Dataset Information

Just-in-Time Simulation to Guide Workflow Design for Coronavirus Disease 2019 Difficult Airway Management.

ABSTRACT:

Objectives

The coronavirus disease 2019 pandemic has required that hospitals rapidly adapt workflows and processes to limit disease spread and optimize the care of critically ill children.

Design and setting

As part of our institution's coronavirus disease 2019 critical care workflow design process, we developed and conducted a number of simulation exercises, increasing in complexity, progressing to intubation wearing personal protective equipment, and culminating in activation of our difficult airway team for an airway emergency.

Patients and interventions

In situ simulations were used to identify and rework potential failure points to generate guidance for optimal airway management in coronavirus disease 2019 suspected or positive children. Subsequent to this high-realism difficult airway simulation was a real-life difficult airway event in a patient suspected of coronavirus disease 2019 less than 12 hours later, validating potential failure points and effectiveness of rapidly generated guidance.

Measurements and main results

A number of potential workflow challenges were identified during tabletop and physical in situ manikin-based simulations. Experienced clinicians served as participants, debriefed, and provided feedback that was incorporated into local site clinical pathways, job aids, and suggested practices. Clinical management of an actual suspected coronavirus disease 2019 patient with difficult airway demonstrated very similar success and anticipated failure points. Following debriefing and assembly of a success/failure grid, a coronavirus disease 2019 airway bundle template was created using these simulations and clinical experiences for others to adapt to their sites.

Conclusions

Integration of tabletop planning, in situ simulations, and debriefing of real coronavirus disease 2019 cases can enhance planning, training, job aids, and feasible policies/procedures that address human factors, team communication, equipment choice, and patient/provider safety in the coronavirus disease 2019 pandemic era.

SUBMITTER: Daly Guris RJ

PROVIDER: S-EPMC7288785 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe aim of this study was to evaluate how anaesthesiologists manage a "cannot intubate, can ventilate" (CI) and "cannot intubate, cannot ventilate" (CICV) scenarios, and how following simulation training will affect their guideline adherence, skills and decision-making immediately after training and 6 months later.MethodsA prospective controlled study was conducted from July to December 2022. Anaesthesiologists who applied for the continuous medical education course "Difficult Airway Management" were involved in the study. Each volunteer participated in two simulation scenarios (CI, CICV) with structural debriefing after each scenario. After the first simulation round, volunteers were trained in difficult airway management according to DAS guidelines, using the same equipment as during the simulation. The participants repeated the simulation scenarios the day after the training and six months later. The primary and secondary endpoints were compared between three rounds: initial simulation (Group 1), immediately after training (Group 2), and six months after training (Group 3).ResultsA total of 24 anaesthesiologists consented to participate in the study and completed the initial survey form. During the first session, 83.3% of participants had at least one major deviation from the DAS protocol. During the first CICV scenario, 79% of participants made at least one deviation from the DAS protocol. The second time after simulation training, significantly better results were achieved: the number of anaesthesiologists, who attempted more than 3 laryngoscopies decreased (OR = 7 [1.8-26.8], p = 0.006 right after training and OR = 3.9 [1.06-14.4], p = 0.035 6 month later); the number, who skipped the supralaryngeal device attempt, call for help and failure to initiate surgical airway also decreased. Simulation training also significantly decreases the time to call for help, cricothyroidotomy initiation time, and mean desaturation time and increases the odds ratio of successful cricothyroidotomy (OR 0.02 [0.003-0.14], p < 0.0001 right after training and OR = OR 0.02 [0.003-0.16] 6 months after training).ConclusionsAnaesthesiologists usually display major deviations from DAS guidelines while managing CI and CICV scenarios. Simulation training improves their guideline adherence, skills, and decision-making when repeating the simulation immediately after training and 6 months later.Study registrationNCT05913492, clinicaltrials.gov, 22/06/2023.