Using hospital discharge data for determining neonatal morbidity and mortality: a validation study

BACKGROUND: Despite widespread use of neonatal hospital discharge data, there are few published reports on the accuracy of population health data with neonatal diagnostic or procedure codes. The aim of this study was to assess the accuracy of using routinely collected hospital discharge data in identifying neonatal morbidity during the birth admission compared with data from a statewide audit of selected neonatal intensive care (NICU) admissions. METHODS: Validation study of population-based linked hospital discharge/birth data against neonatal intensive care audit data from New South Wales, Australia for 2,432 babies admitted to NICUs, 1994–1996. Sensitivity, specificity and positive predictive values (PPV) with exact binomial confidence intervals were calculated for 12 diagnoses and 6 procedures. RESULTS: Sensitivities ranged from 37.0% for drainage of an air leak to 97.7% for very low birthweight, specificities all exceeded 85% and PPVs ranged from 70.9% to 100%. In-hospital mortality, low birthweight (≤1500 g), retinopathy of prematurity, respiratory distress syndrome, meconium aspiration, pneumonia, pulmonary hypertension, selected major anomalies, any mechanical ventilation (including CPAP), major surgery and surgery for patent ductus arteriosus or necrotizing enterocolitis were accurately identified with PPVs over 92%. Transient tachypnea of the newborn and drainage of an air leak had the lowest PPVs, 70.9% and 83.6% respectively. CONCLUSION: Although under-ascertained, routinely collected hospital discharge data had high PPVs for most validated items and would be suitable for risk factor analyses of neonatal morbidity. Procedures tended to be more accurately recorded than diagnoses.