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Adjusting for under-identification of Aboriginal and/or Torres Strait Islander births in time series produced from birth records: Using record linkage of survey data and administrative data sources

DOI: 10.1186/1471-2288-12-90

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Abstract:

We used record linkage between a large-scale survey (the Western Australian Aboriginal Child Health Survey), and two administrative data sources (the Western Australia (WA) Register of Births and the WA Midwives’ Notification System) to compare the degree of consistency in determining Indigenous status of children between the two sources. We then used a logistic regression model predicting probability of consistency between the two sources to estimate the probability of each record on the two administrative data sources being identified as being of Aboriginal and/or Torres Strait Islander origin in a survey. By summing these probabilities we produced model-adjusted time series of neonatal outcomes for Aboriginal and/or Torres Strait Islander births.Compared to survey data, information based only on the two administrative data sources identified substantially fewer Aboriginal and/or Torres Strait Islander births. However, these births were not randomly distributed. Births of children identified as being of Aboriginal and/or Torres Strait Islander origin in the survey only were more likely to be living in urban areas, in less disadvantaged areas, and to have only one parent who identifies as being of Aboriginal and/or Torres Strait Islander origin, particularly the father. They were also more likely to have better health and wellbeing outcomes. Applying an adjustment model based on the linked survey data increased the estimated number of Aboriginal and/or Torres Strait Islander births in WA by around 25%, however this increase was accompanied by lower overall proportions of low birth weight and low gestational age babies.Record linkage of survey data to administrative data sets is useful to validate the quality of recording of demographic information in administrative data sources, and such information can be used to adjust for differential identification in administrative data.

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