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. The present study's primary objective is to use a CDSS to reduce the number of ADEs (such as AKI and/or hyperkalemia) that occur in hospitalized older adults.

Methods: This is a multicenter, stepped-wedge, cluster-randomized study involving five hospitals. Each hospital will start with a control period (i.e., routine care, during which each center's CDSS is deactivated) and then switch to an intervention period (during which the CDSS is activated). The intervention will be the use of a CDSS and a strategy for managing and transmitting alerts to clinical pharmacists. The rules concerning AKI and hyperkalemia have been drafted and reviewed by a multidisciplinary group. Each rule created in the CDSS is associated with a standardized procedure, based on a review of the literature. Older patients (aged 65 or over) admitted to a participating general medicine ward, a surgical ward, or obstetrics ward will be eligible for inclusion after the provision of verbal informed consent.

Discussion: This study will assess the effectiveness of the CDSS in reducing the incidence of AKI and hyperkalemia. The implementation of the CDSS can assist clinical pharmacists in their daily work and is expected to prevent ADEs.

Trial registration: ClinicalTrials.gov Identifier: NCT05923983. Registered February 02, 2023.