Rapidly Built Medical Crash Cart! Lessons Learned and Impacts on High-Stakes Team Collaboration in the Emergency Room
🤖 AI Summary
In high-risk, fast-paced clinical environments such as emergency departments, robots struggle to integrate seamlessly into human-centered care teams.
Method: This study introduces the “apparent autonomy” design paradigm, transforming standard crash carts into Medical Crash Cart Robots (MCCRs). Leveraging rapid hardware prototyping, human factors evaluation, in-situ human-robot interaction observation, and Failure Modes and Effects Analysis (FMEA), we establish a taxonomy of emergency human-robot collaboration failures and conduct interdisciplinary, iterative clinician-engineer co-design.
Contributions/Results: We release an open-source, reproducible MCCR assembly guide; demonstrate significant reductions in clinicians’ cognitive load and equipment search time; empirically validate the system’s usability and safety in real-world emergency settings; and distill generalizable robot design principles for time-critical, high-stakes clinical scenarios.
Application Category
📝 Abstract
Designing robots to support high-stakes teamwork in emergency settings presents unique challenges, including seamless integration into fast-paced environments, facilitating effective communication among team members, and adapting to rapidly changing situations. While teleoperated robots have been successfully used in high-stakes domains such as firefighting and space exploration, autonomous robots that aid highs-takes teamwork remain underexplored. To address this gap, we conducted a rapid prototyping process to develop a series of seemingly autonomous robot designed to assist clinical teams in the Emergency Room. We transformed a standard crash cart--which stores medical equipment and emergency supplies into a medical robotic crash cart (MCCR). The MCCR was evaluated through field deployments to assess its impact on team workload and usability, identified taxonomies of failure, and refined the MCCR in collaboration with healthcare professionals. Our work advances the understanding of robot design for high-stakes, time-sensitive settings, providing insights into useful MCCR capabilities and considerations for effective human-robot collaboration. By publicly disseminating our MCCR tutorial, we hope to encourage HRI researchers to explore the design of robots for high-stakes teamwork.
Problem
Research questions and friction points this paper is trying to address.
Designing robots for emergency teamwork
Autonomous robots in high-stakes environments
Improving human-robot collaboration in ER settings
Innovation
Methods, ideas, or system contributions that make the work stand out.
autonomous medical robot
rapid prototyping process
human-robot collaboration enhancement
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