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Related Experiment Video

Updated: May 13, 2026

Development of a Virtual Reality Assessment of Everyday Living Skills
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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.

Simulation in Healthcare : Journal of the Society for Simulation in Healthcare
|January 13, 2025
PubMed
Summary

Virtual Monitor Technicians (VMTs) experienced significantly increased workload during telemetry monitoring, yet their performance remained stable. Future research should focus on improving VMT response accuracy for non-urgent alerts.

Keywords:
Human factorsremote patient monitoringtelemetryvirtual telemetryworkload

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Area of Science:

  • Healthcare Technology
  • Human Factors Engineering
  • Patient Safety

Background:

  • Virtual Monitor Technicians (VMTs) are essential for remote inpatient telemetry monitoring.
  • Little is known about VMT workload, performance fluctuations, and patient safety implications.

Purpose of the Study:

  • To evaluate VMT workload and performance changes over time in a simulated telemetry monitoring environment.
  • To identify research directions for enhancing VMT performance and patient safety.

Main Methods:

  • A high-fidelity simulation replicating remote telemetry stations and documentation was developed.
  • Twelve VMTs participated in a 1-hour session, with workload measured by NASA-Task Load Index and performance assessed via alert detection and escalation times.

Main Results:

  • Workload significantly increased (NASA-TLX score from 38 to 64), driven by mental and temporal demands.
  • VMT performance did not decline, maintaining a 52% correct response rate.
  • Response times varied by alert urgency, with advisory alerts taking significantly longer to recognize.

Conclusions:

  • The study establishes a baseline for VMT workload expectations, showing increased demands without performance degradation.
  • VMTs are most effective with urgent alerts; accuracy for non-urgent alerts requires improvement.
  • Further research is needed to enhance VMT response accuracy beyond the observed 52%.