Usefulness of Drug Allergy Alert Systems: Present and Future

Abstract

Abstract Purpose of Review The goal of this paper is to review drug allergy alert systems (DAAS), to summarise their key components, and to overview potential benefits and challenges associated with these tools. Methods for validation of their effects on patient safety, alternative uses, and strategies to streamline DAAS’ functions and reduce system fatigue are discussed. Recent Findings DAAS are clinical decision support systems (CDSS) that focus on preventing drug adverse events within healthcare settings. The advent of electronic medical records has facilitated the development of digital DAAS. Existing versions use different methods to document diagnosed allergies, and rely on distinct rules and matching strategies for the generation of real-time alerts. DAAS promote the automation of several processes, facilitate prompt patient referral, and may be customised. Information overload, alert overrides by clinicians, and the development of “alert fatigue” may interfere with their usefulness. The newest strategies to streamline the function of DAAS include the use of artificial intelligence (AI) and other predictive techniques. Summary The rising prevalence of drug allergies underscores the importance of effective DAAS. Further research is needed to evaluate their usefulness, to optimise their performance, to explore different algorithms and data sources, and to enhance the standardised integration of these systems into clinical practice.