Linked Life Data

15714623

Source:http://linkedlifedata.com/resource/pubmed/id/15714623

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2005-2-15
pubmed:abstractText
This paper summarizes the experience of the Real-Time Outbreak and Disease Surveillance (RODS) project in collecting and analyzing free-text emergency department (ED) chief complaints. The technical approach involves real-time transmission of chief-complaint data as Health Level 7 messages from hospitals to a regional data center, where a Bayesian text classifier assigns each chief complaint to one of eight syndrome categories. Time-series algorithms analyze the syndrome data and generate alerts. Authorized public health users review the syndrome data by using Internet interfaces with timelines and maps. Deployments in Pennsylvania, Utah, Atlantic City, and Ohio have demonstrated feasibility of real-time collection of chief complaints. Retrospective experiments that measured case-classification accuracy demonstrated that the Bayesian classifier can discriminate between different syndrome presentations. Retrospective experiments that measured outbreak-detection accuracy determined that the classifier's performance was adequate to support accurate and timely detection of seasonal disease outbreaks. Prospective evaluation revealed that a cluster of carbon monoxide exposures was detected by RODS within 4 hours of the presentation of the first case to an emergency department.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1545-861X
pubmed:author
pubmed:issnType
Electronic
pubmed:day
24
pubmed:volume
53 Suppl
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
28-31
pubmed:dateRevised
2008-2-14
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Syndrome and outbreak detection using chief-complaint data--experience of the Real-Time Outbreak and Disease Surveillance project.
pubmed:affiliation
Real-Time Outbreak and Disease Laboratory, University of Pittsburgh, Suite 500, Cellomics Building, 500 Technology Drive, Pittsburgh, PA 15219, USA. mmw@cbmi.pitt.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't