Evidence map›Paper›PMID 23602781›Full record

ReviewJournal of biomedical informatics2013

Using chief complaints for syndromic surveillance: a review of chief complaint based classifiers in North America.

Mike Conway, John N Dowling, Wendy W Chapman

Open access · greenAbstract readReview
In one paragraph

Review in Journal of biomedical informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
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  15. Coding Free-Text Chief Complaints from a Health Information Exchange: A Preliminary Study.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020
    Article
  16. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Mike ConwayDivision of Biomedical Informatics, University of California, San Diego, 9500 Gilman Dr. MC 0505 La Jolla, California 92093, USA. mconway@ucsd.edu
John N Dowling
Wendy W Chapman
University of California San Diego · USUniversity of Pittsburgh · US

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR000005 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$50.8M
NLP Foundational Studies & Ontologies for Syndromic Surveillance from ED ReportsR01LM009427 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHAPMAN, WENDY W. · 2007 to 2009
$1.4M
Natural Language Processing for Respiratory SurveillanceK22LM008301 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHAPMAN, WENDY W. · 2004 to 2006
$459k
NCATS NIH HHS UL1 TR000005NLM NIH HHS K22 LM008301NLM NIH HHS K22LM008301NLM NIH HHS R01 LM009427NLM NIH HHS R01LM009427
6 · The paper itself

Abstract

A major goal of Natural Language Processing in the public health informatics domain is the automatic extraction and encoding of data stored in free text patient records. This extracted data can then be utilized by computerized systems to perform syndromic surveillance. In particular, the chief complaint--a short string that describes a patient's symptoms--has come to be a vital resource for syndromic surveillance in the North American context due to its near ubiquity. This paper reviews fifteen systems in North America--at the city, county, state and federal level--that use chief complaints for syndromic surveillance.

Indexed as

Population SurveillanceHumansNorth AmericaSyndromeChief complaintsMedical language processingNatural language processingSyndromic surveillance

Identifiers

PMID23602781
PMCPMC3741452
OpenAlexW1988905434

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.