PURPOSE: Our aim was to study drug interactions and dose adjustments in patients with renal impairment in the discharge medication of surgical inpatients and to evaluate the strengths and limitations of clinical decision support software (CDSS) for this task. METHODS: This was a cross-sectional study involving 509 surgical patients of a primary care hospital. We developed a customized interface for the CDSS MediQ, which we used for automated retrospective identification of drug interactions in the patients' discharge medication. The clinical relevance of the interactions was evaluated based on the Zurich Interaction System (ZHIAS) that incorporates the operational classification of drug interactions (ORCA). Prescriptions were further analyzed for recommended dose adjustments in patients with a glomerular filtration rate <60 ml/min. RESULTS: For the total of 2,729 prescriptions written for the 509 patients enrolled in the study, MediQ generated 2,558 interaction alerts and 1,849 comments. Among these were ten "high danger" and 551 "average danger" alerts that we reclassified according to ORCA criteria. This reclassification resulted in ten contraindicated combinations, 77 provisionally contraindicated combinations, and 310 with a conditional and 164 with a minimal risk of adverse outcomes. The ZHIAS classification also provides categorical information on expected adverse outcomes and management recommendations, which are presented in detail. We identified 56 prescriptions without a recommended dose adjustment for impaired renal function. CONCLUSIONS: CDSS identified a large number of drug interactions in surgical discharge medication, but according to ZHIAS criteria only a minor fraction of these appeared to involve a substantial risk to the patient. CDSS should therefore aim at reducing over-alerting and improve usability in order to become more efficacious in terms of the prevention of adverse drug events in clinical practice.
PURPOSE: Our aim was to study drug interactions and dose adjustments in patients with renal impairment in the discharge medication of surgical inpatients and to evaluate the strengths and limitations of clinical decision support software (CDSS) for this task. METHODS: This was a cross-sectional study involving 509 surgical patients of a primary care hospital. We developed a customized interface for the CDSS MediQ, which we used for automated retrospective identification of drug interactions in the patients' discharge medication. The clinical relevance of the interactions was evaluated based on the Zurich Interaction System (ZHIAS) that incorporates the operational classification of drug interactions (ORCA). Prescriptions were further analyzed for recommended dose adjustments in patients with a glomerular filtration rate <60 ml/min. RESULTS: For the total of 2,729 prescriptions written for the 509 patients enrolled in the study, MediQ generated 2,558 interaction alerts and 1,849 comments. Among these were ten "high danger" and 551 "average danger" alerts that we reclassified according to ORCA criteria. This reclassification resulted in ten contraindicated combinations, 77 provisionally contraindicated combinations, and 310 with a conditional and 164 with a minimal risk of adverse outcomes. The ZHIAS classification also provides categorical information on expected adverse outcomes and management recommendations, which are presented in detail. We identified 56 prescriptions without a recommended dose adjustment for impaired renal function. CONCLUSIONS:CDSS identified a large number of drug interactions in surgical discharge medication, but according to ZHIAS criteria only a minor fraction of these appeared to involve a substantial risk to the patient. CDSS should therefore aim at reducing over-alerting and improve usability in order to become more efficacious in terms of the prevention of adverse drug events in clinical practice.
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