Whole record surveillance is superior to chief complaint surveillance for predicting influenza.

Gail Welsh; Dietlind Wahner-Roedler; David Arthur Froehling; Brett Trusko; Peter Elkin

Whole record surveillance is superior to chief complaint surveillance for predicting influenza.

Gail Welsh
, Dietlind Wahner-Roedler
, David Arthur Froehling
, Brett Trusko
, Peter Elkin

Department of Biomedical Informatics

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Matched records of positive and negative influenza cases were parsed with a Natural Language Processor, the Multi-threaded Clinical Vocabulary Server (MCVS). Output was coded into SNOMED-CT reference terminology and compared to the SNOMED case definition of influenza. Odds ratios for each element of the influenza case definition by each section of the record were used to generate ROC curves. C-statistics showed that whole record surveillance was superior to chief complaint surveillance for predicting influenza.

Original language	English
Pages (from-to)	1173
Number of pages	1
Journal	AMIA Annual Symposium proceedings
State	Published - 2008

Cite this

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title = "Whole record surveillance is superior to chief complaint surveillance for predicting influenza.",

abstract = "Matched records of positive and negative influenza cases were parsed with a Natural Language Processor, the Multi-threaded Clinical Vocabulary Server (MCVS). Output was coded into SNOMED-CT reference terminology and compared to the SNOMED case definition of influenza. Odds ratios for each element of the influenza case definition by each section of the record were used to generate ROC curves. C-statistics showed that whole record surveillance was superior to chief complaint surveillance for predicting influenza.",

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AU - Welsh, Gail

AU - Wahner-Roedler, Dietlind

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AU - Trusko, Brett

AU - Elkin, Peter

PY - 2008

Y1 - 2008

N2 - Matched records of positive and negative influenza cases were parsed with a Natural Language Processor, the Multi-threaded Clinical Vocabulary Server (MCVS). Output was coded into SNOMED-CT reference terminology and compared to the SNOMED case definition of influenza. Odds ratios for each element of the influenza case definition by each section of the record were used to generate ROC curves. C-statistics showed that whole record surveillance was superior to chief complaint surveillance for predicting influenza.

AB - Matched records of positive and negative influenza cases were parsed with a Natural Language Processor, the Multi-threaded Clinical Vocabulary Server (MCVS). Output was coded into SNOMED-CT reference terminology and compared to the SNOMED case definition of influenza. Odds ratios for each element of the influenza case definition by each section of the record were used to generate ROC curves. C-statistics showed that whole record surveillance was superior to chief complaint surveillance for predicting influenza.

UR - https://www.scopus.com/pages/publications/73949096495

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AN - SCOPUS:73949096495

SN - 1942-597X

SP - 1173

JO - AMIA Annual Symposium proceedings

JF - AMIA Annual Symposium proceedings

ER -

Whole record surveillance is superior to chief complaint surveillance for predicting influenza.

Abstract

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