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AMIA Summits Transl Sci Proc. 2012; 2012: 63–70.
Published online Mar 19, 2012.
PMCID: PMC3392046
Analyzing Patterns of Drug Use in Clinical Notes for Patient Safety
Paea LePendu, Yi Liu, Srinivasan Iyer, Madeleine R. Udell, and Nigam H. Shah
Stanford University, Stanford, CA
Abstract
Doctors prescribe drugs for indications that are not FDA approved. Research indicates that 21% of prescriptions filled are for off-label indications. Of those, more than 73% lack supporting scientific evidence. Traditional drug safety alerts may not cover usages that are not FDA approved. Therefore, analyzing patterns of off-label drug usage in the clinical setting is an important step toward reducing the incidence of adverse events and for improving patient safety. We applied term extraction tools on the clinical notes of a million patients to compile a database of statistically significant patterns of drug use. We validated some of the usage patterns learned from the data against sources of known on-label and off-label use. Given our ability to quantify adverse event risks using the clinical notes, this will enable us to address patient safety because we can now rank-order off-label drug use and prioritize the search for their adverse event profiles.
Articles from AMIA Summits on Translational Science Proceedings are provided here courtesy of
American Medical Informatics Association