Linked Life Data

18693874

Source:http://linkedlifedata.com/resource/pubmed/id/18693874

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-8-12
pubmed:abstractText
Free text fields are often used to store clinical drug data in electronic health records. The use of free text facilitates rapid data entry by the clinician. Errors in spelling, abbreviations, and jargon, however, limit the utility of these data. We designed and implemented an algorithm, using open source tools and RxNorm, to extract and normalize drug data stored in free text fields of an anesthesia electronic health record. The algorithm was developed using a training set containing drug data from 49,518 cases, and validated using a validation set containing data from 14,655 cases. Overall sensitivity and specificity for the validation set were 92.2% and 95.7% respectively. The mains sources of error were misspellings and unknown but valid drug names. These preliminary results demonstrate that free text clinical drug data can be efficiently extracted and mapped to a controlled drug nomenclature.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1942-597X
pubmed:author
pubmed:issnType
Electronic
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
438-42
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Extraction and mapping of drug names from free text to a standardized nomenclature.
pubmed:affiliation
Department of Anesthesiology, Mount Sinai School of Medicine, New York, NY, USA.
pubmed:publicationType
Journal Article, Validation Studies