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Dr. May Sissel Vadla (MD)

Simulation-based training and data-guided feedback for neonatal resuscitation in rural Tanzania

Dr. May Sissel Vadla (MD)

UiS Brage: Simulation-based training and data-guided feedback for neonatal resuscitation in rural Tanzania (

Background: Globally, 1.4 million newborns die every year due to intrapartum related events and fresh stillbirths, nearly all occurring in low and middle-income countries. Many of these deaths could be prevented if the non-breathing newborns received skilled and timely bag-maskventilation at birth. Neonatal resuscitation guidelines recommend onset of bag-mask ventilation for non-breathing newborns within the first minute of life, the so-called Golden Minute. Guideline adherence for timely ventilation is challenging in clinical practice, and a multi-country study demonstrated that less than one percent of newborns were ventilated within the Golden Minute. The Helping Babies Breathe educational program improves knowledge and simulated skills in neonatal resuscitation. However, two systematic reviews found no overall difference in stimulation, suctioning, or bag-mask ventilation after implementation of the program, demonstrating the challenge of translating improved training-skills into clinical practice. The Helping Babies Breathe 2nd Edition addresses the challenges regarding program implementation and achievement of sustainable results.

Aim: The overall aim of the thesis was to investigate the effects of several quality improvement/simulation-based training interventions, on simulation-based training performance, clinical practice, and perinatal outcome.

Conclusion: This thesis demonstrates translation of simulated ventilation skills to enhanced clinical resuscitation performance, and ultimately improved patient outcome. Improvement of the time-critical procedure of rapid onset of bag-mask ventilation, required data-guided scenario trainings led by qualified facilitators, in combination with a broader quality improvement effort, including provision of feedback from clinical data at quality improvement meetings.