An Algorithm for the Integration of Data from Surgical Robots and Operation Room Management Systems

Abstract

This study presents an algorithm developed by the Clinical Engineering department to automatically match surgical events recorded by robotic systems with corresponding entries in the hospital’s OR management software. At ASST Grande Ospedale Metropolitano Niguarda, robotic procedures were previously identified manually by surgical staff within the operating room management system, often leading to frequent inconsistencies and data quality issues. Two heterogeneous datasets—robot logs and hospital procedure records—were aligned using common features such as date, duration, and operating room, despite the absence of a unique identifier. The matching algorithm enables accurate identification of robotic procedures within the hospital system and facilitates integration of clinical and technical data into a unified framework. This integrated approach supports more effective data utilization for clinical engineering activities, operational monitoring, and Health Technology Assessment (HTA) analyses. The work provides a practical solution to a real-world data integration challenge and lays the foundation for future developments, including the application of machine learning to enhance matching precision.