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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJPDS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Population Data Science</journal-title>
        <abbrev-journal-title>IJPDS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2399-4908</issn>
      <publisher>
        <publisher-name>Swansea University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.23889/ijpds.v10i4.3049</article-id>
      <article-id pub-id-type="publisher-id">10:3:37</article-id>
      <title-group>
        <article-title>MeaFrom Data to Action: Transforming Bradford's Perinatal Mental Health
          Intelligence Through Local Collaboration</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Henderson</surname>
            <given-names initials="H">Hollie</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Shaib</surname>
            <given-names initials="S">Sabah</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Milne</surname>
            <given-names initials="L">Lisa</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ciesla</surname>
            <given-names initials="K">Kayley</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bridges</surname>
            <given-names initials="S">Sally</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>Bradford Institute for Health Research,
        Bradford, United Kingdom</institution></aff>
      <pub-date date-type="pub" publication-format="electronic">
        <day>01</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>8</volume>
      <issue>4</issue>
      <elocation-id>3049</elocation-id>
      <permissions>
        <license license-type="open-access"
          xlink:href="https://creativecommons.org/licences/by/4.0/">
          <license-p>This work is licenced under a Creative Commons Attribution 4.0 International
            License.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://ijpds.org/article/view/3049">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3049</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objective</title>
      <p>The objective was to work with local services in Bradford to improve the quality of routine
        perinatal mental health data for research and service planning. This stemmed from analysis
        of locally linked routine data, which identified significant gaps and issues, and the
        motivation of services to better use their data.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>Born in Bradford for All (BiB4All) is an electronic data linkage cohort of mothers and
        their children, which aims to use routinely collected data for research and to inform local
        policy and practice. To achieve this aim, we established links with relevant stakeholder
        groups in Bradford, to understand their current priorities.</p>
      <p>Through attending stakeholder meetings, we identified a common goal of improving routine
        perinatal mental health data across services in Bradford, to enable a better understanding
        of inequalities and unmet need. We co-produced a research question and analysis of BiB4All
        data to explore the extent of the current data issues.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>Establishing a trusted relationship between local services recording routine data and
        researchers using these data enabled the co-design of a workshop aiming to develop an action
        plan to address identified data issues. The workshop (planned for April 2025) is underpinned
        by Ketso principles and will bring together local maternity, health visiting and specialist
        perinatal mental health services in Bradford to discuss:</p>
      <p>Their current data assets, based on insights from the BiB4All data analysis</p>
      <p>How to improve their data</p>
      <p>Barriers to improving their data</p>
      <p>Next steps for implementing changes to data collection</p>
      <p>This collaboration has developed understanding among perinatal mental health services about
        how routine data can be used beyond individual clinical care for research and service
        planning.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>Building capacity for routine data to be used for research and service improvements is an
        important step to more equitable access and uptake to perinatal mental health services. We
        are planning an evaluation to understand the impact of this work on data quality, service
        access and inclusion.</p>
    </sec>
  </body>
</article>