Improving Newborn Resuscitation by Making Every Birth a Learning Event.
Kourtney BettingerEric MafutaAmy MackayCarl BoseHelge MyklebustIngunn HaugDaniel Katuashi IshosoJacquelyn K PattersonPublished in: Children (Basel, Switzerland) (2021)
One third of all neonatal deaths are caused by intrapartum-related events, resulting in neonatal respiratory depression (i.e., failure to breathe at birth). Evidence-based resuscitation with stimulation, airway clearance, and positive pressure ventilation reduces mortality from respiratory depression. Improving adherence to evidence-based resuscitation is vital to preventing neonatal deaths caused by respiratory depression. Standard resuscitation training programs, combined with frequent simulation practice, have not reached their life-saving potential due to ongoing gaps in bedside performance. Complex neonatal resuscitations, such as those involving positive pressure ventilation, are relatively uncommon for any given resuscitation provider, making consistent clinical practice an unrealistic solution for improving performance. This review discusses strategies to allow every birth to act as a learning event within the context of both high- and low-resource settings. We review strategies that involve clinical-decision support during newborn resuscitation, including the visual display of a resuscitation algorithm, peer-to-peer support, expert coaching, and automated guidance. We also review strategies that involve post-event reflection after newborn resuscitation, including delivery room checklists, audits, and debriefing. Strategies that make every birth a learning event have the potential to close performance gaps in newborn resuscitation that remain after training and frequent simulation practice, and they should be prioritized for further development and evaluation.
Keyphrases
- cardiac arrest
- cardiopulmonary resuscitation
- septic shock
- clinical practice
- primary care
- depressive symptoms
- clinical decision support
- machine learning
- healthcare
- deep learning
- public health
- cardiovascular disease
- type diabetes
- virtual reality
- physical activity
- intensive care unit
- risk factors
- high throughput
- metabolic syndrome
- adipose tissue
- cardiovascular events
- glycemic control
- insulin resistance
- mechanical ventilation
- respiratory failure