Accepted for/Published in: JMIR Nursing
Date Submitted: Mar 16, 2022
Date Accepted: May 7, 2022
Date Submitted to PubMed: Jun 8, 2022
Developing and Testing a Protocol for Managing Cardiopulmonary Resuscitation of Patients with Suspected or Confirmed COVID-19: An In-Situ Simulation Study
ABSTRACT
Background:
Resuscitating patients with suspected or confirmed COVID-19 imposes unique challenges to organizations and code blue teams. Studies that applied the American Heart Association (AHA) COVID-19-related Interim Resuscitation Guideline and similar European guidelines are scarce.
Objective:
This study aimed to develop and test a cardiopulmonary resuscitation (CPR) protocol based on the AHA COVID-19-related Interim Resuscitation Guideline.
Methods:
The study was conducted as an in-situ simulation in a medical intensive care unit. The COVID-19 CPR protocol was created and validated by 11 healthcare team members and was tested using four simulation sessions where 46 code blue team members participated. During the simulation, we observed role clarity, effectiveness of the communication, team dynamics, infection control measures, and availability of essential supplies and equipment.
Results:
The main issues identified in each simulation session were debriefed to the code blue teams and were used to further revise the protocol. These include assignment of tasks, availability of equipment and supplies, and failure of communication between the in-room and out-of-room teams. Solutions included changes in placement of team members and roles and responsibilities; creation of isolation code medication package, a respiratory therapy kit, and isolation code blue bag; and utilization of two-way radios and N-95 with eye goggles to enhance the communication between the teams.
Conclusions:
The study shed the light on challenges to implement the AHA COVID-19-related Interim Resuscitation Guideline. The in-situ simulation was an effective approach for rapid training and identifying unreliable equipment, ineffective and inefficient workflow, and managing the complexity of the physical environment.
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