Alert fatigue and errors caused by technology: A scoping review and introduction to the flow of cognitive processing model

Technologies such as electronic health records (EHRs), embedded clinical decision support systems (CDSS) and computerized physician order entry (CPOE) systems are at the forefront of healthcare’s technological revolution. These health information technologies (HIT) pose great promise to improve patient safety, reduce medication errors and increase operational efficiencies in healthcare organizations. However, despite the perceived benefits that these complex technologies offer, their associated risks must not be overlooked or disregarded (Borycki et al., 2012). The objective of this article is to answer the following questions: 1) What is the nature of errors caused by technology (i.e., technology-induced errors) and alert fatigue in healthcare? 2) Is there a relationship between alert fatigue and technology-induced errors? 3) Do organizational strategies exist to address these problems and enhance patient safety? 4) Do technological recommendations exist to improve the current issues surrounding safety? To answer these questions a scoping review following the Arksey and O’Malley (2005) framework was conducted using the CINAHL®, Web of Science®, IEEE Xplore® and PubMed® databases. The search focused on English publications only, using the search terms “Alert Fatigue” and “Technology Errors.” Articles were iteratively assessed based on the inclusion and exclusion criteria, resulting in an inclusion of 36 articles in the final scoping review. Following this, a thematic analysis was conducted and the findings placed in a data extraction table. The results indicated that while HIT present a significant opportunity to streamline processes and reduce medication errors, there is a critical need to assess them from a patient safety and quality lens. Lastly, a novel conceptual tool was created, the Flow of Cognitive Processing Model. The model provides an iterative perspective and an insightful view into the cognitive realms of healthcare professionals in their interactions with HIT. By illustrating the complexities of healthcare providers from a humanistic lens, the model could guide HIT design, acquisitions and implementations to reduce alert fatigue and mitigate the introduction of technology-induced errors.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.