CONGRESS ABSTRACT

Introduction: Patient safety in interventional cardiology laboratories remains a critical challenge due to the high procedural complexity and technological intensity of these environments. Although international guidelines provide general recommendations, the absence of tools specifically adapted to catheterisation laboratory workflows may limit the effectiveness of quality and risk management processes. This project aims to structure and design an artificial intelligence supported checklist to improve procedural safety, operational efficiency, and patient centred care. Methods: A multidisciplinary and multicentre survey was conducted involving cardiovascular healthcare professionals, relevant scientific societies, the Nursing Professions Association, and the clinical risk management unit. Through this collaborative approach, the checklist was developed and optimized for interventional cardiology workflows. Results: The checklist encourages accurate documentation, reduces errors, and improves clinical risk management. With AI support, it enables continuous procedural monitoring and timely anomaly detection, which allows anticipation of complications. These improvements benefit clinical outcomes and help optimise resources. Additionally, using the checklist facilitates compliance with safety regulations and professional liability requirements. This, in turn, supports a more predictive and personalised patient care approach. Conclusions: This initiative represents the first Italian implementation of an AI-integrated checklist specifically designed for the cath lab. Integrating artificial intelligence into cath lab workflows has the potential to reshape clinical practice by enabling real time procedure monitoring, early identification of risk patterns, and the use of machine learning based predictive models. The most impactful element, however, lies in its seamless connection with electronic health record systems, which is essential to fully harness the clinical and organizational benefits of AI. Direct integration with electronic medical records allows automatic retrieval of comprehensive patient data, including medical history, laboratory values, imaging reports, and demographic information providing a holistic patient overview while minimizing manual data entry. This streamlined workflow reduces the risk of errors and accelerates clinical decision-making, ultimately supporting safer and more efficient practice.