Implementation of artificial intelligence tools in intensive care units for nursing care: a systematic review
DOI:
https://doi.org/10.62305/biosana.v6i4.1251Keywords:
intensive care; nursing; artificial intelligence; critically ill patientAbstract
The integration of artificial intelligence (AI) in Intensive Care Units (ICUs) is relevant for the care of critically ill patients, where rapid response is crucial for survival. This study analyzed the implementation of AI tools in ICUs for nursing care, identifying applications, advantages, limitations, and clinical impact. A systematic review was conducted following PRISMA 2020 guidelines, searching Scopus, PubMed, SciELO, LILACS, BVS, CINAHL, and ScienceDirect using DeCS/MeSH descriptors and Boolean operators AND/OR. Original studies published between 2021 and 2026 in Spanish, English, and Portuguese were included, and methodologically assessed using Johns Hopkins EBP and MMAT. Twenty studies met the inclusion criteria, predominantly focusing on machine learning algorithms aimed at predicting mortality, sepsis, acute kidney injury, nutritional risk, and other complications. The results showed improvements in diagnostic accuracy, early detection of clinical deterioration, and support for decision-making. Barriers related to infrastructure, training, algorithmic bias, transparency, ethics, and professional trust were identified. The study concluded that AI is a complementary tool that strengthens nursing clinical judgment, promoting safer, more timely, and personalized care, provided its implementation incorporates adequate training and ethical validation.
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