The effect of demographic, financial and hospital factors on the length of stay of preterm infants: a US national database study

• Published in: Journal of perinatology Vol. 44; no. 2; pp. 173 - 178
• Main Authors: Qattea, Ibrahim, Ejaz, Sehar, Kattea, Mohammad O., Kteish, Rayan, Chaudry, Sana, Aly, Hany
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01-02-2024; Nature Publishing Group
• Subjects: 692/699; 692/700; 9/10; Birth rate; Demographics; Demography; Female; Gestational Age; Hospitals; Humans; Infant; Infant, Newborn; Infant, Premature; Infants; Information processing; Length of Stay; Medicine; Medicine & Public Health; Minority & ethnic groups; Neonates; Newborn babies; Pediatric Surgery; Pediatrics; Premature babies; Premature Birth; Resource allocation; Review Article; Socioeconomic factors; Variance analysis; United States > US
• ISSN: 0743-8346; 1476-5543; 1476-5543
• DOI: 10.1038/s41372-023-01836-9

Introduction
Preterm birth is a leading cause for prolonged length of stay (LOS) in the hospital. In the USA, the rate of preterm birth is around 10.5%, thereby contributing substantially to the burden of hospitalization. The interaction of demographic, financial, and hospital factors with LOS of preterm infants has not been studied.
Objective
To assess the effect of demographic, financial, and hospital factors on LOS of surviving preterm infants born at 23 0/7–36 6/7 weeks of gestational age (GA).
Methods
We utilized de-identified patient information from the Healthcare Cost and Utilization Project (HCUP) from 2016–2020. All infants with GA between 23 0/7 and 36 6/7 weeks were identified. ANOVA test was used to assess LOS differences at different GA. Cochran-Armitage test was used for trend analyses.
Results
A total of 1,359,280 surviving premature infants were included in the study. LOS was significantly (
p
 < 0.001) impacted by GA, ethnic group, hospital size and type, and US geographic region. LOS was not affected by sex or type of health insurance.
Conclusion
LOS of preterm infants is significantly affected by multiple demographic factors that are potentially modifiable. These findings can remarkably help policymakers and stakeholders optimize interventions and resource allocations for preterm infants.