Current perspectives on the use of artificial intelligence in critical patient safety

Abstract

Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.

Keywords: Adverse events; Algorithms; Algoritmos; Aprendizaje automático; Artificial intelligence; Critical care; Cuidados críticos; Evaluación de riesgos; Eventos adversos; Inteligencia artificial; Machine learning; Patients safety; Predicción; Prediction; Risk assessment; Seguridad del paciente.