Neonatal hypoglycemia algorithms improve hospital outcomes

Objective: Neonatal hypoglycemia is a common diagnosis for which management strategies vary. Our goal was to implement hypoglycemia algorithms (HGA) to streamline management of neonatal hypoglycemia within our hospital system and improve outcomes related to promoting the mother-infant dyad and decreasing hospital costs. Patients and methods: A retrospective cohort study analyzed data on 4,666 asymptomatic infants at risk for hypoglycemia and born at two, large, community hospitals between 2010 and 2016. The first algorithm (HGA1) was created in 2012 and subsequently updated (HGA2) in 2014 to include the use of dextrose gel. Infants were separated into three groups by epoch: pre-HGA (2010–2011), HGA1 (2012–2013), and HGA2 (2014–2016). Outcomes between groups were then analyzed. Cost savings were calculated using linear regression. Results: Compared with the pre-HGA group, the HGA1 group had decreased intravenous dextrose use (3.9 vs. 2.5%, p <.001). Compared with the HGA1 group, the HGA2 group had decreased intravenous dextrose use (2.5 vs. 1.0%, p <.001) and increased breastfeeding rates (88.4% vs. 86.7%, p =.003). Neonatal intensive care unit admission rates decreased when comparing the pre-HGA group with the HGA2 group (10.6% vs 9.4%, p =.03). Length of stay was overall unchanged. Total cost savings were approximately $222 per case. Conclusions: By implementing HGA1 and providing resources to unify care for asymptomatic infants at risk for hypoglycemia, short-term outcomes in our hospital system improved. By updating HGA2 to include the use of dextrose gel, the advantages gained by HGA1 were maintained and further enhanced. Overall cost of care was reduced.