Obuseh & Yu Develop Sensor-Based Framework for use in Operating Rooms
Marian Obuseh and Denny Yu were recently awarded the Work Systems Best Track Paper at the 2023 IISE Annual Conference and Expo.
Denny Yu, Associate Professor of Industrial Engineering
Marian Obuseh, a PhD student in the School of Industrial Engineering, and Denny Yu, Associate Professor in the School of IE, were recently awarded the Work Systems Best Track Paper at the 2023 IISE Annual Conference and Expo. Their paper, titled “A sensor-based framework for layout and workflow assessment in operating rooms” explores the obstacles posed by integrating robotic technologies in the operating room.
The benefits of technology in the operating room (OR) are proving to be more widely appreciated and incorporated. Higher visualization and dexterity in surgeries has the potential to revolutionize patient care, however, incorporating this technology into common workflows can be challenging. This technology is quite sizable, and most ORs are not designed to easily integrate large robotic systems as they are often already crowded with personnel and equipment.
The paper outlines a sensing framework for layout and workflow assessment within the OR. Designed and tested on 15 robotic-assisted surgeries (RAS), data from 12 of these surgeries helped define recommendations and best practices for the proper implementation of the framework. Focusing on the distance covered by personnel, areas of congestion within the OR, and proximity of personnel and equipment, recommendations for evaluating surgical workflows were suggested.
This research aims to aid the integration of robotic technologies in ORs. Assessing and prioritizing workflows and efficiencies will help the design of OR layouts for better use of space, personnel, and other resources.
Obuseh, M., Cavuoto, L., Stefanidis, D., & Yu, D. (2023). A sensor-based framework for layout and Workflow Assessment in Operating Rooms. Applied Ergonomics, 112. https://doi.org/10.1016/j.apergo.2023.104059