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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.v9i5.2576</article-id>
      <article-id pub-id-type="publisher-id">9:5:092</article-id>
      <title-group>
        <article-title>Towards Streamlined Transparent Data Linkage</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Kurdyak</surname>
            <given-names initials="P">Paul</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Crocker</surname>
            <given-names initials="M">Matthew</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Huang</surname>
            <given-names initials="A">Anjie</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Saunders</surname>
            <given-names initials="N">Natasha</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>ICES</institution></aff>
      <aff id="affil-2"><label>2</label><institution>Hospital for Sick Children</institution></aff>
      <pub-date date-type="pub" publication-format="electronic">
        <day>18</day>
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2024</year>
      </pub-date>
      <volume>9</volume>
      <issue>5</issue>
      <elocation-id>2575</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/2575">This article is available from the IJPDS website at: https://ijpds.org/article/view/2575</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Introduction</title>
      <p>Most substance use disorder (SUD) treatment occurs in community settings. Community-based SUD treatment information is rarely captured or utilized. The objective of this study was to examine the efficiency of a data linkage of community-based SUD treatment to health administrative data holdings in Ontario, Canada, and to describe sociodemographic and clinical characteristics of individuals accessing SUD services.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>Data from community-based SUD service providers (>180) from April 2015 to March 2022 were linked to administrative data holdings at ICES. Linkage rates were evaluated. Sociodemographic (age, sex, neighbourhood-level income) and clinical (substance use, physician visits, Emergency Department (ED) visits and hospitalizations) characteristics were evaluated.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>The linkage rate of DATIS ICES data holdings was >92% for all years (2015-2022). Of the 234,501 individuals admitted to a DATIS program, 36.1% were female, 46.2% were 25-44 years old, and 51.6% resided in the two lowest neighbourhood income quintiles. Alcohol (33.4%) was the most common substance identified. For outpatient care occurring within 1 year prior to admission, around 56.0% and 23.3% had Mental Health and Addictions (MHA) related primary care and psychiatrist visits, respectively. For acute health services, 29.8% and 14.2%  had a MHA- related ED visit or hospitalization, respectively.</p>
    </sec>
    <sec>
      <title>Discussion</title>
      <p>SUD treatment data from community settings can be successfully linked to other health administrative data. Individuals with SUD have a high rate of acute health care use, and a relatively low access to psychiatrists. SUD treatment data linkage should be used to understand how to optimize access to care for vulnerable individuals.</p>
    </sec>
  </body>
</article>