ORLIX (Operating Room Logistics & Intelligent eXecution)：ORLIX (Operating Room Logistics & Intelligent eXecution) Platform: As the demand for medical services continues to grow, efficient management of the operating room (OR) has become crucial for hospitals to enhance medical quality and operational effectiveness. In our "Operating Room Logistics & Intelligent eXecution (ORLIX)" project, we utilized advanced artificial intelligence technology and discrete event simulation methods to optimize OR resource allocation and scheduling decisions. This initiative successfully improved the management efficiency of the operating rooms, achieving a win-win situation for both medical quality and resource performance. This innovative system has brought significant benefits to the hospital's OR operations and effectively supports AI-enhanced surgical planning and assistance.
This project aimed to address the challenges faced in hospital OR management, particularly concerning the efficiency of surgical scheduling and resource allocation. With continuous advancements in medical technology and rising patient expectations for service quality, hospitals must not only tackle difficulties in resource deployment but also maintain the quality of patient care. To this end, our hospital employed discrete event simulation technology and a decision support system. By simulating various surgical scheduling and room allocation scenarios, we helped hospital administrators develop more scientific and effective surgical scheduling plans, thereby optimizing OR management.
The core of this project lies in using AI technology for comprehensive simulation and prediction of OR operations. Through the AI-assisted surgical scheduling system, the hospital can more accurately assess the utilization efficiency of operating rooms, analyze the actual impact of different scheduling methods on surgical resources, and predict surgical performance under various configuration scenarios. The application of these technologies enables the hospital to adapt quickly in a highly variable medical environment, enhance surgical efficiency, reduce waiting times, and optimize resource allocation, thus effectively improving the quality of patient care.
Following the system's implementation, our hospital's surgical scheduling efficiency significantly improved. The average number of overtime surgeries decreased from 8.7 to 6.6 cases, and the number of operating rooms running overtime decreased from 5.4 to 4.2 rooms, markedly reducing resource idling and excessive overtime. The system also supports multiple scheduling methods, including an innovative "dedicated scheduling for emergency surgeries," which effectively addresses the challenges of unexpected surgeries, ensuring timely handling of emergency procedures and achieving an optimal balance between medical quality and operational efficiency. Furthermore, the system's quantitative data analysis and simulation scenario design make surgical scheduling more visual and actionable, assisting hospital management in making data-driven decisions and effectively enhancing the quality and efficiency of medical services.
Through the introduction of AI technology and the application of the discrete event simulation system, this project successfully resolved several core issues in hospital operating room management. It not only enhanced scheduling efficiency and resource utilization but also substantially improved the quality of patient care and provided a more relaxed working environment for medical staff. The successful implementation of this system has ushered in a new era for hospital OR operational management and provides valuable experience for the future application of AI technology in smart hospitals. This achievement undoubtedly represents a significant breakthrough for our hospital in the field of "AI-enhanced surgical planning and assistance" and makes a positive contribution to the development of smart healthcare.
