Improving Medication Safety in Chronic Kidney Disease Using Rule-Based and Artificial Intelligence–Based Clinical Decision Support Systems: A Systematic Review of Randomized Controlled Trials

<ns5:p>Background Optimization of renal drug dosing to avoid drug toxicity is essential in Chronic Kidney Disease (CKD), yet prescribing errors are common. CDSS with rule-based and AI/ML based tools are used to address this safety gap; however, their impact remains uncertain. Methods We performed a PRISMA-guided systematic review and meta-analysis of RCTs comparing rule-based or AI/ML CDSS with usual care comparators among adults with CKD or at risk of CKD-related prescribing errors. The primary outcome was a medication safety endpoint aligned with the CDSS logic (appropriate renal dosing, potentially inappropriate prescribing, and medication errors). Secondary outcomes were quality-of-care processes, clinical endpoints, use of health services, and patient-reported outcomes. To address heterogeneity, we supplemented meta-analysis with a structured Best Evidence Synthesis and trial-level mapping by delivery mode and workflow stage. Results Among the 20 RCTs that met our inclusion criteria, 6 provided data for the meta-analysis. CDSS improved proximal medication-safety processes (RR 1.76; 95% CI, 1.13-2.74). The wide prediction interval indicates that effectiveness depends on implementation and local settings. Documentation of CKD in electronic health records improved (risk ratio 1.19; 95% confidence interval 1.07–1.32), but downstream clinical outcomes were less studied and remain equivocal. Interventions with current evidence were predominantly interruptive, order-entry interventions. Implementation barriers were common; clinician compliance ranged from 17% to 74% due to alert fatigue, time constraints, and unclear understanding of system function and override processes. Conclusions CDSS for CKD have shown value in enhancing medication safety, but not all models have been successful. These process-based benefits are not yet supported by demonstrable improvements in clinical outcomes. This gap supports treating renal CDSS as part of safety-critical services, requiring auditable logic, clear severity tiers, and a traceable mechanism for overrides. A replicable evidence base requires agreed core outcomes and reporting standards.</ns5:p>