Robotic Assistance in Coordination of Patient Care
Name
Gombolay_RSS_2016.pdf
Size
5.86 MB
Format
Adobe PDF
Checksum (MD5)
e5978f9e7fbdf11672c9a1caf6870131
Author(s)
Shah, Neel
Golen, Toni
Gombolay, Matthew C.
Yang, Xi
Hayes, Bradley H
Seo, Nicole
Liu, Zixi
Wadhwania, Samir
Yu, Tania W.
Shah, Julie A
Date Issued
2016
Journal
Robotics: Science and Systems XII
Publisher
MIT Press
Citation
Gombolay, Matthew et al. “Robotic Assistance in Coordination of Patient Care.” Robotics: Science and Systems XII June 18-22 2016, Ann Arbor, Michigan, USA, MIT Press, 2016
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.15607/RSS.2016.XII.026
