Enhancing Operating Room Efficiency: The Impact of Computational Algorithms on Surgical Scheduling and Team Dynamics

Background/Objectives: Operating room (OR) efficiency is a critical factor in healthcare delivery, influenced by various components including surgical duration, room turnover, staff availability, and equipment preparation. Optimizing surgical start times through systematic strategies such as computational algorithms can significantly enhance OR utilization and management. This study aimed to improve OR efficiency by effectively managing and optimizing surgical start times using a computational algorithm designed to allocate resources more efficiently. Methods: A comparative analysis was conducted over two six-month periods from January to June 2023 and January to June 2024, with an improvement phase implemented between July and December 2023. Results: These measures encompassed training surgical personnel, strengthening the medical team, revising work procedures and hospital regulations, and the integration of a computational algorithm to better schedule and manage surgical interventions. Following the implementation of these comprehensive measures, enhanced management of surgical start times was observed. A statistically significant increase in surgical interventions between 8 and 10 a.m. was noted for the entire OR, rising from 28.65% to 32.13%. While OR occupancy between 8 and 12 a.m. increased from 63.91% to 73.30%, this difference was not statistically significant. However, a notable improvement in average occupancy between 9 and 11 a.m. was observed, rising from 87.53% to 98.07%. Conclusions: The introduction of computational algorithms significantly improved operating room efficiency, particularly in managing surgical start times. Additionally, team coordination improved as a result of more structured scheduling processes. The results indicate that effective management of surgical start times, especially when enhanced by computational algorithms, can positively impact OR utilization, particularly within specific time blocks.