BMC Med Inform Decis Mak - Text data extraction for a prospective, research-focused data mart: implementation and validation.

Tópicos

{ data(1714) softwar(1251) tool(1186) }
{ research(1218) medic(880) student(794) }
{ data(2317) use(1299) case(1017) }
{ search(2224) databas(1162) retriev(909) }
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{ take(945) account(800) differ(722) }
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{ featur(3375) classif(2383) classifi(1994) }
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Resumo

CKGROUND: Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of 'machine generated' sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review.METHODS: Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined.RESULTS: There was a near perfect (99.5%) agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012.CONCLUSIONS: Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor) to parse, abstract and assemble structured data from text data contained in the electronic health record. Regextractor has been successfully used to create additional data marts in other medical domains and is available to the public.

Resumo Limpo

ckground translat research typic requir data abstract medic record well data collect specif research unfortun mani data within electron health record repres text amen aggreg analys present scalabl open sourc sql server integr servic packag call regextractor includ regular express parser classic extract transform load workflow use regextractor abstract discret data textual report number machin generat sourc valid packag creat pulmonari function test data mart analyz qualiti data mart versus manual chart reviewmethod eleven variabl pulmonari function test perform closest initi clinic evalu date studi random select subject scleroderma one research assist manual review abstract enter relev data databas correl data obtain autom pulmonari function test data mart within northwestern medic enterpris data warehous determinedresult near perfect agreement result generat regextractor packag obtain via manual chart abstract pulmonari function test data mart use subsequ monitor diseas progress patient northwestern scleroderma registri addit pulmonari function test exampl present manuscript regextractor packag use creat cardiac catheter echocardiographi data mart regextractor packag releas open sourc softwar octob download time conclus collabor clinic research biomed informat expert enabl develop valid tool regextractor pars abstract assembl structur data text data contain electron health record regextractor success use creat addit data mart medic domain avail public

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