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Background The co-administration of drugs known to interact greatly impacts morbidity, mortality, and health economics. This study aims to examine the drug–drug interaction (DDI) phenomenon with a large-scale longitudinal analysis of age and gender differences found in drug administration data from three distinct healthcare systems. Methods This study analyzes drug administrations from population-wide electronic health records in Blumenau (Brazil; 133 K individuals), Catalonia (Spain; 5.5 M individuals), and Indianapolis (USA; 264 K individuals). The stratified prevalences of DDI for multiple severity levels per patient gender and age at the time of administration are computed, and null models are used to estimate the expected impact of polypharmacy on DDI prevalence. Finally, to study actionable strategies to reduce DDI prevalence, alternative polypharmacy regimens using drugs with fewer known interactions are simulated. Results A large prevalence of co-administration of drugs known to interact is found in all populations, affecting 12.51%, 12.12%, and 10.06% of individuals in Blumenau, Indianapolis, and Catalonia, respectively. Despite very different healthcare systems and drug availability, the increasing prevalence of DDI as patients age is very similar across all three populations and is not explained solely by higher co-administration rates in the elderly. In general, the prevalence of DDI is significantly higher in women — with the exception of men over 50 years old in Indianapolis. Finally, we show that using proton pump inhibitor alternatives to omeprazole (the drug involved in more co-administrations in Catalonia and Blumenau), the proportion of patients that are administered known DDI can be reduced by up to 21% in both Blumenau and Catalonia and 2% in Indianapolis. Conclusions DDI administration has a high incidence in society, regardless of geographic, population, and healthcare management differences. Although DDI prevalence increases with age, our ana, J.S.V. was funded by the Spanish Ministry of Economics and Competitiveness (RTI2018-096653-B-I00 and PID2022-141809OB-I00). R.B.C. was partially funded by Fundacão para a Ciência e a Tecnologia (grant PTDC/MECAND/30221/2017) and the National Institutes of Health (NIH), National Library of Medicine (grant R01-LM012832). L.M.R. was partially funded by the National Institutes of Health (NIH), National Library of Medicine (grants R01-LM011945 and R01-LM012832), by a Fulbright Commission fellowship, and by the National Science Foundation Research Traineeship “Interdisciplinary Training in Complex Networks and Systems” (grant 1735095). J.S.V., R.B.C., and L.M.R. were funded by the Fundação para a Ciência e a Tecnologia Grant No. 2022.09122.PTDC (https://doi.org/https://doi.org/10.54499/2022.09122.PTDC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., Peer Reviewed, Postprint (published version)