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This article is part of the supplement: Proceedings of the Bio-Ontologies Special Interest Group 2011

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Annotation Analysis for Testing Drug Safety Signals using Unstructured Clinical Notes

Paea LePendu1*, Srinivasan V Iyer1, Cédrick Fairon2 and Nigam H Shah1

Author Affiliations

1 Stanford Center for Biomedical Informatics Research, Stanford University, USA

2 Institut Langage et Communication, Centre de traitement automatique du langage, Université catholique de Louvain, Belgium

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Journal of Biomedical Semantics 2012, 3(Suppl 1):S5  doi:10.1186/2041-1480-3-S1-S5

Published: 24 April 2012



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.


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.


Our results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records.