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.

Integrating automated dispensing cabinets into the medication dispensing process: feedback from the practice in European hospitals.

Objectives: Automated dispensing cabinets (ADCs) offer improved medication safety, greater efficiency and return on investment. However, integrating ADCs into medication dispensing processes can be challenging in complex hospital environments. This study aimed to draft suggestions to help hospitals adopt ADCs.

Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.

The health product circuit corresponds to the chain of steps that a medicine goes through in hospital, from prescription to administration. The safety and regulation of all the stages of this circuit are major issues to ensure the safety and protect the well-being of hospitalized patients. In this paper we present an automatic system for analyzing prescriptions using Artificial Intelligence (AI) and Machine Learning (ML), with the aim of ensuring patient safety by limiting the risk of prescription errors or drug iatrogeny.

[Development of a methodological guide on the implementation of a pharmaceutical decision support system: Feedback from a French university hospital].

Objective: Develop a methodological guide on the implementation of a PDSS (pharmaceutical decision support system).

Method: Observational study, retrospective conducted at Lille University Hospital from May 2017 to December 2020, corresponding to the period of implementation and then use of the software. The different phases of the project are described as well as the methodology at each stage.

Escitalopram-induced hepatitis: A case report.

Background: The antidepressant escitalopram is widely prescribed for the treatment of depression. It is generally well-tolerated, and cholestasis is not mentioned in its summary of product characteristics (SmPC). We present a case of cholestatic and cytolysis liver injury due to escitalopram and a VigiBase study.