OBJECTIVE: The evaluation of the prevalence of potential drug-drug interactions and assessment of their clinical relevance in patients' discharge medication in the medical ward of a community teaching hospital. The relevant clinical information was reported to the treating physicians. METHODS: 200 patients at discharge from a medical ward were included. Prescribed drugs were analysed for interactions using commercially available software (Pharmavista). Clinical pharmacists and a physician assessed the clinical relevance of detected interactions, eliminated those which were not considered clinically relevant and formulated recommendations for those considered clinically relevant. A written recommendation was given to the physician to provide rapid feedback before discharge. RESULTS: The median age of the 200 patients studied was 69 years. At discharge, patients took an average of 7 different drugs. 62.5% of patients had at least one potential drug-drug interaction. In total, 373 potential drug-drug interactions were identified: 223 (60%) of minor severity, 143 (38%) of moderate severity and 7 (2%) of major severity. CONCLUSIONS: A computerised drug-drug interaction program (detection) together with clinical pharmacological experience (interpretation/evaluation) can be useful for decreasing the number of potentially harmful drug combinations. This approach may lead to an improvement in the quality of prescription, reducing possible risks and thus contributing to patient safety.
OBJECTIVE: The evaluation of the prevalence of potential drug-drug interactions and assessment of their clinical relevance in patients' discharge medication in the medical ward of a community teaching hospital. The relevant clinical information was reported to the treating physicians. METHODS: 200 patients at discharge from a medical ward were included. Prescribed drugs were analysed for interactions using commercially available software (Pharmavista). Clinical pharmacists and a physician assessed the clinical relevance of detected interactions, eliminated those which were not considered clinically relevant and formulated recommendations for those considered clinically relevant. A written recommendation was given to the physician to provide rapid feedback before discharge. RESULTS: The median age of the 200 patients studied was 69 years. At discharge, patients took an average of 7 different drugs. 62.5% of patients had at least one potential drug-drug interaction. In total, 373 potential drug-drug interactions were identified: 223 (60%) of minor severity, 143 (38%) of moderate severity and 7 (2%) of major severity. CONCLUSIONS: A computerised drug-drug interaction program (detection) together with clinical pharmacological experience (interpretation/evaluation) can be useful for decreasing the number of potentially harmful drug combinations. This approach may lead to an improvement in the quality of prescription, reducing possible risks and thus contributing to patient safety.