In Situ Simulation as a Quality Improvement Tool to Identify and Mitigate Latent Safety Threats for Emergency Department SARS-CoV-2 Airway Management: A Multi-Institutional Initiative

Jt Comm J Qual Patient Saf. 2023 Jun-Jul;49(6-7):297-305. doi: 10.1016/j.jcjq.2023.02.005. Epub 2023 Feb 24.

Abstract

Background: In situ simulation has emerged as a powerful quality improvement (QI) tool in the identification of latent safety threats (LSTs). Following the first wave of SARS-CoV-2 at an urban epicenter of the disease, a multi-institutional collaborative was formed to integrate an in situ simulation protocol across five emergency departments (EDs) for systems improvement of acute airway management.

Methods: A prospective, multi-institutional QI initiative using two Plan-Do-Study-Act (PDSA) cycles was implemented across five EDs. Each institution conducted simulations involving mannequins in acute respiratory failure requiring definitive airways. Simulations and systems-based debriefs were standardized. LSTs were collected in an online database, focused on (1) equipment availability, (2) infection control, and (3) communication.

Results: From June 2020 through May 2021, 58 of 70 (82.9%) planned simulations were completed across five sites with 328 unique individual participants. Overall LSTs per simulation (7.00-4.69, p < 0.001) and equipment LSTs (3.00-1.46, p < 0.001) decreased from cycle 1 to cycle 2. Changes in mean LSTs for infection control and communication categories varied among sites. There was no correlation between total LSTs or any of the categories and team size. Number of beds occupied was significantly negatively correlated with total and infection control LSTs.

Conclusion: This study was unique in simultaneously running a structured in situ protocol across numerous diverse institutions during a global pandemic. This initiative found similar categories of threats across sites, and the protocol developed empowered participants to implement changes to mitigate identified threats.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • COVID-19*
  • Emergency Service, Hospital
  • Humans
  • Prospective Studies
  • Quality Improvement
  • SARS-CoV-2*