Linkage of routinely collected health data collections is increasingly being used to investigate maternal and infant morbidity and mortality. Such data have the advantage of being population based and readily available. However, in using such data it is important to understand the data linkage process, the proportions of unmatched records and the characteristics of these records so that potential bias can be recognised. This article describes the differences in characteristics of matched and unmatched mothers’ and babies’ records generated in the linkage of birth records with hospital discharge data and explores some of the reasons for these differences. The study population included over 250 000 women and their babies discharged from hospital following delivery in New South Wales, Australia between 1 January 2000 and 31 December 2002.
Hospital discharge and birth data were linked using probabilistic linkage methods for both mothers and babies. Matching rates were 98.5% and 99.0% for maternal birth and hospital discharge records, respectively, and 98.8% and 99.4% for baby records. Unmatched maternal records had higher proportions of Australian-born women, private hospital births and stillbirths compared with matched records. Unmatched baby records had higher proportions of low-birthweight babies, preterm births and in-hospital deaths than matched records. With the possible exception of stillbirths, these differences are unlikely to cause important bias in studies relying on matched records only. Our results suggest studies using linked data should generally examine and report on the characteristics of unmatched records, and recognise them as a potential source of bias.