Analysis and classification of errors made by teams during neonatal resuscitation

Area of Science:

• Medical Resuscitation
• Neonatal Care
• Patient Safety

Background:

• The Neonatal Resuscitation Program (NRP) algorithm guides care for newborns transitioning to life outside the womb.
• Despite its importance, adherence to the NRP algorithm is challenging, leading to frequent errors.
• Error classification in high-risk fields like air traffic control aids recognition and remediation.

Purpose of the Study:

• To determine and characterize common deviations from the NRP algorithm during neonatal resuscitation.
• To identify specific errors in neonatal resuscitation procedures.
• To inform strategies for improving neonatal resuscitation safety and effectiveness.

Main Methods:

• Analysis of 23 complex neonatal resuscitations from 250 audiovisual recordings.
• Assessment of adherence to the NRP algorithm using a validated NRP Megacode Checklist.
• Classification of observed errors using a novel scoring tool.

Main Results:

• Observed 780 algorithm-driven tasks with an overall error rate of 23% (194 incorrect tasks).
• Errors of commission (72%) were more frequent than errors of omission (28%).
• Common errors included failure to assess heart rate, improper ventilation pressures and rates, incorrect chest compression technique, and asynchronous ventilation and compressions.

Conclusions:

• Errors of commission during advanced life support interventions (ventilation, intubation, chest compressions) are frequent and pose potential harm.
• Healthcare should consider adopting error reduction strategies from other industries to decrease cognitive and technical load.
• Standardizing communication and implementing error reduction strategies are crucial for improving neonatal resuscitation outcomes.