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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.v10i3.3114</article-id>
      <article-id pub-id-type="publisher-id">10:3:95</article-id>
      <title-group>
        <article-title>Understanding the young social care workforce: An analysis of linked
          workforce, education and census data</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>McDonald</surname>
            <given-names initials="T">Ted</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>McGrail</surname>
            <given-names initials="K">Kim</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Hayes</surname>
            <given-names initials="A">Anne</given-names>
          </name>
          <xref ref-type="aff" rid="affil-3">3</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Gatley</surname>
            <given-names initials="J">Jodi</given-names>
          </name>
          <xref ref-type="aff" rid="affil-3">3</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>University of New Brunswick, Fredericton,
        Canada</institution></aff>
      <aff id="affil-2"><label>2</label><institution>University of British Columbia, Vancouver,
        Canada</institution></aff>
      <aff id="affil-3"><label>3</label><institution>ICES, Toronto, Canada</institution></aff>
      <aff id="affil-4"><label>4</label><institution>Health Data Research Network Canada, Toronto,
        Canada</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>3114</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/3114">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3114</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Our Organization, a pan-Canadian network that facilitates publicly-funded multi-regional health research, is developing a process to undertake multi-jurisdictional data analytic services with private sector entities. We describe experiences and approaches to working with the private sector across Organization member sites, and concerns raised by our Public Advisory Committee.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>We administered a survey with categorical and open-ended questions about work with the private sector including project volume, timelines, and differences from publicly-funded projects in terms of review and approval, fee structure, limitations on data access, and additional safeguards. It was distributed to 10 provincial and two pan-Canadian member sites holding linked health administrative data. Findings were organized using the Five Safes framework, a tool for evaluating access to privacy-sensitive data across five dimensions, and were presented at a quarterly PAC meeting to the group of ~15 members from diverse backgrounds. Key discussion and questions points were recorded.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>Among 12 sites surveyed, 10 worked with the private sector in some capacity and 2 planned to in future. Common themes identified, though with variation across sites, included: safe data - some datasets are restricted from private sector use; <underline>safe projects</underline> - require public benefit and exclude market research, require research ethics board approval, monitor projects to ensure public benefit through milestone reporting; <underline>safe people and settings</underline> - no access to individual level data, require use of the site’s analytic services; <underline>safe outputs</underline> - require project summary/results be made public and shared with decision-makers, exclusion of site staff from authorship on publications. Other safeguards included dedicated access pathways to ensure publicly-funded work is not displaced. Most sites had higher project fees for the private sector.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>Given growing private sector demand for pan-Canadian, population-level, data analytic services to demonstrate product value and support adoption decisions, it is essential to set policies and practices that ensure public benefit. These results are supporting the launch of a pilot multi-site use case with a private sector organization.</p>
    </sec>
  </body>
</article>