Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1782231053920894976 |
---|---|
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. |
format | Online Article Text |
id | pubmed-3337270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT lependupaea annotationanalysisfortestingdrugsafetysignalsusingunstructuredclinicalnotes AT iyersrinivasanv annotationanalysisfortestingdrugsafetysignalsusingunstructuredclinicalnotes AT faironcedrick annotationanalysisfortestingdrugsafetysignalsusingunstructuredclinicalnotes AT shahnigamh annotationanalysisfortestingdrugsafetysignalsusingunstructuredclinicalnotes |