Development and Validation of an Automated Acute Kidney Injury E-Alert System Integrated with Clinical Decision Support for Hospitalized Patients.

Abstract

Automated electronic alerts integrated into inpatient electronic health records (EHRs) may improve recognition of moderate-to-severe acute kidney injury (AKI) and support timely medication review. An AKI e-alert system integrated with medication-focused clinical decision support (CDS) was implemented to identify adults with KDIGO stage 2-3 hospital-acquired AKI in near real time while minimizing alert burden. The alert logic used KDIGO serum creatinine (SCr) criteria, defined the operational real-time inpatient baseline as the lowest SCr value within the preceding seven days, and applied suppression rules for dialysis within seven days or imminent transfer/discharge. Alerts were generated through scheduled near-real-time processing four times daily and were accompanied by secure in-hospital medication guidance; the CDS did not automatically place orders. System performance was evaluated at a 2,768-bed tertiary medical center in Taiwan using EHR data from March 2018 to May 2023 and validated against a retrospective computerized reference algorithm designed to replicate the deployed logic. The system generated 3,946 stage 2-3 AKI alerts, achieving 90.94% sensitivity and 99.65% accuracy compared with the reference algorithm. Seasonal alert rates were highest in winter (4.48%) and lowest in summer (3.17%), supporting the temporal face validity of the detection approach. In a hospital-wide physician survey (n = 78), 63.0% agreed that the medication guidance accompanying alerts was clinically helpful. An EHR-integrated e-alert targeting advanced AKI can achieve high real-world performance, and linking alerts to targeted medication CDS may facilitate nephrotoxin stewardship and medication safety while limiting alert fatigue.