Challenges to measuring variation in readmission rates of neonatal intensive care patients

Objective: To examine the viability of a hospital readmission quality metric for infants requiring neonatal intensive care.

Methods: Two cohorts were constructed. First, a cohort was constructed from infants born in California from 1995 to 2009 at 23 to 34 weeks' gestation, using birth certificates linked to maternal and infant inpatient records (N = 343,625). Second, the Medicaid Analytic eXtract (MAX) identified Medicaid-enrolled infants admitted to the neonatal intensive care unit (NICU) during their birth hospitalization in 18 states during 2006 to 2008 (N = 254,722). Hospital and state-level unadjusted readmission rates and rates adjusted for gestational age, birth weight, insurance status, gender, and common complications of preterm birth were calculated.

Results: Within California, there were wide variations in hospital-level readmission rates that were not completely explained through risk adjustment. Similar unadjusted variation was seen between states using MAX data, but risk adjustment and calculation of hospital-level rates were not possible because of missing gestational age, birth weight, and birth hospital data.

Conclusions: The California cohort shows significant variation in hospital-level readmission rates after risk adjustment, supporting the premise that readmission rates of prematurely born infants may reflect care quality. However, state data do not include term and early term infants requiring neonatal intensive care. MAX allows for multistate comparisons of all infants requiring NICU care. However, there were extensive missing data in the few states with sufficient information on managed care patients to calculate state-level measures. Constructing a valid readmission measure for NICU care across diverse states and regions requires improved data collection, including potential linkage between MAX data and vital statistics records.