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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.v7i3.2047</article-id>
      <article-id pub-id-type="publisher-id">7:03:270</article-id>
      <title-group>
        <article-title>Evaluation of the reported data linkage process and associated quality issues for linked routinely collected healthcare data in Multimorbidity research: a systematic review.</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Elstad</surname>
            <given-names initials="M">Maria</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Douiri</surname>
            <given-names initials="A">Abdel</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Røislien</surname>
            <given-names initials="J">Jo</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label>
        <institution>King's College London</institution>
      </aff>
      <aff id="affil-2"><label>2</label>
        <institution>University of Stavanger</institution>
      </aff>
      <pub-date date-type="pub" publication-format="electronic"><day></day><month>09</month><year>2022</year></pub-date>
      <pub-date date-type="collection" publication-format="electronic"><year>2022</year></pub-date>
      <volume>7</volume>
      <issue>3</issue>
      <elocation-id>2047</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/2047">This article is available from the IJPDS website at: https://ijpds.org/article/view/2047</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>The objective for this systematic review was to examine how the record linkage process was reported and to understand challenges related to accessing, linking, and analysing linked routinely collected data used for multimorbidity research.</p>
    </sec>
    <sec>
      <title>Approach</title>
      <p>Twenty studies were included, of which seventeen looked at the relationship between two specified long-term conditions. Fourteen studies received the linked dataset from an external data linkage provider. Hospital Episode Statistics was the most common source of data (n=5). Eight studies reported variables used for the data linkage, while only two studies reported pre-linkage checks. The quality of the linkage was assessed by three studies, of which two reported linkage rate and one reported raw linkage figures. Only one study checked for bias by comparing patient characteristics of linked and non-linked records.</p>
      <p>The findings from this study will feed into further guidance to understand and minimise bias due to linkage error in medical research.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>Twenty studies were included, of which seventeen looked at the relationship between two specified long-term conditions. Fourteen studies received the linked dataset from an external data linkage provider. Hospital Episode Statistics was the most common source of data (n=5). Eight studies reported variables used for the data linkage, while only two studies reported pre-linkage checks. The quality of the linkage was assessed by three studies, of which two reported linkage rate and one reported raw linkage figures. Only one study checked for bias by comparing patient characteristics of linked and non-linked records.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>UK LLC provides a strategic research-ready platform for longitudinal research: a clear step change from pre-pandemic capability. With sustained investment, and through exploring options to extend linkages and generalise to wider purposes, UK LLC is positioned to inform cross-cutting themes such as understanding health and social inequalities, health-social-environmental interactions, and managing the COVID-19 recovery.</p>
    </sec>
  </body>
</article>