Renal CDSS Improve Prescribing Processes but Not Proven Outcomes

This systematic review clarifies what rule-based and artificial intelligence clinical decision support can and cannot deliver for medication safety in chronic kidney disease, and why implementation, not algorithm sophistication, drives benefit.

📅 Journal publication: 2026 (online Aug 28, 2026) · Last updated: Oct 7, 2026

clinical decision support systemsartificial intelligencemachine learningrule-based CDSSchronic kidney diseaserenal dose adjustmentmedication safetyprescribing errorssystematic reviewmeta-analysisalert fatigueEHRCPOE Medication Safety

Also in Nephrology

Background Information

Clinical Decision Support Systems may boost medication safety in CKD patients.

Chronic Kidney Disease (CKD) patients often face medication safety issues due to inappropriate dosing, necessitating effective Clinical Decision Support Systems (CDSS). Among 20 Randomized Controlled Trials (RCTs), CDSS improved appropriate renal dosing with a relative risk (RR) of 1.76, yet heterogeneity was extreme (I² = 97%). CDSS has potential to enhance medication safety in CKD, but significant variability and factors like alert fatigue impact clinician compliance. CDSS shows promise for improving renal drug dosing but requires careful implementation to overcome variability and compliance barriers.

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Authors: Ismail A, Sauriasari R, Yanuar A, Sudiana D, Cokro F

Citation: Ismail A, Sauriasari R, Yanuar A, et al. 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. F1000Research. 2026;15:532. doi:10.12688/f1000research.178438.2

Article Links: PubMed · Journal / DOI · Free Full Text (PMC)

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