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Update in intensive care medicine: Critical patient safety
Available online 28 April 2024
Current perspectives on the use of artificial intelligence in critical patient safety
Perspectivas actuales sobre el uso de la inteligencia artificial en la seguridad del paciente crítico
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Jesús Abelardo Barea Mendozaa,
Corresponding author
, Marcos Valiente Fernandeza, Alex Pardo Fernandezb, Josep Gómez Álvarezc
a UCI de Trauma y Emergencias. Servicio de Medicina Intensiva. Hospital Universitario 12 de Octubre. Instituto de Investigación Hospital 12 de Octubre, Spain
b Universitat Rovira i Virgili, Tarragona, Spain
c Hospital Universitari de Tarragona Joan XXIII. Universitat Rovira i Virgili. Institut d’Investigació Sanitària Pere i Virgili, Tarragona, Spain
This item has received
Received 19 December 2023. Accepted 11 March 2024
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Table 1. Possible functionalities of CDSS, potential risks, and risk mitigation strategies.
Table 2. Types of most common CDSS-generated alerts based on models.
Table 3. Main metrics used in the evaluation of AI models.
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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:
Critical care
Patients safety
Prediction
Risk assessment
Algorithms
Artificial intelligence
Machine learning
Adverse events
Resumen

Las unidades de cuidados intensivos (UCI) han sido objeto de mejoras en la seguridad del paciente y la inteligencia artificial (IA) se presenta como una tecnología disruptiva que ofrece nuevas oportunidades. Aunque la evidencia publicada es limitada y presenta problemas metodológicos algunas áreas resultan prometedoras como los sistemas de ayuda a la decisión, detección de eventos adversos o errores de prescripción. El uso de la IA en seguridad puede tener un objetivo diagnóstico o predictivo. La implementación de sistemas basados en IA requiere procedimientos para garantizar la asistencia segura, enfrentando desafíos como la confianza en dichos sistemas, sesgos, calidad de los mismos, escalabilidad y consideraciones éticas y de confidencialidad.

El desarrollo y la aplicación de la IA demandan pruebas exhaustivas, incluyendo testeo sobre datos retrospectivos, validación con cohortes prospectivas en tiempo real y demostración de eficacia en ensayos clínicos. La transparencia y explicabilidad algorítmica resultan esenciales siendo la participación activa de profesionales clínicos en la implementación es crucial.

Palabras clave:
Cuidados críticos
Seguridad del paciente
Predicción
Evaluación de riesgos
Algoritmos
Inteligencia artificial
Aprendizaje automático
Eventos adversos

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