In Situ Simulation as a Tool to Longitudinally Identify and Track Latent Safety Threats in a Structured Quality Improvement Initiative for SARS-CoV-2 Airway Management

Abstract

Background:In situ simulation has emerged as a powerful tool for identifying latent safety threats (LSTs). After the first wave of the SARS-CoV-2 pandemic, an urban community emergency department (ED) identified opportunities for improvement surrounding acute airway management and particularly focused on infection control precautions, equipment availability, and interprofessional communication during acute resuscitation. Using the Model for Improvement, a hybrid in situ/quality improvement initiative was implemented using Plan-Do-Study-Act (PDSA) cycles to enhance systems for intubating patients with SARS-CoV-2. Methods: Three PDSA cycles consisting of 10 simulations each were conducted from June 2020 through February 2021. Latent safety threats (LST) were identified through an in situ simulation scenario involving a patient with SARS-CoV-2 in acute respiratory failure. LSTs were collected through structured debriefs focused on (1) infection control, (2) equipment availability, and (3) communication. The SAFER-Matrix was used to score LSTs according to frequency and likelihood of harm by members of the ED QI team (SAFER score). The research team worked with the same QI leaders to implement action plans based on scored threats using cause-and-effect and driver diagrams. The Donabedian model was used to conceptually evaluate the quality of interventions upon conclusion of the third PDSA cycle. Results: The median SAFER score decreased from 10.94 in PDSA cycle 1 to 6.77 in PDSA cycle 2 to 4.71 in PDSA cycle 3. Across all identified LSTs, the SAFER score decreased by 3.114 for every additional PDSA cycle ( P = 0.0167). When evaluating for threats identified as being primarily structure based, there was a decrease in SAFER score of 1.28 per every additional PDSA cycle ( P = 0.001). There was a decrease in total count of LST of 0.20 per additional simulation run ( P = 0.02) after controlling for shift type, census, perceived workload, team size, and prior attendance in simulations across all PDSA cycles. Conclusions: This study presents a blueprint for the utilization of in situ simulation through multiple waves of the SARS-CoV-2 pandemic to identify LSTs and use the SAFER score as a surrogate marker to monitor the impact of interventions for a safer environment for both medical staff and patients.

Stress Testing the Cardiac Catheterization Laboratory

“…In the PDSA process, the “study” section consisted of an evaluation of threats through the development of subcategories. The goal was to perform up to 5 simulations per PDSA round to better understand the trends of LSTs developed; this number was based on what the departments involved considered feasible, as well as our team's experience running ISS in past programs 6 . After each round of up to 5 simulations, the simulation team would review the LSTs identified and organize them into subcategories through group consensus, similar to what has been done in previous studies.…”

“…The goal was to perform up to 5 simulations per PDSA round to better understand the trends of LSTs developed; this number was based on what the departments involved considered feasible, as well as our team's experience running ISS in past programs. 6 After each round of up to 5 simulations, the simulation team would review the LSTs identified and organize them into subcategories through group consensus, similar to what has been done in previous studies. With subcategories identified, after each round, the medical director and nurse manager of the CCL would determine the "likelihood of harm" to a patient (low, medium, high) and the "scope of harm" occurring during that cycle during actual clinical work (limited, pattern, widespread) for plotting on the SAFER-Matrix.…”

“…4 Although resourceful in threat identification, what to do once a threat is identified is underdeveloped in ISS literature, with the only reports describing a structured QI approach toward threat mitigation being the previous work by our team, limited to emergency departments (EDs) and inpatient units. 6 In addition to identifying threats, our team leveraged the Survey Analysis for Evaluating Risk (SAFER-Matrix) developed by the Joint Commission to provide a visual identification of risk levels used to weigh identified LSTs and track them over time based on threat level. 7 With ISS and CCL-specific CAT research in the CCL being underdeveloped, our team's objective was to perform an ISS-based protocol to identify system threats associated with a complex and high-risk environment while also leveraging proven QI tools to weigh, track, and mitigate these threats longitudinally.…”

“…In situ simulation has been leveraged as a powerful quality improvement (QI) tool in identifying latent safety threats (LSTs), which are system-based errors that are previously unrecognized by hospital frontline staff and/or leadership 4 . Although resourceful in threat identification, what to do once a threat is identified is underdeveloped in ISS literature, with the only reports describing a structured QI approach toward threat mitigation being the previous work by our team, limited to emergency departments (EDs) and inpatient units 6 . In addition to identifying threats, our team leveraged the Survey Analysis for Evaluating Risk (SAFER-Matrix) developed by the Joint Commission to provide a visual identification of risk levels used to weigh identified LSTs and track them over time based on threat level 7…”

Validation of a Novel Mobile Application for Assessing Pediatric Tracheostomy Emergency Simulations

“…It can also measure system‐level performance and identify latent safety threats (LSTs), and organizational or environmental issues that make a system more prone to human error. 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 …”