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Related Experiment Video

Updated: Jun 6, 2026

Emergency Undocking in Robotic Surgery: A Simulation Curriculum
06:48

Emergency Undocking in Robotic Surgery: A Simulation Curriculum

Published on: May 20, 2018

National Emergency Department Overcrowding Scale as a Predictor for Running an In-Situ Simulation.

Alexander Croft1, Christian Gerhart1, Daniel Suarez1

  • 1Emergency Medicine, Washington University School of Medicine, St. Louis, USA.

Cureus
|June 5, 2026
PubMed
Summary
This summary is machine-generated.

The National Emergency Department Overcrowding Scale (NEDOCS) can predict in-situ simulation (ISS) cancellations. Higher NEDOCS scores eight hours before simulation start significantly correlate with cancellations, enabling better resource allocation.

Keywords:
clinical operationsemergency medicineemergency medicine informaticshealthcare simulationin-situ simulation

Related Experiment Videos

Last Updated: Jun 6, 2026

Emergency Undocking in Robotic Surgery: A Simulation Curriculum
06:48

Emergency Undocking in Robotic Surgery: A Simulation Curriculum

Published on: May 20, 2018

Area of Science:

  • Healthcare Operations
  • Medical Simulation
  • Emergency Medicine

Background:

  • In-situ simulation (ISS) is vital for team training and identifying safety threats.
  • Operational constraints, like Emergency Department (ED) overcrowding, frequently lead to simulation cancellations.
  • Objective measures are needed to predict ISS cancellations and optimize resource allocation.

Purpose of the Study:

  • To investigate the National Emergency Department Overcrowding Scale (NEDOCS) as an objective predictor of ISS cancellation.
  • To determine if NEDOCS scores can forecast the need to cancel simulations due to ED overcrowding.

Main Methods:

  • Retrospective observational cohort study in an urban, quaternary ED.
  • Comparison of mean NEDOCS scores on days with ISS cancellations (No Go) versus days without cancellations (Go).
  • Statistical analysis using two-tailed t-tests and point-biserial Pearson correlation at various time points before ISS start.

Main Results:

  • A statistically significant higher mean NEDOCS was observed eight hours prior to ISS start on cancellation days (160.6 vs 121.4, p=0.011).
  • A moderate negative correlation (r=-0.61) was found between NEDOCS at T-minus-eight hours and simulation cancellation (Go/No Go).
  • Overall correlation between NEDOCS and Go/No Go status was -0.42 (p=0.0006).

Conclusions:

  • NEDOCS scores show a statistically significant association with ISS cancellations.
  • Elevated NEDOCS eight hours before simulation may indicate a higher likelihood of cancellation, aiding proactive rescheduling.
  • Utilizing NEDOCS can improve the efficiency of time and resource allocation for ISS programs.