MedEx: a medication information extraction system for clinical narratives
- 1Department of Biomedical Informatics, Vanderbilt University, School of Medicine, Nashville, Tennessee, USA
- 2Department of Medicine, Vanderbilt University, School of Medicine, Nashville, Tennessee, USA
- 3Department of Pediatrics, Vanderbilt University, School of Medicine, Nashville, Tennessee, USA
- Correspondence to Dr Hua Xu, Department of Biomedical Informatics, Vanderbilt University, 2209 Garland Ave, 412 EBL, Nashville, TN 37232, USA;
- Received 9 August 2009
- Accepted 21 October 2009
Medication information is one of the most important types of clinical data in electronic medical records. It is critical for healthcare safety and quality, as well as for clinical research that uses electronic medical record data. However, medication data are often recorded in clinical notes as free-text. As such, they are not accessible to other computerized applications that rely on coded data. We describe a new natural language processing system (MedEx), which extracts medication information from clinical notes. MedEx was initially developed using discharge summaries. An evaluation using a data set of 50 discharge summaries showed it performed well on identifying not only drug names (F-measure 93.2%), but also signature information, such as strength, route, and frequency, with F-measures of 94.5%, 93.9%, and 96.0% respectively. We then applied MedEx unchanged to outpatient clinic visit notes. It performed similarly with F-measures over 90% on a set of 25 clinic visit notes.
Funding This study was partially supported by grants from the US NIH: NHGRI U01 HG004603 and NLM R01-LM007995-05. The datasets used were obtained from Vanderbilt University Medical Center's Synthetic Derivative which is supported by institutional funding and by the Vanderbilt CTSA grant 1UL1RR024975-01 from NCRR/NIH.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.