Performance of a clinical decision support system and of clinical pharmacists in preventing drug–drug interactions on a geriatric ward

Background Drug–drug interactions (DDIs) can lead to adverse drug events and compromise patient safety. Two common approaches to reduce these interactions in hospital practice are the use of clinical decision support systems and interventions by clinical pharmacists. Objective To compare the performance of both approaches with the main objective of learning from one approach to improve the other. Setting Acute geriatric ward in a university hospital. Methods Prospective single-centre, cohort study of patients admitted to the geriatric ward. An independent pharmacist compared the clinical decision support alerts with the DDIs identified by clinical pharmacists and evaluated their interventions. Contextual factors used by the clinical pharmacists for evaluation of the clinical relevance were analysed. Adverse drug events related to DDIs were investigated and the causality was evaluated by a clinical pharmacologist based on validated criteria. Main outcome measure Number of alerts, interventions and the acceptance rates. Results Fifty patients followed by the clinical pharmacists, were included. The clinical pharmacists identified 240 DDIs (median of 3.5 per patient) and advised a therapy change for 16 of which 13 (81.2 %) were accepted and three (18.8 %) were not. The decision support system generated only six alerts of which none were accepted by the physicians. Thirty-seven adverse drug events were identified for 29 patients that could be related to 55 DDIs. For two interactions the causality was evaluated as certain, for 31 as likely, for ten as possible and for 12 as unlikely. Mainly intermediate level interactions were related to adverse drug events. Contextual factors taken into account by the clinical pharmacists for evaluation of the interactions were blood pressure, international normalised ratio, heart rate, potassium level and glycemia. Additionally, the clinical pharmacists looked at individual administration intervals and drug sequence to determine the clinical relevance of the interactions. Conclusion Clinical pharmacists performed better than the decision support system mainly because the system screened only for high level DDIs and because of the low specificity of the alerts. This specificity can be increased by including contextual factors into the logic and by defining appropriate screening intervals that take into account the sequence in which the drugs are given.