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Data for Equity: Can Linked Administrative Data Inform Pathways to More Equitable Child Health?

Sarah Gray, Shuaijun Guo, Meredith O'Connor, Elodie O'Connor, Katrina Williams, Hannah Badland, Susan Woolfenden, Josie Dickerson, Gerry Redmond, Marnie Downes, Sharon R. Goldfeld
Correspondence: sarah.gray@mcri.edu.au
Med J Aust 2026; 224 (3) || doi: 10.5694/mja2.70149
Published online: 2 March 2026

Abstract

Child health inequities remain a persistent challenge, with well-described long-term consequences. Advances in cross-sector administrative data linkage and causal inference methods offer powerful opportunities to transform data into evidence for addressing inequities. This article explores how linked administrative data support timely, precise, agile and coordinated policy responses and monitor their impact. We outline conditions needed to realise this potential, including sustained cross-sector data infrastructure, analytic capability and increased efforts to translate evidence into action. We argue linked administrative data can inform pathways to more equitable child health and, with investment, help deliver on lasting returns for children, families and society.

  • Sarah Gray, Shuaijun Guo, Meredith O'Connor, Elodie O'Connor, Katrina Williams, Hannah Badland, Susan Woolfenden, Josie Dickerson, Gerry Redmond, Marnie Downes, Sharon R. Goldfeld



Correspondence: sarah.gray@mcri.edu.au

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