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Background <p>This paper outlines the development of a new, collaborative data harmonisation initiative within the Hunter New England (HNE) region of New South Wales in Australia. The initiative aims to address the issue of fragmented population mental health data across health services, research institutions and government agencies through development of a standardised platform that facilitates sharing and harmonisation of data across diverse datasets. By enhancing the region’s data integration capabilities, incorporating both new and retrospective data, the platform will support emerging collaborative research initiatives and improve decision-making efficiency and effectiveness in mental health service planning. Data harmonisation is essential for mental health research because it enables large-scale, high-quality studies that can uncover patterns, causes, and solutions that would otherwise remain hidden in fragmented datasets. Mental health conditions are highly variable in their presentation, progression, and response to treatment, making it crucial for researchers to analyse diverse data sources—spanning clinical records, epidemiological studies, social determinants, genetics, and real-world patient experiences. Furthermore, population data suggests that fewer than 50% of people experiencing mental health difficulties seek treatment. Without harmonisation, inconsistencies in data collection and classification limit the ability to compare studies, replicate findings, or generate insights that are applicable across different populations and healthcare settings. Platforms supporting harmonisation of data can be enhanced with real-time data queries and visualisation, providing a unique way to understand, monitor and address population health priorities that have national significance.</p> Method <p>Key stakeholders contributed through formation of a steering committee with clinical oversight and governance, and by providing feedback during development, resulting in a preliminary prototype data dashboard, focused on mental health data. Key aims of the platform were ease and suitability for use by various end-user groups.</p> Results/Discussion <p>The first version of the prototype dashboard is being developed in the Power BI platform, focusing on the mental health domain. It is hoped that the platform will be piloted in the next phase of our project to inform scalability and potential for broader rollout within other regional and metropolitan areas of Australia.</p>

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Harmonising research data to support mental health services decision making and care planning: development of a data harmonisation platform in regional Australia

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月11日

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  • Agatha Conrad,
  • Jamin Day,
  • Ross Tynan,
  • Dara Sampson,
  • Frances Kay-Lambkin,
  • Brian Kelly,
  • Rhonda Wilson,
  • Emma Axelsson,
  • Louise Thornton,
  • Patrick Skippen,
  • Emily Pollock,
  • Shaun Grady,
  • Jaelea Skehan,
  • Ketrina Sly

摘要

Background

This paper outlines the development of a new, collaborative data harmonisation initiative within the Hunter New England (HNE) region of New South Wales in Australia. The initiative aims to address the issue of fragmented population mental health data across health services, research institutions and government agencies through development of a standardised platform that facilitates sharing and harmonisation of data across diverse datasets. By enhancing the region’s data integration capabilities, incorporating both new and retrospective data, the platform will support emerging collaborative research initiatives and improve decision-making efficiency and effectiveness in mental health service planning. Data harmonisation is essential for mental health research because it enables large-scale, high-quality studies that can uncover patterns, causes, and solutions that would otherwise remain hidden in fragmented datasets. Mental health conditions are highly variable in their presentation, progression, and response to treatment, making it crucial for researchers to analyse diverse data sources—spanning clinical records, epidemiological studies, social determinants, genetics, and real-world patient experiences. Furthermore, population data suggests that fewer than 50% of people experiencing mental health difficulties seek treatment. Without harmonisation, inconsistencies in data collection and classification limit the ability to compare studies, replicate findings, or generate insights that are applicable across different populations and healthcare settings. Platforms supporting harmonisation of data can be enhanced with real-time data queries and visualisation, providing a unique way to understand, monitor and address population health priorities that have national significance.

Method

Key stakeholders contributed through formation of a steering committee with clinical oversight and governance, and by providing feedback during development, resulting in a preliminary prototype data dashboard, focused on mental health data. Key aims of the platform were ease and suitability for use by various end-user groups.

Results/Discussion

The first version of the prototype dashboard is being developed in the Power BI platform, focusing on the mental health domain. It is hoped that the platform will be piloted in the next phase of our project to inform scalability and potential for broader rollout within other regional and metropolitan areas of Australia.