| An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records. | |
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MedLine Citation:
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PMID: 20688191 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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We describe a two-stage analytical approach for characterizing morbidity profile dissimilarity among patient cohorts using electronic medical records. We capture morbidities using the International Statistical Classification of Diseases and Related Health Problems (ICD-9) codes. In the first stage of the approach separate logistic regression analyses for ICD-9 sections (e.g., "hypertensive disease" or "appendicitis") are conducted, and the odds ratios that describe adjusted differences in prevalence between two cohorts are displayed graphically. In the second stage, the results from ICD-9 section analyses are combined into a general morbidity dissimilarity index (MDI). For illustration, we examine nine cohorts of patients representing six phenotypes (or controls) derived from five institutions, each a participant in the electronic MEdical REcords and GEnomics (eMERGE) network. The phenotypes studied include type II diabetes and type II diabetes controls, peripheral arterial disease and peripheral arterial disease controls, normal cardiac conduction as measured by electrocardiography, and senile cataracts. |
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Authors:
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Jonathan S Schildcrout; Melissa A Basford; Jill M Pulley; Daniel R Masys; Dan M Roden; Deede Wang; Christopher G Chute; Iftikhar J Kullo; David Carrell; Peggy Peissig; Abel Kho; Joshua C Denny |
Publication Detail:
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Type: Journal Article Date: 2010-08-03 |
Journal Detail:
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Title: Journal of biomedical informatics Volume: 43 ISSN: 1532-0480 ISO Abbreviation: J Biomed Inform Publication Date: 2010 Dec |
Date Detail:
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Created Date: 2010-11-24 Completed Date: 2011-03-18 Revised Date: 2011-12-21 |
Medline Journal Info:
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Nlm Unique ID: 100970413 Medline TA: J Biomed Inform Country: United States |
Other Details:
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Languages: eng Pagination: 914-23 Citation Subset: IM |
Copyright Information:
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Copyright © 2010 Elsevier Inc. All rights reserved. |
Affiliation:
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Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232-2156, USA. jonathan.schildcrout@vanderbilt.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Cohort Studies Diabetes Mellitus, Type 2 / epidemiology Electronic Health Records* Humans International Classification of Diseases Morbidity* Peripheral Arterial Disease / epidemiology Phenotype Prevalence United States |
| Grant Support | |
ID/Acronym/Agency:
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U01 HG004603-03/HG/NHGRI NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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