| Using natural language processing to improve accuracy of automated notifiable disease reporting. | |
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MedLine Citation:
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PMID: 18999177 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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Jeff Friedlin; Shaun Grannis; J Marc Overhage |
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Publication Detail:
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Type: Journal Article Date: 2008-11-06 |
Journal Detail:
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Title: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium Volume: - ISSN: 1942-597X ISO Abbreviation: - Publication Date: 2008 |
Date Detail:
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Created Date: 2008-11-12 Completed Date: 2010-01-08 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101209213 Medline TA: AMIA Annu Symp Proc Country: United States |
Other Details:
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Languages: eng Pagination: 207-11 Citation Subset: IM |
Affiliation:
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Regenstrief Institute, Inc, Indianapolis, IN, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Artificial Intelligence* Disease Notification / methods* Documentation / methods* Indiana Medical Records Systems, Computerized / organization & administration* Natural Language Processing* Writing* |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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