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

**Authors:** 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

PMC · DOI: 10.5694/mja2.70149 · The Medical Journal of Australia · 2026-03-02

## TL;DR

Linked administrative data can help address child health inequities by supporting better policy decisions and tracking their impact.

## Contribution

The paper highlights how linked administrative data can be used to inform and monitor equitable child health policies.

## Key findings

- Linked administrative data can enable timely and precise policy responses to child health inequities.
- Sustained data infrastructure and analytic capability are essential to realize the potential of these data.
- Investing in linked data systems can lead to lasting benefits for children, families, and society.

## 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.

## Full-text entities

- **Diseases:** infection (MESH:D007239), COVID-19 (MESH:D000086382), disabilities (MESH:D009069), PLIDA (MESH:D000081042)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

34 references — full list in the complete paper: https://tomesphere.com/paper/PMC12954355/full.md

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Source: https://tomesphere.com/paper/PMC12954355