, Illinois
Ari Robicsek
Affiliation:
Department of Medicine, Division of Infection Diseases, NorthShore University HealthSystem, Evanston, Illinois University of Chicago, Chicago, Illinois
Richard B. Thomson Jr
Affiliation:
Department of Laboratory Medicine and Pathology, Division of Microbiology, NorthShore University HealthSystem, Evanston, Illinois University of Chicago, Chicago, Illinois
Lance R. Peterson*
Affiliation:
Department of Laboratory Medicine and Pathology, Division of Microbiology, NorthShore University HealthSystem, Evanston, Illinois Department of Medicine, Division of Infection Diseases, NorthShore University HealthSystem, Evanston, Illinois University of Chicago, Chicago, Illinois
*
Department of Pathology and Laboratory Medicine, NorthShore University HealthSystem, Walgreen SB 525, 2650 Ridge Avenue, Evanston, IL 60201 (lancel@uchicago.edu)
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Abstract

Objective.

Interventions for reducing methicillin-resistant Staphylococcus aureus (MRSA) healthcare-associated disease require outcome assessment; this is typically done by manual chart review to determine infection, which can be labor intensive. The purpose of this study was to validate electronic tools for MRSA healthcare-associated infection (HAI) trending that can replace manual medical record review.

Design and Setting.

This was an observational study comparing manual medical record review with 3 electronic methods: raw culture data from the laboratory information system (LIS) in use by our healthcare organization, LIS data combined with admission-discharge-transfer (ADT) data to determine which cultures were healthcare associated (LIS + ADT), and the CareFusion MedMined Nosocomial Infection Marker (NIM). Each method was used for the same 7-year period from August 2003 through July 2010.

Patients.

The data set was from a 3-hospital organization covering 342,492 admissions.

Results.

Correlation coefficients for raw LIS, LIS + ADT, and NIM were 0.976, 0.957, and 0.953, respectively, when assessed on an annual basis. Quarterly performance for disease trending was also good, with R2 values exceeding 0.7 for all methods.

Conclusions.

The electronic tools accurately identified trends in MRSA HAI incidence density when all infections were combined as quarterly or annual data; the performance is excellent when annual assessment is done. These electronic surveillance systems can significantly reduce (93% [in-house-developed program] to more than 99.9999% [commercially available systems]) the personnel resources needed to monitor the impact of a disease control program.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 33 , Issue 8 , August 2012 , pp. 790 - 795
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2012

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