UC-Butterfly Healthcare co-funded PhD scholarship

Surgical consignment and loan management are pivotal yet complex processes in hospital operations. These workflows involve managing prostheses, surgical trays, and instruments placed at hospitals without immediate purchase and stock ownership transfer, necessitating meticulous inventory tracking, usage monitoring, and timely supplier payments. Traditional methods face significant challenges, including inaccurate consignment and loan records, a lack of understanding of what is required for each surgery at the patient level, and inefficient supplier coordination. These challenges can lead to stockouts, overstocking, increased costs, and potential risks to patient safety. This research project is motivated by applying computer vision technology to address these inefficiencies. Our innovative approach harnesses novel computer vision algorithms and real-time data acquisition to enhance the accuracy and efficiency of managing surgical consignments and loans. By integrating these advanced technologies, the project aims to provide solutions that improve inventory management, forecast material requirements, and validate processes to reduce human error. This research aims to explore and advance computer vision techniques that can transform the handling of surgical supplies consignment and loan management. This includes developing systems that precisely track consignment and loan surgical materials, streamline workflows, and enhance overall operational efficiency. The outcomes of this research are expected to significantly advance the surgical consignment and loan management field significantly, offering improved patient safety, operational efficiency, and accuracy in healthcare settings. The complete research proposal is attached as a separate document to this agreement.