Related Experiment Video
Updated: Apr 25, 2026
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Challenges to measuring variation in readmission rates of neonatal intensive care patients
Scott A Lorch1, Molly Passarella2, Ashley Zeigler2
1Department of Pediatrics, The Children's Hospital of Philadelphia and Perelman School of Medicine at The University of Pennsylvania, Philadelphia, Pa; Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, Pa; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pa.
Insights
Hospital readmission rates for infants in neonatal intensive care units (NICUs) vary significantly, suggesting potential quality differences. Improved data collection is needed for accurate multistate comparisons of NICU care quality.
Area of Science:
- Neonatal intensive care
- Healthcare quality metrics
- Pediatric readmission analysis
Background:
- Assessing hospital quality for infants requiring neonatal intensive care (NICU) is crucial.
- Existing data limitations hinder comprehensive evaluation of NICU care quality across different regions.
Purpose of the Study:
- To evaluate the feasibility of using hospital readmission rates as a quality metric for infants admitted to the NICU.
- To identify variations in readmission rates and assess the impact of risk adjustment.
Main Methods:
- Constructed two cohorts: California infants (1995-2009) and Medicaid-enrolled infants in 18 states (2006-2008).
- Utilized birth certificates, inpatient records, and Medicaid Analytic eXtract (MAX) data.
- Calculated hospital and state-level readmission rates, adjusting for factors like gestational age and birth weight.
Main Results:
- Significant hospital-level variation in readmission rates was observed in California, even after risk adjustment.
- Multistate comparisons using MAX data showed unadjusted variation, but risk adjustment was limited by missing data.
- Data limitations in MAX prevented calculation of hospital-level rates in most states.
Conclusions:
- Risk-adjusted readmission rates in California suggest potential for reflecting NICU care quality.
- Current state-level data are insufficient for comprehensive, multistate NICU quality assessment.
- Enhanced data collection and linkage are necessary to develop a valid readmission quality metric for NICU infants.
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.
Related Concept Videos
01:29Nursing Interventions II: Selecting and Classifying the Nursing Interventions
01:20Assessment of Ventilation I: Respiratory Rate
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:
01:19Guidelines For Measuring Vital Signs
Before taking a patient's vital signs, a nurse would consider and assess the patient's comfort level and ensure appropriate equipment is available.
01:11Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
01:52Regression Toward the Mean
01:10Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...