Identification of pneumonia and influenza deaths using the Death Certificate Pipeline.

BMC Medical Informatics and Decision Making
Kailah DavisJulio C Facelli

Abstract

Death records are a rich source of data, which can be used to assist with public surveillance and/or decision support. However, to use this type of data for such purposes it has to be transformed into a coded format to make it computable. Because the cause of death in the certificates is reported as free text, encoding the data is currently the single largest barrier of using death certificates for surveillance. Therefore, the purpose of this study was to demonstrate the feasibility of using a pipeline, composed of a detection rule and a natural language processor, for the real time encoding of death certificates using the identification of pneumonia and influenza cases as an example and demonstrating that its accuracy is comparable to existing methods. A Death Certificates Pipeline (DCP) was developed to automatically code death certificates and identify pneumonia and influenza cases. The pipeline used MetaMap to code death certificates from the Utah Department of Health for the year 2008. The output of MetaMap was then accessed by detection rules which flagged pneumonia and influenza cases based on the Centers of Disease and Control and Prevention (CDC) case definition. The output from the DCP was compared with the current me...Continue Reading

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Citations

Feb 14, 2014·American Journal of Epidemiology·Eric M Ossiander
Jun 15, 2014·Journal of the American Medical Informatics Association : JAMIA·David A HanauerNaren Ramakrishnan
Sep 2, 2015·International Journal of Medical Informatics·Bevan KoopmanNarelle Grayson
Jul 16, 2015·BMC Medical Informatics and Decision Making·Bevan KoopmanSarah Thackway
May 21, 2016·PloS One·Calvin LamMin-Huey Chung

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Software Mentioned

MICAR
GSPELL
PERL script
Super
MICAR200
Mortality Medical Data System ( MMDS )
UMLS SL
ASPELL
MMDS
SuperMICAR

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