Robotics: Science and Systems XII

Robotic Assistance in Coordination of Patient Care

Matthew Gombolay, Xi Jessie Yang, Brad Hayes, Nicole Seo, Zixi Liu, Samir Wadhwania, Tania Yu, Neel Shah, Toni Golen, Julie Shah


We conducted a study to investigate trust in and dependence upon robotic decision support among nurses and doctors on a labor and delivery floor. There is evidence that suggestions provided by embodied agents engender inappropriate degrees of trust and reliance among humans. This concern is a critical barrier that must be addressed before fielding intelligent hospital service robots that take initiative to coordinate patient care. Our experiment was conducted with nurses and physicians, and evaluated the subjects’ levels of trust in and dependence on high- and low-quality recommendations issued by robotic versus computer-based decision support. The support, generated through action-driven learning from expert demonstration, was shown to produce high-quality recommendations that were ac- cepted by nurses and physicians at a compliance rate of 90%. Rates of Type I and Type II errors were comparable between robotic and computer-based decision support. Furthermore, em- bodiment appeared to benefit performance, as indicated by a higher degree of appropriate dependence after the quality of recommendations changed over the course of the experiment. These results support the notion that a robotic assistant may be able to safely and effectively assist in patient care. Finally, we conducted a pilot demonstration in which a robot assisted resource nurses on a labor and delivery floor at a tertiary care center.



    AUTHOR    = {Matthew Gombolay AND Xi Jessie Yang AND Brad Hayes AND Nicole Seo AND Zixi Liu AND Samir Wadhwania AND Tania Yu AND Neel Shah AND Toni Golen AND Julie Shah}, 
    TITLE     = {Robotic Assistance in Coordination of Patient Care}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2016}, 
    ADDRESS   = {AnnArbor, Michigan}, 
    MONTH     = {June}, 
    DOI       = {10.15607/RSS.2016.XII.026}