Details:

Alternative Title:
BMC Med Inform Decis Mak
Publisher's site:
http://dx.doi.org/10.1186/1472-6947-12-34
Personal Author:
Jones, Makoto ; DuVall, Scott L ; Spuhl, Joshua ; Samore, Matthew H ; Nielson, Christopher ; ... More +
Jones, Makoto ; DuVall, Scott L ; Spuhl, Joshua ; Samore, Matthew H ; Nielson, Christopher ; Rubin, Michael ; Less -
Description:
Background Accurate information is needed to direct healthcare systems’ efforts to control methicillin-resistant Staphylococcus aureus (MRSA). Assembling complete and correct microbiology data is vital to understanding and addressing the multiple drug-resistant organisms in our hospitals. Methods Herein, we describe a system that securely gathers microbiology data from the Department of Veterans Affairs (VA) network of databases. Using natural language processing methods, we applied an information extraction process to extract organisms and susceptibilities from the free-text data. We then validated the extraction against independently derived electronic data and expert annotation. Results We estimate that the collected microbiology data are 98.5% complete and that methicillin-resistant Staphylococcus aureus was extracted accurately 99.7% of the time. Conclusions Applying natural language processing methods to microbiology records appears to be a promising way to extract accurate and useful nosocomial pathogen surveillance data. Both scientific inquiry and the data’s reliability will be dependent on the surveillance system’s capability to compare from multiple sources and circumvent systematic error. The dataset constructed and methods used for this investigation could contribute to a comprehensive infectious disease surveillance system or other pressing needs.
Subject:
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Algorithms
Bias (Epidemiology)
Hospitals, Veterans
Humans
Information Storage And Retrieval
Internet
Medical Records Systems, Computerized
Methicillin-Resistant Staphylococcus Aureus
Microbiological Techniques
Natural Language Processing
Population Surveillance
Quality Control
Reference Standards
Reproducibility Of Results
Research Article
Staphylococcal Infections

Source:
BMC Med Inform Decis Mak. 2012; 12:34.
Pubmed ID:
22533507
Pubmed Central ID:
PMC3394221
Document Type:
Journal Article ;
Funding:
07FED706504/PHS HHS/United States ; 5U01CI000334/CI/NCPDCID CDC HHS/United States ; UL1 RR024153/RR/NCRR NIH HHS/United States ; UL1 TR000005/TR/NCATS NIH HHS/United States ;
07FED706504/PHS HHS/United States ; 5U01CI000334/CI/NCPDCID CDC HHS/United States ; UL1 RR024153/RR/NCRR NIH HHS/United States ; UL1 TR000005/TR/NCATS NIH HHS/United States ; Less -
Name as Subject:
United States. Department of Veterans Affairs. ;
Place as Subject:
United States ;
Collection(s):
CDC Public Access
Main Document Checksum:
[+]
urn:sha256:eef3021b99869db24b3827e7721b7a79f700b2f8bac8c341e934db5b3cb608ce
File Type:

Supporting Files

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