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  dtd-version="1.2" article-type="abstract">
  <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.v10i3.3142</article-id>
      <article-id pub-id-type="publisher-id">10:3:117</article-id>
      <title-group>
        <article-title>Linking dental and medical hospital records to investigate oral-systemic
          health relationships</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Wu</surname>
            <given-names initials="J">Jianhua</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Kang</surname>
            <given-names initials="J">Jing</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Gao</surname>
            <given-names initials="C">Chenyi</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Donos</surname>
            <given-names initials="N">Nikos</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Pavitt</surname>
            <given-names initials="S">Sue</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>Queen Mary University of London, London, United
        Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>Kings College London, London, 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>3142</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/3142">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3142</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Traditionally, dental and medical records are collected and stored separately within the
        healthcare system, limiting opportunities for integrated research. This study explores the
        feasibility of integrating routinely collected administrative secondary care dental and
        hospital inpatient records to create a scalable research infrastructure for investigating
        associations between oral health and systemic disease. </p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>We established a data linkage framework using routinely collected dental and hospital EHR
        from Leeds Teaching Hospitals NHS Trust. Patient records (2014–2023) were linked via NHS
        numbers, integrating dental treatment data with systemic disease diagnoses (ICD-10). Linkage
        success rates and data completeness were assessed. We examined systemic disease prevalence
        and multimorbidity patterns across dental specialties to validate the utility of
        administrative data for oral-systemic research. </p>
    </sec>
    <sec>
      <title>Results</title>
      <p>TThe linkage framework successfully integrated 32,675 dental patient records with hospital
        EHR, with over 90% achieving complete linkage. One in five patients (19.7%) had at least one
        systemic disease, with the highest burden in periodontal/restorative patients (50.9%).
        Cardiovascular and musculoskeletal conditions were significantly more prevalent in these
        patients, reinforcing established oral-systemic health associations. Data completeness
        analysis identified opportunities for further linkage with primary care records to enhance
        multimorbidity profiling. </p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>By integrating routinely collected dental and hospital records, this study demonstrates the
        potential of administrative health data for investigating oral-systemic health
        relationships. This approach provides a scalable framework for future multimorbidity
        research, supporting the development of integrated healthcare strategies and informing
        evidence-based policy in oral and general health.</p>
    </sec>
  </body>
</article>