Authors
Nourelsabah Mohamed, Alaa Mansour, Ahmed Farouk Donia
Published in
Journal of nephrology. Jul 16, 2026. Epub Jul 16, 2026.
Abstract
Chronic kidney disease (CKD) patients in resource-limited settings face high risks of medication-related problems due to polypharmacy and suboptimal clinical decision support systems. Despite the implementation of Computerized Physician Order Entry systems, errors occur and their patterns and system gaps remain understudied in outpatient nephrology clinics.
This cross-sectional study analyzed 552 CKD patients attending a tertiary nephrology clinic in Egypt (January-July 2024). We conducted standardized medication reviews using National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) and Pharmaceutical Care Network Europe (PCNE) criteria to classify medication-related problems.
Medication-related problems occurred in 23.5% of patients (130/552), with 140 errors identified. Overdose (38.5%) and legacy prescribing (35.8%) were most common, primarily involving statins (24.3%), vitamin D analogs (15.7%), and prokinetics (14.3%). A dose-response relationship emerged: patients prescribed >14 medications had an 8.94-fold higher odds of errors (46.5% error rate) versus those on 1-4 medications (7.4%). Post-transplant status independently increased risk (adjusted odds ratio [OR] 4.12, 95% confidence interval [CI] 1.45-11.72), reflecting the complexity of immunosuppressive regimens. Errors persisted for a median of 174 days, underscoring system deficiencies such as absent estimated glomerular filtration rate (eGFR)-based dosing alerts.
Despite the use of Computerized Physician Order Entry systems, medication-related problems persist in CKD outpatients, driven by polypharmacy and inadequate clinical decision support system functionality. Prioritizing eGFR-integrated alerts, pharmacist-led reconciliation, and deprescribing protocols for high-risk patients (eg, those with >10 medications) could mitigate errors. These findings highlight urgent needs for enhanced clinical decision support systems and multidisciplinary interventions in resource-limited settings.
PMID:
42460517
Bibliographic data and abstract were imported from PubMed on 16 Jul 2026.
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