Challenges for implementation of "Enhanced Recovery After Surgery" (ERAS) protocols and artificial intelligence support tools in resource-limited countries.

Abstract

Surgical patient safety remains a major challenge in resource-limited settings, where preventable harm may be increased by delayed assessment, limited monitoring, workforce shortages, weak documentation, and inconsistent use of standardized perioperative protocols. Enhanced Recovery After Surgery offers an evidence-based pathway for improving perioperative care, while artificial intelligence may support risk prediction, complication surveillance, audit feedback, and clinical decision-making. This correspondence argues that artificial intelligence and Enhanced Recovery After Surgery should be considered complementary patient safety strategies rather than separate innovations. In low-resource surgical systems, their combined use may strengthen perioperative reliability, improve early recognition of risk, and support continuous quality improvement. However, implementation must be gradual, locally adapted, ethically governed, and built on essential safety practices such as checklist adherence, multidisciplinary teamwork, staff training, and audit.