PURPOSE: The current study aimed at identifying and quantifying critical drug interactions in neurological inpatients using clinical decision support software (CDSS). Reclassification of interactions with a focus on clinical management aimed to support the development of CDSS with higher efficacy to reduce overalerting and improve medication safety in clinical practice. METHODS: We conducted a cross-sectional study in consecutive patients admitted to the neurology ward of a tertiary care hospital. We developed a customized interface for mass analysis with the CDSS MediQ, which we used for automated retrospective identification of drug interactions during the first day of hospitalization. Interactions were reclassified according to the Zurich Interaction System (ZHIAS), which incorporates the Operational Classification of Drug Interactions (ORCA). Dose adjustments for renal impairment were also evaluated. RESULTS: In 484 patients with 2812 prescriptions, MediQ generated 8 "high danger," 518 "average danger," and 1233 "low danger" interaction alerts. According to ZHIAS, 6 alerts involved contraindicated and 33 alerts involved provisionally contraindicated combinations, and 327 alerts involved a conditional and 1393 alerts involved a minimal risk of adverse outcomes. Thirty-five patients (6.2%) had at least one combination that was at least provisionally contraindicated. ZHIAS also provides categorical information on expected adverse outcomes and management recommendations, which are presented in detail. We identified 13 prescriptions without recommended dose adjustment for impaired renal function. CONCLUSIONS: MediQ detected a large number of drug interactions with variable clinical relevance in neurological inpatients. ZHIAS supports the selection of those interactions that require active management, and the effects of its implementation into CDSS on medication safety should be evaluated in future prospective studies. Copyright © 2011 John Wiley & Sons, Ltd.