EXPERTS’ OPINION   

Minerva Anestesiologica 2025 Apr 11

DOI: 10.23736/S0375-9393.25.18746-4

Copyright © 2025 EDIZIONI MINERVA MEDICA

language: English

ERAS and the challenge of the new technologies

Elena BIGNAMI ^{1, 2} ✉, Brigida LEONI ^{1, 2}, Tania DOMENICHETTI ^{1, 2}, Matteo PANIZZI ^{1, 2}, Luis A. DIEGO ³, Valentina BELLINI ^{1, 2}

¹ Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Parma, Italy; ² Second Division of Anesthesia and Intensive Care, University Hospital of Parma, Parma, Italy; ³ Department of Anesthesiology, Fluminense Federal University (UFF), Rio de Janeiro, Brazil

The integration of artificial intelligence (AI) and all new technologies (NTs) into enhanced recovery after surgery (ERAS) protocols offers significant opportunities to address implementation challenges and improve patient care. Despite the proven benefits of ERAS, limitations such as resistance to change, resource constraints, and poor interdepartmental communication persist. AI can play a crucial role in overcoming ERAS implementation barriers by simplifying clinical plans, ensuring high compliance, and creating patient-centered approaches. Advanced techniques like machine learning and deep learning can optimize preoperative management, intraoperative phases, and postoperative recovery pathways. AI integration in ERAS protocols has the potential to revolutionize perioperative medicine by enabling personalized patient care, enhancing monitoring strategies, and improving clinical decision-making. The technology can address common postoperative challenges by developing individualized ERAS plans based on patient risk factors and optimizing perioperative processes. While challenges remain, including the need for external validation and data security, the authors suggest that the combination of AI, NTs, and ERAS protocols should become an integral part of routine clinical practice. This integration ultimately leads to improved patient outcomes and satisfaction in surgical care, transforming the perioperative medicine landscape by tailoring pathways to patients’ needs.

KEY WORDS: Artificial intelligence; Enhanced recovery after surgery; Precision medicine