With increasing emphasis on high “value” care, we designed this study to evaluate the relationship between hospital costs and patient outcomes in pediatric critical care.Design:
Post hoc analysis of data from an existing administrative national database, Pediatric Health Information Systems. Multivariable mixed effects logistic regression models were fitted to evaluate association of hospital cost tertiles with odds of mortality after adjusting for patient and center characteristics.Setting:
Forty-seven children’s hospitals across the United States.Patients:
Patients 18 years old or younger admitted to a PICU at a Pediatric Health Information Systems participating hospital were included (2004–2015).Interventions:
None.Measurements and Main Results:
A total of 917,663 patients from 47 hospitals were included. Median cost per patient was $42,181 in the low-cost hospitals (341,689 patients, 16 hospitals), $56,806 in the middle-cost hospitals (310,293 patients, 16 hospitals), and $82,588 in the high-cost hospitals (265,681 patients, 15 hospitals). In unadjusted analysis, patients cared for in the high-cost tertile hospitals were younger in age, associated with more comorbidities, had higher resource utilization (including extracorporeal membrane oxygenation and nitric oxide), had higher prevalence of cardiac arrest, and were associated with worse outcomes (including mortality). In adjusted analysis, high-cost tertile hospitals were not associated with improved mortality, when compared with low- and medium-cost tertile hospitals (low cost vs high cost: odds ratio, 0.99; 95% CI, 0.79–1.25 and middle cost vs high cost: odds ratio, 1.10; 95% CI, 0.86–1.41). When stratified by diagnoses category, we noted similar trends among cardiac and noncardiac patients.Conclusions:
This large observational study did not demonstrate any relationship between hospital costs and patient outcomes in children with critical illness. Further efforts are needed to evaluate quality-cost relationship and high value care in critically ill children across centers of varying volume by linking data from clinical and administrative databases.