title: DRUG-DRUG INTERACTION PROFILES OF MEDICATION REGIMENS EXTRACTED FROM A DE-IDENTIFIED ELECTRONIC MEDICAL RECORDS SYSTEM.
abstract: With age, the number of prescribed medications increases and subsequently raises the risk for adverse drug-drug interactions. These adverse effects lower quality of life and increase health care costs. Quantifying the potential burden of adverse effects before prescribing medications can be a valuable contribution to health care. This study evaluated medication lists extracted from a subset of the Vanderbilt de-identified electronic medical record system. Reported drugs were cross-referenced with the Kyoto Encyclopedia of Genes and Genomes DRUG database to identify known drug-drug interactions. On average, a medication regimen contained 6.58 medications and 2.68 drug-drug interactions. Here, we quantify the burden of potential adverse events from drug-drug interactions through drug-drug interaction profiles and include a number of alternative medications as provided by the Anatomical Therapeutic Chemical Classification System.
authors: Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, US.
authors: Mariusz
authors: M
authors: Butkiewicz
authors: Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, US.
authors: Nicole A
authors: NA
authors: Restrepo
authors: Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, US.
authors: Jonathan L
authors: JL
authors: Haines
authors: Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, US.
authors: Dana C
authors: DC
authors: Crawford