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Rochester Epidemiology Project Data Exploration Portal

INTRODUCTION: The goal of this project was to develop an interactive, web-based tool to explore patterns of prevalence and co-occurrence of diseases using data from the expanded Rochester Epidemiology Project (E-REP) medical records-linkage system. METHODS: We designed the REP Data Exploration Porta...

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Autores principales: St. Sauver, Jennifer L., Grossardt, Brandon R., Finney Rutten, Lila J., Roger, Veronique L., Majerus, Michelle, Jensen, Daniel W., Brue, Scott M., Bock-Goodner, Cynthia M., Rocca, Walter A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912927/
https://www.ncbi.nlm.nih.gov/pubmed/29654640
http://dx.doi.org/10.5888/pcd15.170242
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author St. Sauver, Jennifer L.
Grossardt, Brandon R.
Finney Rutten, Lila J.
Roger, Veronique L.
Majerus, Michelle
Jensen, Daniel W.
Brue, Scott M.
Bock-Goodner, Cynthia M.
Rocca, Walter A.
author_facet St. Sauver, Jennifer L.
Grossardt, Brandon R.
Finney Rutten, Lila J.
Roger, Veronique L.
Majerus, Michelle
Jensen, Daniel W.
Brue, Scott M.
Bock-Goodner, Cynthia M.
Rocca, Walter A.
author_sort St. Sauver, Jennifer L.
collection PubMed
description INTRODUCTION: The goal of this project was to develop an interactive, web-based tool to explore patterns of prevalence and co-occurrence of diseases using data from the expanded Rochester Epidemiology Project (E-REP) medical records-linkage system. METHODS: We designed the REP Data Exploration Portal (REP DEP) to include summary information for people who lived in a 27-county region of southern Minnesota and western Wisconsin on January 1, 2014 (n = 694,506; 61% of the entire population). We obtained diagnostic codes of the International Classification of Diseases, 9th edition, from the medical records-linkage system in 2009 through 2013 (5 years) and grouped them into 717 disease categories. For each condition or combination of 2 conditions (dyad), we calculated prevalence by dividing the number of persons with a specified condition (numerator) by the total number of persons in the population (denominator). We calculated observed-to-expected ratios (OERs) to test whether 2 conditions co-occur more frequently than would co-occur as a result of chance alone. RESULTS: We launched the first version of the REP DEP in May 2017. The REP DEP can be accessed at http://rochesterproject.org/portal/. Users can select 2 conditions of interest, and the REP DEP displays the overall prevalence, age-specific prevalence, and sex-specific prevalence for each condition and dyad. Also displayed are OERs overall and by age and sex and maps of county-specific prevalence of each condition and OER. CONCLUSION: The REP DEP draws upon a medical records-linkage system to provide an innovative, rapid, interactive, free-of-charge method to examine the prevalence and co-occurrence of 717 diseases and conditions in a geographically defined population.
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spelling pubmed-59129272018-05-01 Rochester Epidemiology Project Data Exploration Portal St. Sauver, Jennifer L. Grossardt, Brandon R. Finney Rutten, Lila J. Roger, Veronique L. Majerus, Michelle Jensen, Daniel W. Brue, Scott M. Bock-Goodner, Cynthia M. Rocca, Walter A. Prev Chronic Dis Original Research INTRODUCTION: The goal of this project was to develop an interactive, web-based tool to explore patterns of prevalence and co-occurrence of diseases using data from the expanded Rochester Epidemiology Project (E-REP) medical records-linkage system. METHODS: We designed the REP Data Exploration Portal (REP DEP) to include summary information for people who lived in a 27-county region of southern Minnesota and western Wisconsin on January 1, 2014 (n = 694,506; 61% of the entire population). We obtained diagnostic codes of the International Classification of Diseases, 9th edition, from the medical records-linkage system in 2009 through 2013 (5 years) and grouped them into 717 disease categories. For each condition or combination of 2 conditions (dyad), we calculated prevalence by dividing the number of persons with a specified condition (numerator) by the total number of persons in the population (denominator). We calculated observed-to-expected ratios (OERs) to test whether 2 conditions co-occur more frequently than would co-occur as a result of chance alone. RESULTS: We launched the first version of the REP DEP in May 2017. The REP DEP can be accessed at http://rochesterproject.org/portal/. Users can select 2 conditions of interest, and the REP DEP displays the overall prevalence, age-specific prevalence, and sex-specific prevalence for each condition and dyad. Also displayed are OERs overall and by age and sex and maps of county-specific prevalence of each condition and OER. CONCLUSION: The REP DEP draws upon a medical records-linkage system to provide an innovative, rapid, interactive, free-of-charge method to examine the prevalence and co-occurrence of 717 diseases and conditions in a geographically defined population. Centers for Disease Control and Prevention 2018-04-12 /pmc/articles/PMC5912927/ /pubmed/29654640 http://dx.doi.org/10.5888/pcd15.170242 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Original Research
St. Sauver, Jennifer L.
Grossardt, Brandon R.
Finney Rutten, Lila J.
Roger, Veronique L.
Majerus, Michelle
Jensen, Daniel W.
Brue, Scott M.
Bock-Goodner, Cynthia M.
Rocca, Walter A.
Rochester Epidemiology Project Data Exploration Portal
title Rochester Epidemiology Project Data Exploration Portal
title_full Rochester Epidemiology Project Data Exploration Portal
title_fullStr Rochester Epidemiology Project Data Exploration Portal
title_full_unstemmed Rochester Epidemiology Project Data Exploration Portal
title_short Rochester Epidemiology Project Data Exploration Portal
title_sort rochester epidemiology project data exploration portal
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912927/
https://www.ncbi.nlm.nih.gov/pubmed/29654640
http://dx.doi.org/10.5888/pcd15.170242
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