ASTRID: A Robotic Tutor for Nurse Training to Reduce Healthcare-Associated Infections


Peizhu Qian, Filip Bajraktari, Carlos Quintero-Pena, Qingxi Meng, Shannan Hamlin, Lydia E. Kavraki, Vaibhav V. Unhelkar

Paper ID 90

Session 9. HRI

Poster Session (Day 3): Monday, June 23, 12:30-2:00 PM

Abstract: The central line dressing change is a life-critical procedure performed by nurses to provide patients with rapid infusion of fluids, such as blood and medications. Due to their complexity and the heavy workloads nurses face, dressing changes are prone to preventable errors that can result in central line-associated bloodstream infections (CLABSIs), leading to serious health complications or, in the worst cases, patient death. In the post-COVID-19 era, CLABSI rates have increased, partly due to the heightened nursing workload caused by shortages of both registered nurses and nurse educators. To address this challenge, healthcare facilities and educators are seeking innovative solutions to complement expert nurse educators. In response, we present a robotic tutoring system, Astrid (the Automated Sterile Technique Review and Instruction Device). Astrid is designed to aid in the training of nursing skills essential for CLABSI prevention, which is the outcome of a two-year participatory design process. First, we describe insights gained from interviews with nurse educators and nurses, which revealed the gaps of current training methods and requirements for new training tools. Based on these findings, we outline the development of our robotic tutor, which interacts with nursing students, providing real-time interventions and summary feedback to support skill acquisition. Finally, we present evaluations of the system’s performance and perceived usefulness, conducted in a simulated clinical setting with nurse participants. These evaluations demonstrate the potential of our robotic tutor in nursing education. Our work highlights the importance of participatory design for robotics systems, and motivates new avenues for foundational research in robotics.