The occurrence of drug-drug-interactions (DDI) from multiple drug dispensations is a serious problem, both for individuals and health-care systems, since patients with complications due to DDI are likely to re-enter the system at a costlier level. We present a large-scale longitudinal study (18 months) of the DDI phenomenon at the primary- and secondary-care level using electronic health records (EHR) from the city of Blumenau in Southern Brazil (pop. ~ 340,000). This is the first study of DDI we are aware of that follows an entire city longitudinally for more than 3 months. We found that 181 distinct drug pairs known to interact were dispensed concomitantly to 12 \% of the patients in the city's public health-care system. Further, 4\% of the patients were dispensed DDI combinations, likely to result in major adverse reactions with costs estimated to be larger than previously reported in smaller studies. DDI results are integrated into associative networks for inference and visualization, revealing key medications and interactions involved in the DDI phenomenon. Analysis reveals that women have a 60\% increased risk of DDI as compared to men; the increase becomes 90\% when only major DDI are considered. Furthermore, DDI risk increases substantially with age. Patients aged 70-79 years have a 34\% risk of DDI when they are dispensed two or more drugs concomitantly. Interestingly, a null model demonstrates that age- and women-specific risks from increased polypharmacy fail by far to explain the observed risks of DDI in those populations. This suggests that social and biological factors are at play. These results demonstrate that considerable gender and age biases exist, but that accurate warning systems for known DDI can be devised for health-care systems and public-health policy management, to reduce DDI-related adverse reactions and health-care costs. \\%DIF > of the patients in the city's public health-care system. Further, 4\\% of the patients were dispensed drug pairs that are likely to result in major adverse drug reactions (ADR)---with costs estimated to be much larger than previously reported in smaller studies. The large-scale analysis reveals that women have a 60\\% increased risk of DDI as compared to men; the increase becomes 90\\% when considering only DDI known to lead to major ADR. Furthermore, DDI risk increases substantially with age; patients aged 70-79 years have a 34\\% risk of DDI when they are dispensed two or more drugs concomitantly. Interestingly, a statistical null model demonstrates that age- and female-specific risks from increased polypharmacy fail by far to explain the observed DDI risks in those populations, suggesting unknown social or biological causes. We also provide a network visualization of drugs and demographic factors that characterize the DDI phenomenon and demonstrate that accurate DDI prediction can be included in healthcare and public-health management, to reduce DDI-related ADR and costs.
The occurrence of drug-drug-interactions (DDI) from multiple drug dispensations is a serious problem, both for individuals and health-care systems, since patients with complications due to DDI are likely to reenter the system at a costlier level. We present a large-scale longitudinal study (18 months) of the DDI phenomenon at the primary- and secondary-care level using electronic health records (EHR) from the city of Blumenau in Southern Brazil (pop. \approx 340,000). We found that 181 distinct drug pairs known to interact were dispensed concomitantly to 12 \\%DIF > of the patients in the city's public health-care system. Further, 4\\% of the patients were dispensed drug pairs that are likely to result in major adverse drug reactions (ADR)---with costs estimated to be much larger than previously reported in smaller studies. The large-scale analysis reveals that women have a 60\\% increased risk of DDI as compared to men; the increase becomes 90\\% when considering only DDI known to lead to major ADR. Furthermore, DDI risk increases substantially with age; patients aged 70-79 years have a 34\\% risk of DDI when they are dispensed two or more drugs concomitantly. Interestingly, a statistical null model demonstrates that age- and female-specific risks from increased polypharmacy fail by far to explain the observed DDI risks in those populations, suggesting unknown social or biological causes. We also provide a network visualization of drugs and demographic factors that characterize the DDI phenomenon and demonstrate that accurate DDI prediction can be included in healthcare and public-health management, to reduce DDI-related ADR and costs.
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This is the first study of DDI we are aware of that follows an entire city longitudinally for more than 3 months.
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\% of the patients in the city's public health-care system. Further, 4\% of the patients were dispensed DDI combinations, likely to result in major adverse reactions with costs estimated to be larger than previously reported in smaller studies. DDI results are integrated into associative networks for inference and visualization, revealing key medications and interactions involved in the DDI phenomenon. Analysis reveals that women have a 60\% increased risk of DDI as compared to men; the increase becomes 90\% when only major DDI are considered. Furthermore, DDI risk increases substantially with age. Patients aged 70-79 years have a 34\% risk of DDI when they are dispensed two or more drugs concomitantly. Interestingly, a null model demonstrates that age- and women-specific risks from increased polypharmacy fail by far to explain the observed risks of DDI in those populations. This suggests that social and biological factors are at play. These results demonstrate that considerable gender and age biases exist, but that accurate warning systems for known DDI can be devised for health-care systems and public-health policy management, to reduce DDI-related adverse reactions and health-care costs.