title: Adverse Drug Event Ontology: Gap Analysis for Clinical Surveillance Application.
abstract: Adverse drug event identification and management are an important patient safety problem given the potential for event prevention. Previous efforts to provide structured data methods for population level identification of adverse drug events have been established, but important gaps in coverage remain. ADE identification gaps contribute to suboptimal and inefficient event identification. To address the ADE identification problem, a gap assessment was completed with the creation of a proposed comprehensive ontology using a Minimal Clinical Data Set framework incorporating existing identification approaches, clinical literature and a large set of inpatient clinical data. The new ontology was developed and tested using the National Inpatient Sample database with the validation results demonstrating expanded ADE identification capacity. In addition, the newly proposed ontology elements are noted to have significant inpatient mortality, above median inpatient costs and a longer length of stay when compared to existing ADE ontology elements and patients without ADE exposure.
authors: Institute for Health Informatics, University of Minnesota, Minneapolis, MN. ; College of Pharmacy, University of Minnesota, Minneapolis, MN.
authors: Terrence J
authors: TJ
authors: Adam
authors: Institute for Health Informatics, University of Minnesota, Minneapolis, MN. ; College of Pharmacy, University of Minnesota, Minneapolis, MN.
authors: Jin
authors: J
authors: Wang