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Virtual Monitoring Technician Performance in High-Fidelity Simulations of Remote Patient Monitoring: An Exploratory
Harsh Sanghavi1, Yuhao Peng, Emmanuel Tetteh
1From the Department of Human Factors (H.S., Y.P., E.T., L.D.W.), Center for the Simulation, Research, and Patient Safety, Carilion Clinic, Roanoke, VA; and Health Systems and Implementation Science (S.H.P.), Virginia Tech Carilion School of Medicine, Roanoke, VA.
Introduction:
Virtual Monitor Technicians (VMTs) are crucial in remotely monitoring inpatient telemetry. However, little is known about VMT workload and intratask performance changes, and their potential impact on patient safety. This exploratory study used a high-fidelity simulation aimed to evaluate VMTs' workload and performance changes over time in telemetry monitoring and identify future research directions for performance improvement.
Methods:
The research team created a simulation of the current remote telemetry stations with 36 patient waveforms across 3 screens alongside a documentation screen, replicating VMTs' work. Twelve VMTs participated in a 1-hour session, and time-to-escalate and detection accuracy to auditory/visual alerts were recorded. Workload was measured using the NASA-Task Load Index.
Results:
The post-task NASA-Task Load Index score showed an increased workload score of 64 of 100 from a prescore of 38 of 100, with mental and temporal demands being the largest contributors. The performance of VMTs did not change significantly over time, with a 52% correct response rate. Participants' ability to detect signals was slightly better than chance ( d ' = 0.477), and they tended to be cautious in their responses, β ( M = 1.989, SD = 1.635). Urgent, Warning, and Medium audiovisual alerts were recognized in 9, 35, and 39 seconds, respectively, whereas advisory alerts (visual only) were recognized in 13 minutes.
Conclusion:
This study sets a foundation for future work on VMT workload expectations. Although our work is exploratory, the results indicate a significant increase in VMT workload with no decline in performance; VMTs responded most quickly and accurately to urgent alerts, whereas overall response accuracy to nonurgent alerts was marginally better than chance. Future research needs to explore techniques to improve response accuracy rate beyond the 52% measured in this study.
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