Abstract
Primary Subject area
Neonatal-Perinatal Medicine
Background
Neonatal Intensive Care Units (NICUs) account for over 35% of pediatric in-hospital clinical costs, thus implying that a better understanding of care expenditures within these units is the first step for improving efficiency of care. The Canadian Neonatal Network (CNN) algorithm is the first to provide case-specific costs based on resource usage among preterm infants born < 37 weeks but has not yet been validated for other populations in the NICU.
Objectives
To validate the CNN costing algorithm in six case-mix categories with real-time costs obtained from hospital-specific financial software (CPSS) in a tertiary-level NICU and assess the variations in proportion of cost centers across case-mixes.
Design/Methods
A retrospective cohort study of all patients admitted within 24h of birth to a Level 3 medico-surgical NICU 2016-2019. Patient demographics, clinical information and CNN predicted costs were obtained from the CNN database. Real-time costs were obtained from the hospital financial software (CPSS). Total and daily costs were compared between sources using Pearson correlation coefficient (r) and paired Student’s t-test. Costs were adjusted to account for inter-institutional and -provincial price variations using the Cost of Standard Hospitalization Stay from the Canadian Institute for Health Information. Proportions of each cost center across the different case-mix categories were compared using Chi-square analyses.
Results
Among the 1795 live infants admitted into the NICU, 167 (9.3%) were < 29 weeks gestational age (GA), 193 (11%) were 29-32 weeks GA, 457 (25.5%) were 33-36 weeks GA, 144 (8%) had major congenital anomalies, 179 (10%) were term infants diagnosed with Hypoxic-Ischemic Encephalopathy (HIE) and 672 (37%) were term infants with no HIE or major congenital anomalies. Median NICU costs varied according to each case-mix from $10,025 for term infants without HIE or congenital anomaly to $180,145 for infants born < 29 weeks (Figure 1). Despite high variation in total NICU costs, there were small variations in median daily costs (range: $1,312-$1,941). Overall, the CNN algorithm strongly correlated with CPSS total costs across all 6 case-mix categories (r range 0.90-1.00, p-value < 0 .01) (Figure 2). We report a consistent strong predictive performance of the algorithm in 5/8 pre-specified cost centers among preterm infants (r range 0.77-0.99, p-value < 0 .01). Unit producing personnel (nurses and physicians) consistently comprised the largest proportion of total costs (64-78%) for all case-mix categories.
Conclusion
The CNN algorithm accurately predicts NICU total costs for six case-mix categories. Costs per day were comparable across different case-mix categories, and unit producing personnel represented the highest proportion of costs suggesting that reductions in length of stay would be the most efficient method to reduce NICU costs.
Antecedents of Using Financial Software Applications on MSME Sustainability in Banyumas Regency during the Covid-19 Pandemic
