Can the integration of new rules into a clinical decision support system reduce the incidence of acute kidney injury and hyperkalemia among hospitalized older adults: a protocol for a stepped-wedge, cluster-randomized trial (DETECT-IP).

Background: Clinical decision support systems (CDSSs) enable the automated, real-time detection of situations associated with a risk of adverse drug events (ADEs). However, the effectiveness of CDSS in reducing ADEs has yet to be demonstrated. We have chosen to focus on the detection of ADE such as hyperkalemia and/or acute kidney injury (AKI), which are common among hospitalized older adults.