Hospital variation in admissions to neonatal intensive care units by diagnosis severity and category.

OBJECTIVE: To examine interhospital variation in admissions to neonatal intensive care units (NICU) and reasons for the variation. STUDY DESIGN: 2010-2012 linked birth certificate and hospital discharge data from 35 hospitals in California on live births at 35-42 weeks gestation and ≥1500 g birth weight were used. Hospital variation in NICU admission rates was assessed by coefficient of variation. Patient/hospital characteristics associated with NICU admissions were identified by multivariable regression. RESULTS: Among 276,489 newborns, 6.3% were admitted to NICU with 34.5% of them having mild diagnoses. There was high interhospital variation in overall risk-adjusted rate of NICU admission (coefficient of variation = 26.2) and NICU admission rates for mild diagnoses (coefficient of variation: 46.4-74.0), but lower variation for moderate/severe diagnoses (coefficient of variation: 8.8-14.1). Births at hospitals with more NICU beds had a higher likelihood of NICU admission. CONCLUSION: Interhospital variation in NICU admissions is mostly driven by admissions for mild diagnoses, suggesting potential overuse.

Utility of Birth Certificate Data for Evaluating Hospital Variation in Admissions to NICUs.

OBJECTIVES: Efforts to study potential overuse of NICU admissions and hospital variation in practice are often hindered by a lack of an appropriate data source. We examined the concordance of hospital-level NICU admission rates between birth certificate data and California Children's Services (CCS) data to inform the utility of birth certificate data in studying hospital variation in NICU admissions. METHODS: We analyzed birth certificate data from California in 2012 and hospital-specific summary data from CCS regarding NICU admissions. NICU admission rates were calculated for both data sets while using CCS data as the gold standard. The difference between birth certificate-based and CCS-based NICU admission rates was assessed by using the Wilcoxon signed rank test, and concordance between the 2 rates was evaluated by using Lin's concordance correlation coefficient and Kendall's W concordance coefficient. RESULTS: Among a total of 103 hospitals that were linked between the 2 data sets, birth certificate data generally underreported NICU admission rates compared with CCS data (median = 7.72% vs 11.51%; P < .001). However, in a subset of 35 hospitals where the difference in NICU admission rates between the 2 data sets was small, the birth certificate-based NICU admission rate showed good concordance with the rate from CCS data (Lin's concordance correlation coefficient = 0.91; 95% confidence interval: 0.84-0.95; Kendall's W concordance coefficient = 0.99; P < .001). Hospitals with good-concordance data did not differ from other hospitals in the institutional characteristics assessed. CONCLUSIONS: For a selected subset of hospitals, birth certificate data may offer a reasonable means to investigate hospital variation in NICU admissions.