Robotic assistance in the coordination of patient care
Name
Gombolay_RSS_2016.pdf
Description
Accepted version
Size
5.86 MB
Format
Adobe PDF
Checksum (MD5)
e5978f9e7fbdf11672c9a1caf6870131
Author(s)
Gombolay, Matthew C.
Hayes, Bradley H
Seo, Nicole
Liu, Zixi
Wadhwania, Samir
Yu, Tania W.
Shah, Neel
Golen, Toni
Shah, Julie A
Date Issued
June 2018
Journal
International Journal of Robotics Research
Publisher
SAGE Publications
Citation
Gombolay, Matthew et al. "Robotic assistance in the coordination of patient care." International Journal of Robotics Research 37, 10 (September 2018): 1300-1316 © 2018 The Author(s).
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 represents a critical barrier that must be addressed before fielding intelligent hospital service robots that take initiative to coordinate patient care. We conducted our experiment with nurses and physicians, and evaluated the subjects’ levels of trust in and dependence upon high- and low-quality recommendations issued by robotic versus computer-based decision support. The decision support, generated through action-driven learning from expert demonstration, produced high-quality recommendations that were accepted 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, embodiment 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 with 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
Lincoln Laboratory
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1177/0278364918778344
