Factors That Contribute to Cost Differences Based on ICU of Admission in Neonates Undergoing Congenital Heart Surgery: A Novel Decomposition Analysis.

OBJECTIVES

We leveraged decomposition analysis, commonly used in labor economics, to understand determinants of cost differences related to location of admission in children undergoing neonatal congenital heart surgery.

DESIGN

A retrospective cohort study.

SETTING

Pediatric Health Information Systems database.

PATIENTS

Neonates (<30 d old) undergoing their index congenital heart surgery between 2004 and 2013.

MEASUREMENTS AND MAIN RESULTS

A decomposition analysis with bootstrapping determined characteristic (explainable by differing covariate levels) and structural effects (if covariates are held constant) related to cost differences. Covariates included center volume, age at admission, prematurity, sex, race, genetic or major noncardiac abnormality, Risk Adjustment for Congenital Heart Surgery-1 score, payor, admission year, cardiac arrest, infection, and delayed sternal closure.Of 19,984 infants included (10,491 [52%] to cardiac ICU/PICU and 9,493 [48%] to neonatal ICU), admission to the neonatal ICU had overall higher average costs ($24,959 ± $3,260; p < 0.001) versus cardiac ICU/PICU admission. Characteristic effects accounted for higher costs in the neonatal ICU ($28,958 ± $2,044; p < 0.001). Differing levels of prematurity, genetic syndromes, hospital volume, age at admission, and infection contributed to higher neonatal ICU costs, with infection rate providing the most significant contribution ($13,581; p < 0.001). Aggregate structural effects were not associated with cost differences for those admitted to the neonatal ICU versus cardiac ICU/PICU (p = 0.1). Individually, prematurity and age at admission were associated with higher costs due to structural effects for infants admitted to the neonatal ICU versus cardiac ICU/PICU.

CONCLUSIONS

The difference in cost between neonatal ICU and cardiac ICU/PICU admissions is largely driven by differing prevalence of risk factors between these units. Infection rate was a modifiable factor that accounted for the largest difference in costs between admitting units.