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Annotation analysis for testing drug safety signals using unstructured clinical notes

BACKGROUND: The electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text of clinical notes and is not gathered into centralized repositories. With the i...

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Detalles Bibliográficos
Autores principales: LePendu, Paea, Iyer, Srinivasan V, Fairon, Cédrick, Shah, Nigam H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3337270/
https://www.ncbi.nlm.nih.gov/pubmed/22541596
http://dx.doi.org/10.1186/2041-1480-3-S1-S5
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author LePendu, Paea
Iyer, Srinivasan V
Fairon, Cédrick
Shah, Nigam H
author_facet LePendu, Paea
Iyer, Srinivasan V
Fairon, Cédrick
Shah, Nigam H
author_sort LePendu, Paea
collection PubMed
description BACKGROUND: The electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text of clinical notes and is not gathered into centralized repositories. With the increasing access to large volumes of electronic medical data—in particular the clinical notes—it may be possible to computationally encode and to test drug safety signals in an active manner. RESULTS: We describe the application of simple annotation tools on clinical text and the mining of the resulting annotations to compute the risk of getting a myocardial infarction for patients with rheumatoid arthritis that take Vioxx. Our analysis clearly reveals elevated risks for myocardial infarction in rheumatoid arthritis patients taking Vioxx (odds ratio 2.06) before 2005. CONCLUSIONS: Our results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records.
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spelling pubmed-33372702012-04-26 Annotation analysis for testing drug safety signals using unstructured clinical notes LePendu, Paea Iyer, Srinivasan V Fairon, Cédrick Shah, Nigam H J Biomed Semantics Proceedings BACKGROUND: The electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text of clinical notes and is not gathered into centralized repositories. With the increasing access to large volumes of electronic medical data—in particular the clinical notes—it may be possible to computationally encode and to test drug safety signals in an active manner. RESULTS: We describe the application of simple annotation tools on clinical text and the mining of the resulting annotations to compute the risk of getting a myocardial infarction for patients with rheumatoid arthritis that take Vioxx. Our analysis clearly reveals elevated risks for myocardial infarction in rheumatoid arthritis patients taking Vioxx (odds ratio 2.06) before 2005. CONCLUSIONS: Our results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records. BioMed Central 2012-04-24 /pmc/articles/PMC3337270/ /pubmed/22541596 http://dx.doi.org/10.1186/2041-1480-3-S1-S5 Text en Copyright ©2012 LePendu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
LePendu, Paea
Iyer, Srinivasan V
Fairon, Cédrick
Shah, Nigam H
Annotation analysis for testing drug safety signals using unstructured clinical notes
title Annotation analysis for testing drug safety signals using unstructured clinical notes
title_full Annotation analysis for testing drug safety signals using unstructured clinical notes
title_fullStr Annotation analysis for testing drug safety signals using unstructured clinical notes
title_full_unstemmed Annotation analysis for testing drug safety signals using unstructured clinical notes
title_short Annotation analysis for testing drug safety signals using unstructured clinical notes
title_sort annotation analysis for testing drug safety signals using unstructured clinical notes
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3337270/
https://www.ncbi.nlm.nih.gov/pubmed/22541596
http://dx.doi.org/10.1186/2041-1480-3-S1-S5
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