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Decreasing birth asphyxia: utility of statistical process control in a low-resource setting
Mariya Mukhtar-Yola1, Lamidi Isah Audu1, Oluyinka Olaniyan2
1Neonatal Unit, Department of Paediatrics, National Hospital Abuja (NHA), Abuja, Nigeria.
Neonatal resuscitation training and equipment improved outcomes for newborns in Nigeria, significantly reducing birth asphyxia incidence. These interventions demonstrate a feasible approach to enhancing perinatal survival in low-resource settings.
Area of Science:
- Neonatal care
- Public health
- Improvement science
Background:
- Neonatal mortality is high in low-resource settings, with birth asphyxia being a major contributor.
- Perinatal events, particularly birth asphyxia, disproportionately affect neonatal survival in developing countries.
Purpose of the Study:
- To reduce the incidence of birth asphyxia by 20% at the National Hospital Abuja, Nigeria.
- To implement and evaluate the impact of neonatal resuscitation training and improved equipment availability.
Main Methods:
- A prospective, longitudinal study utilizing statistical process control (SPC) methods.
- Training of labor and delivery staff on Apgar scoring and neonatal resuscitation techniques.
- Monitoring Apgar scores weekly over 25 months using control charts.
Main Results:
- Baseline incidence of low Apgar scores (<7) was 33% (1 min), 17% (5 min), and 10% (10 min).
- Post-intervention, incidence decreased to 18% (1 min), 17% (5 min), and 6% (10 min), representing a 45% and 40% reduction in 1-min and 10-min low Apgar scores, respectively.
- Sustained improvements in neonatal outcomes were observed.
Conclusions:
- Neonatal resuscitation training and enhanced equipment availability are associated with significant reductions in birth asphyxia.
- Improvement science methods are effective for assessing and improving perinatal outcomes in resource-limited environments.
- The study demonstrates the feasibility and utility of these interventions for wider implementation.
Related Concept Videos
Introduction to Statistical Process Control
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