Abstract

There has been increasing use of hospital discharge data to identify congenital anomalies, with limited information about the accuracy of these data. To evaluate the accuracy of hospital discharge data in ascertaining major congenital anomalies in infants. All liveborn infants with major congenital anomalies born between 2004 and 2009 in New South Wales, Australia were included. They were separated into two study groups: (a) infants identified from the Register of Congenital Conditions with a corresponding record in linked hospital discharge data; and (b) infants with a recorded congenital anomaly in hospital data, but without a register record. For the first group, we assessed agreement (concordant diagnoses) and the proportion of anomalies with discrepant diagnoses in each dataset. For the second group, we determined the number of anomalies recorded only in hospital data and applied specific conditions restricting to those recorded in the birth admission, excluding nonspecific diagnoses, or those with relevant surgical procedures to minimize potential false positives or over-reporting. The first study group included 9,346 infants with an average 84% agreement in the ascertainment of major anomalies between hospital and registry data, and >93% agreement for cardiac, abdominal wall, and gastrointestinal anomalies. Discrepant diagnoses occurred on average in 20% of cases from hospital data and 17% from registry data, and were slightly reduced with the use of diagnoses recorded only in tertiary pediatric hospitals. The second group included 25,893 infants where anomalies were only recorded in hospital data, most commonly skin and unspecified anomalies. Excluding unspecified cases, those only diagnosed at the birth admission and restricting to surgical procedures reduced over-reporting by up to 96%. Hospital discharge data provide an acceptable means to ascertain congenital anomalies, but with variable accuracy for different anomalies. Application of specific conditions and limited to surgical procedures improves the utility of using hospital discharge data to ascertain congenital anomalies.

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