OVERCROWDING IN ICUS AND ADVERSE EVENTS: CONTRIBUTIONS OF ARTIFICIAL INTELLIGENCE IN HOSPITAL MANAGEMENT

Abstract

Overcrowding in Intensive Care Units (ICUs) is one of the main contemporary challenges in hospital management, being directly associated with an increased occurrence of adverse events and a reduction in the quality of care. In this context, the incorporation of innovative technologies, such as Artificial Intelligence (AI), has been identified as a promising strategy to optimize both clinical and managerial processes. This study aimed to analyze the contributions of Artificial Intelligence to hospital management in reducing ICU overcrowding and preventing adverse events. This is a qualitative study developed through an integrative literature review, with searches conducted in PubMed/MEDLINE, SciELO, LILACS, Scopus, and Web of Science, including articles published between 2021 and 2026 in Portuguese, English, and Spanish. Ten studies were selected, analyzed descriptively and interpretatively, and organized into three thematic axes: ICU overcrowding and its impacts; adverse events and patient safety; and AI applications in hospital management. The findings indicate that overcrowding is associated with increased care failures, staff overload, and higher incidence of adverse events, while AI demonstrates significant potential in clinical risk prediction, continuous monitoring, and bed management optimization. It is concluded that AI represents a strategic tool for transforming hospital management, with potential to reduce ICU overcrowding and enhance patient safety, provided it is integrated critically, ethically, and evidence based.