Document Detail

Using natural language processing to improve accuracy of automated notifiable disease reporting.
MedLine Citation:
PMID:  18999177     Owner:  NLM     Status:  MEDLINE    
We examined whether using a natural language processing (NLP) system results in improved accuracy and completeness of automated electronic laboratory reporting (ELR) of notifiable conditions. We used data from a community-wide health information exchange that has automated ELR functionality. We focused on methicillin-resistant Staphylococcus Aureus (MRSA), a reportable infection found in unstructured, free-text culture result reports. We used the Regenstrief EXtraction tool (REX) for this work. REX processed 64,554 reports that mentioned MRSA and we compared its output to a gold standard (human review). REX correctly identified 39,491(99.96%) of the 39,508 reports positive for MRSA, and committed only 74 false positive errors. It achieved high sensitivity, specificity, positive predicted value and F-measure. REX identified over two times as many MRSA positive reports as the ELR system without NLP. Using NLP can improve the completeness and accuracy of automated ELR.
Jeff Friedlin; Shaun Grannis; J Marc Overhage
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Publication Detail:
Type:  Journal Article     Date:  2008-11-06
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  -     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2008  
Date Detail:
Created Date:  2008-11-12     Completed Date:  2010-01-08     Revised Date:  2013-06-04    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  207-11     Citation Subset:  IM    
Regenstrief Institute, Inc, Indianapolis, IN, USA.
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MeSH Terms
Artificial Intelligence*
Disease Notification / methods*
Documentation / methods*
Medical Records Systems, Computerized / organization & administration*
Natural Language Processing*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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