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Introduction: Drug-disease interactions (DDSIs) are associated with increasing morbidity, mortality, and healthcare costs. These interactions are preventable if recognized and managed properly. Medication safety is critical in kidney transplant patients due to polypharmacy, co-morbidities, and susceptibility to adverse events. Clinical decision support systems (CDSSs) can play a key role therein. Therefore, this study aims to report on the process of developing an innovative, patient-centered, context-aware CDSS for managing DDSIs in kidney recipients. Material and Methods: Clinically important DDSIs were identified in the medications of patients at a kidney transplant outpatient clinic. Subsequently, rules for their detection and management were extracted based on pharmacology references and clinical expertise. A CDSS was developed and piloted following recommendations on medication CDSS design principles. Results: The knowledge base for this CDSS was developed with clinical context sensitivity. We defined priority levels for alerts, established associated display rules, and determined necessary actions based on the transplantation clinical workflow. The DDSI-CDSS correctly detected 37 DDSIs and displayed nine warnings and 28 cautionary alerts for the medications of 113 study patients (32.7% DDSI rate). The system fired three warnings for diltiazem in bradyarrhythmia, and two for each of the following medications and underlying diseases: aspirin in asthma, erythropoietin alfa in hypertension, and gemfibrozil in gall bladder disease. The potential consequences of the identified DDSIs were GI complications (17%), deterioration of the existing disease/condition (6.1%), and an increased risk of arrhythmias (2.6%), thrombosis (2.6%), and hypertension (1.7%). Complying with system alerts and recommendations would potentially prevent all these DDSIs. Conclusion: This study delineates the proce

Background and Aims: A potentially inappropriate medication (PIM) is a pharmaceutical agent that poses a greater risk of harm than potential benefit to elderly patients. This study aimed to detect PIMs and their risk factors in hospitalized elderly patients with kidney disease. Methods: This cross-sectional study assessed medication orders of elderly patients (≥65 years old) with kidney diseases admitted to the hospital. In the first 6 months, we retrospectively evaluated all medications to identify PIMs according to the 2019 Beers criteria. In the second phase, a clinical pharmacist prospectively evaluated all medications and suggested modifications as needed. Data were analyzed to determine risk factors for prescribing PIMs. Results: Based on our evaluation of 258 patients, we observed that the utilization of PIMs was prevalent among the study population. Of the total patients evaluated, 273 instances of PIM use were identified, with only 23.3% of patients not having any PIMs. Notably, proton pump inhibitors and benzodiazepines were the most frequently prescribed PIMs. The risk of experiencing a PIM was significantly amplified by a higher degree of polypharmacy, with odds approximately 2.68 times higher (p < 0.01). Several factors were found to be associated with an increased likelihood of having a PIM, including being male, undergoing hemodialysis, having chronic kidney disease or other comorbidities, and having an extended hospital stay. The second phase of study, in terms of addressing these issues, physicians adhered to 67.5% of the 120 recommendations made by pharmacists regarding the discontinuation of PIM usage. Conclusion: High prevalence of PIMs was detected in our study population. Preventing medication-associated harms in the elderly can reduce the financial burden imposed on healthcare systems. Therefore, routine evaluation of medications with clinical pharmacists and/or implementation of computerized medication decision support systems is recomm