Investigating linkage rates among probabilistically linked birth and hospitalization records

Abstract

Background: With the increasing use of probabilistically linked administrative data in health research, it is important to understand whether systematic differences occur between the populations with linked and unlinked records. While probabilistic linkage involves combining records for individuals, population perinatal health research requires a combination of information from both the mother and her infant(s). The aims of this study were to (i) describe probabilistic linkage for perinatal records in New South Wales (NSW) Australia, (ii) determine linkage proportions for these perinatal records, and (iii) assess records with linked mother and infant hospital-birth record, and unlinked records for systematic differences.

Methods: This is a population-based study of probabilistically linked statutory birth and hospital records from New South Wales, Australia, 2001-2008. Linkage groups were created where the birth record had complete linkage with hospital admission records for both the mother and infant(s), partial linkage (the mother only or the infant(s) only) or neither. Unlinked hospital records for mothers and infants were also examined. Rates of linkage as a percentage of birth records and descriptive statistics for maternal and infant characteristics by linkage groups were determined.

Results: Complete linkage (mother hospital record - birth record - infant hospital record) was available for 95.9% of birth records, partial linkage for 3.6%, and 0.5% with no linked hospital records (unlinked). Among live born singletons (complete linkage = 96.5%) the mothers without linked infant records (1.6%) had slightly higher proportions of young, non-Australian born, socially disadvantaged women with adverse pregnancy outcomes. The unlinked birth records (0.4%) had slightly higher proportions of nulliparous, older, Australian born women giving birth in private hospitals by caesarean section. Stillbirths had the highest rate of unlinked records (3-4%).

Conclusions: This study shows that probabilistic linkage of perinatal records can achieve high, representative levels of complete linkage. Records for mother's that did not link to infant records and unlinked records had slightly different characteristics to fully linked records. However, these groups were small and unlikely to bias results and conclusions in a substantive way. Stillbirths present additional challenges to the linkage process due to lower rates of linkage for lower gestational ages, where most stillbirths occur.

Figure 1

Use of thresholds to minimise false positive and negative matched records. In this theoretical example the two vertical lines show the lower and upper cut-offs (thresholds) that are used in probabilistic record linkage to accept or reject matches. The amount of false positive and negative matches can be managed by moving the thresholds. If false matches are unacceptably high the upper cut-off can be moved to the right, creating more clerical reviews and minimising false decisions from automatically accepting records as a match. A similar process can be used to minimise false negatives.

Figure 2

Linkage rate for complete group by gestational age (weeks). Complete linkage rate (number of birth records linked to both a mother and infant hospital admission birth record as a percentage of all birth records) by gestational age for all births (blue line) and liveborn singletons (dotted black line).

Figure 3

Linkage rate for complete group by birth weight (grams). Complete linkage rate (number of birth records linked to both a mother and infant hospital admission birth record as a percentage of all birth records) by birthweight for all births (blue line) and liveborn singletons (dotted black line).