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OBJECTIVE Drug-drug interaction (DDI) alerting is an important form of clinical decision support, yet physicians often fail to attend to critical DDI warnings due to alert fatigue. We previously described a model for highlighting patients at high risk of a DDI by enhancing alerts with relevant laboratory data. We sought to evaluate the effect of this model(More)
Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism(More)
PURPOSE Bioequivalent medications are required by the Food and Drug Administration to have identical warnings on their labels. This requirement has both clinical and legal importance, yet has never been validated. We sought to determine the real-world consistency of electronic labeling for bioequivalent drugs from different manufacturers. METHODS Using(More)
BACKGROUND Methodological research to evaluate the performance of methods requires a benchmark to serve as a referent comparison. In drug safety, the performance of analyses of spontaneous adverse event reporting databases and observational healthcare data, such as administrative claims and electronic health records, has been limited by the lack of such(More)
Evaluating the potential harm of a drug-drug interaction (DDI) requires knowledge of a patient's relevant co-morbidities and risk factors. Current DDI alerts lack such patient-specific contextual data. In this paper, we present an efficient model for integrating pertinent patient data into DDI alerts. This framework is designed to be interoperable across(More)
The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to(More)
Evaluating medications for potential adverse events is a time-consuming process, typically involving manual lookup of information by physicians. This process can be expedited by CDS systems that support dynamic retrieval and filtering of adverse drug events (ADE's), but such systems require a source of semantically-coded ADE data. We created a two-component(More)
BACKGROUND The official prescribing information document distributed with a prescription drug is a key source of safety information, but it may include excessive or insufficient details. OBJECTIVES To compare prescribing information approved by the US Food and Drug Administration with the UK, Canada and Australia to identify content differences in safety(More)