1. Annotation Analysis for Testing Drug Safety Signals using Unstructured Clinical Notes
- Author
-
LePendu, Paea, Iyer, Srinivasan V, Fairon, Cédrick, and Shah, Nigam H
- Subjects
Information and Computing Sciences ,Heart Disease - Coronary Heart Disease ,Patient Safety ,Networking and Information Technology R&D (NITRD) ,Cardiovascular ,Arthritis ,Autoimmune Disease ,Heart Disease ,5.1 Pharmaceuticals ,Development of treatments and therapeutic interventions ,Inflammatory and immune system ,Good Health and Well Being ,Other Biological Sciences ,Artificial Intelligence and Image Processing ,Information Systems ,Information and computing sciences - Abstract
BackgroundThe 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.ResultsWe 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.ConclusionsOur results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records.
- Published
- 2012