Identification of Aboriginal children using linked administrative data: Consequences for measuring inequalities

Gialamas, Angela; Pilkington, Rhiannon; Berry, Jesia G.; Scalzi, Daniel; Gibson, Odette; Brown, Alex; Lynch, John

doi:10.1111/jpc.13132

Cited by 20 publications

(24 citation statements)

References 12 publications

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“…The strengths of this study include the high population coverage of the source data, and the large sample size, which enabled us to quantify outcomes for Aboriginal children, a small and vulnerable population group. Linkage of multiple cross‐sectoral administrative datasets enabled enhanced identification of Aboriginal children compared with a single data source …”

Section: Commentmentioning

confidence: 99%

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Gestational Age and Child Development at Age Five in a Population‐Based Cohort of Australian Aboriginal and Non‐Aboriginal Children

Hanly¹,

Falster

Chambers³

et al. 2017

Paediatric Perinatal Epid

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Background: Preterm birth and developmental vulnerability are more common in Australian Aboriginal compared with non-Aboriginal children. We quantified how gestational age relates to developmental vulnerability in both populations. Methods: Perinatal datasets were linked to the Australian Early Development Census (AEDC), which collects data on five domains, including physical, social, emotional, language/cognitive, and general knowledge/ communication development. We quantified the risk of developmental vulnerability on ≥1 domains at age 5, according to gestational age and Aboriginality, for 97 989 children born in New South Wales, Australia, who started school in 2009 or 2012. Results: Seven thousand and seventy-nine children (7%) were Aboriginal. Compared with non-Aboriginal children, Aboriginal children were more likely to be preterm (5% vs. 9%), and developmentally vulnerable on ≥1 domains (20% vs. 36%). Overall, the proportion of developmentally vulnerable children decreased with increasing gestational age, from 44% at ≤27 weeks to 20% at 40 weeks. Aboriginal children had higher risks than nonAboriginal children across the gestational age range, peaking among early term children (risk difference [RD] 19.0, 95% confidence interval [CI] 16.3, 21.7; relative risk [RR] 1.91, 95% CI 1.77, 2.06). The relation of gestational age to developmental outcomes was the same in Aboriginal and non-Aboriginal children, and adjustment for socioeconomic disadvantage attenuated the risk differences and risk ratios across the gestational age range. Conclusions: Although the relation of gestational age to developmental vulnerability was similar in Aboriginal and non-Aboriginal children, Aboriginal children had a higher risk of developmental vulnerability at all gestational ages, which was largely accounted for by socio-economic disadvantage.

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Section: Commentmentioning

confidence: 99%

“…Linkage of multiple cross-sectoral administrative datasets enabled enhanced identification of Aboriginal children compared with a single data source. 24…”

Section: Strengths Of the Studymentioning

confidence: 99%

Gestational Age and Child Development at Age Five in a Population‐Based Cohort of Australian Aboriginal and Non‐Aboriginal Children

Hanly¹,

Falster

Chambers³

et al. 2017

Paediatric Perinatal Epid

Self Cite

View full text Add to dashboard Cite

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“…Linking health-related data requires care, patience and expertise [23], especially linking maternal or neonatal datasets [22,37,38], and identifying and adjusting for errors and disparities [31,32,[39][40][41][42][43][44]. Some researchers have described data linkage techniques for perinatal health research within one Australian state [23,45,46], although compiling and merging maternity data across jurisdictions is less common [40,47].…”

Section: Medical Record Linkage Pregnancy Outcome Retrospective Stumentioning

confidence: 99%

Creating the first national linked dataset on perinatal and maternal outcomes in Australia: Methods and challenges

Cheah

Scarf

Rossiter

et al. 2019

Journal of Biomedical Informatics

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“…Disparities in health outcomes between Aboriginal and non-Aboriginal Australians occur from birth, with higher rates of Aboriginal children born preterm and/or small for gestational age [9,10], and higher rates of infant and child mortality [11][12][13]. Tailoring and resourcing of services to improve the health of Aboriginal children and families require accurate information on health outcomes and risk factors at state and regional levels [4,11,14]. Given that methods used to identify Aboriginality in data may have differing impacts on the reported outcomes depending on the type of data and on the age and region [4,15], it is important to examine these potential impacts.…”

Section: Introductionmentioning

confidence: 99%

“…Tailoring and resourcing of services to improve the health of Aboriginal children and families require accurate information on health outcomes and risk factors at state and regional levels [4,11,14]. Given that methods used to identify Aboriginality in data may have differing impacts on the reported outcomes depending on the type of data and on the age and region [4,15], it is important to examine these potential impacts.…”

Section: Introductionmentioning

confidence: 99%

Identifying young Aboriginal and Torres Strait Islander children in linked administrative data: A comparison of methods

McNamara

Jones

Shepherd

et al. 2020

IJPDS

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BackgroundIn the ongoing debate on optimum methods for identification of Indigenous people within linked administrative data, few studies have examined the impacts of method on population counts and outcomes in family-based linkage studies of Aboriginal children. ObjectiveTo quantify differences between three algorithms in ascertaining Aboriginal and Torres Strait Islander children in linked administrative data. MethodsLinked administrative health data for children born in Western Australia (WA) from 2000-2013, were used to examine the cohorts identified by three methods: A) the Indigenous Status Flag (ISF, derived by the WA Data Linkage Branch using a multistage-median approach) for the children alone; B) the ISF of the children, their parents and grandparents; and C) Indigenous status of the child, mother or father on either of the child's perinatal records (Midwives or birth registration), to determine differing characteristics of each cohort. ResultsMethod B established a larger cohort (33,489) than Method C (33,306) and Method A (27,279), with all methods identifying a core group of 26,790 children (80-98%). Compared with children identified by Method A, additional children identified by Methods B or C, were from less-disadvantaged and more urban areas, and had better perinatal outcomes (e.g. lower proportions of small-for-gestational age, 10% vs 16%). Differences in demographics and health outcomes between Methods C and B were minimal. ConclusionsDemographic and perinatal health characteristics differ by Aboriginal identification method. Using perinatal records or the ISF of parents and grandparents (in addition to the ISF of the child) appear to be more inclusive methods for identifying young Indigenous children in administrative datasets.

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Identification of Aboriginal children using linked administrative data: Consequences for measuring inequalities

Cited by 20 publications

References 12 publications

Gestational Age and Child Development at Age Five in a Population‐Based Cohort of Australian Aboriginal and Non‐Aboriginal Children

Gestational Age and Child Development at Age Five in a Population‐Based Cohort of Australian Aboriginal and Non‐Aboriginal Children

Creating the first national linked dataset on perinatal and maternal outcomes in Australia: Methods and challenges

Identifying young Aboriginal and Torres Strait Islander children in linked administrative data: A comparison of methods

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