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

The Medical Journal of Australia 2026 Dataset Open access

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Authors: Sarah A. O. Gray, Shuaijun Guo, Meredith O'Connor, Elodie O'Connor, Katrina Jane Williams, Hannah M Badland, Susan Woolfenden, Josie Dickerson, Gerry Redmond, Marnie Downes, Sharon R Goldfeld
DOI: 10.5694/mja2.70149
Cited by: 1
References: 34

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.

Fields of Study & Subjects

Advanced Causal Inference Techniques Food Security and Health in Diverse Populations Data Quality and Management

Publication details

Journal / source
The Medical Journal of Australia
Publisher
Wiley
Volume
224
Issue
3
Pages
e70149–e70149
Publication date
1 March 2026
Language
EN
Document type
Dataset