180510 Integrating the Electronic Laboratory Reporting of Methicillin-resistant Staphylococcus aureus (MRSA) Data

Sunday, October 26, 2008

Nikolay Lipskiy, PhD , Depr, CDC, NCPHI, Atlanta, GA
Jerome Tokars, MD, MPH , Division of Emergency Preparedness and Response, National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, GA
Roseanne English , Division of Emergency Preparedness and Response, National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, GA
Scott J. N. McNabb, PhD , Ncphi, DISSS, CDC, Atlanta, GA
John Abellera, MPH , Ncphi, Disss, CDC, Atlanta, GA
The development of algorithms for integrating ELR of MRSA can improve public health surveillance; reduce the burden on clinical, laboratory, and public health partners; and enhance public health action. The ELR from BioSense, as well as from national commercial ELR systems, can help develop and evaluate MRSA ELR algorithms.

Our objective was to examine variability among MRSA results in ELR systems from laboratories supplying data to BioSense and define algorithms for the integration of MRSA ELR data from hospitals and national commercial laboratory for case reporting to public health.

We analyzed ELR messages from more than 263,000 patients from 30 BioSense hospital data suppliers between 03/2004 and 12/2007 and more than 3,300,000 patient records from the national laboratory during 08/2007.

MRSA ELR results were reported in free-text format by eight hospital laboratories. The remaining 22 hospital sources and the national ELR sources reported results in coded format. We found 78.1% (1,684) MRSA ELR results were reported in coded elements. Accurate test names from MRSA patients were reported from 28 hospital laboratories (93.3%) and from the national laboratory. Local codes (coding format) for ELR, as well as targeted MRSA descriptors for free text format, were the most reliable elements of MRSA ELR.

We classified types of tests and responses associated with positive MRSA ELR findings, and developed an algorithm for the integration of incoming MRSA ELR results. Further work on the development of algorithms for integrating various ELR data sources will improve the public health reporting and follow-up of MRSA.

Learning Objectives:
Identify the need for the MRSA laboratory surveillance Describe the basic mechanisms of MRSA laboratory data collection and management Describe strategies for integration of MRSA findings from hospital and commercial laboratories

Keywords: Communicable Disease, Information Technology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am CDC scientist
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.