Monitoring the quality of maternity care: how well are labour and delivery events reported in population health data?

Administrative or population health data sets (PHDS), such as birth and hospital discharge data, are used increasingly to evaluate maternity care. Use of PHDS requires reliable identification of diagnoses and procedures. The aim of this study was to determine the accuracy and reliability of the reporting of diagnoses and procedures related to childbirth in both individual and linked, birth and ICD10-coded hospital discharge data. Data from a population-based validation study of 1200 women provided the 'gold standard' for labour and delivery events and were compared with the hospital discharge and birth databases. Reporting characteristics (sensitivity, specificity, positive and negative predictive values) were determined for: induction, augmentation and obstruction of labour, modes of delivery (including failed instrumental delivery), episiotomy, perineal tears and repairs, and manual removal of the placenta. Differences in reporting by mode of delivery were also examined. Of the 1184 records available for review, 25% had labour induced, 25% had labour augmented and, of those who laboured, 17% had obstructed labour reported. Fourteen per cent had an elective/planned caesarean section (CS) including 2% that went into labour prior to the planned date, and 11% had an emergency, unplanned CS including 2% who had no labour. With the exception of augmentation and obstruction of labour, failed instrumental delivery and manual removal, there were high levels of accuracy for reporting of diagnoses and procedures during labour and delivery. There were no significant differences in reporting by mode of delivery. The findings suggest that PHDS-reported induction of labour, mode of delivery, and 3rd and 4th degree tears and repairs can be reliably used to evaluate maternity care. Consistency in reporting in birth and hospital discharge data from different countries and over time suggests the findings are likely to be generalisable to high-income countries.