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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Privacy preserving interactive record linkage (PPIRL)</title><author><name sortKey="Kum, Hye Chung" sort="Kum, Hye Chung" uniqKey="Kum H" first="Hye-Chung" last="Kum">Hye-Chung Kum</name><affiliation><nlm:aff id="af1"><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af2"><addr-line>Department of Health Policy and Management, Texas A&M Health Science Center, College Station, Texas, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af4"><addr-line>Department of Pediatrics, College of Medicine Baylor Scott & White, Texas A&M Health Science Center, Temple, Texas, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Krishnamurthy, Ashok" sort="Krishnamurthy, Ashok" uniqKey="Krishnamurthy A" first="Ashok" last="Krishnamurthy">Ashok Krishnamurthy</name><affiliation><nlm:aff id="af1"><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af5"><addr-line>RENCI, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Machanavajjhala, Ashwin" sort="Machanavajjhala, Ashwin" uniqKey="Machanavajjhala A" first="Ashwin" last="Machanavajjhala">Ashwin Machanavajjhala</name><affiliation><nlm:aff id="af6"><addr-line>Department of Computer Science, Duke University, Durham, North Carolina, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Reiter, Michael K" sort="Reiter, Michael K" uniqKey="Reiter M" first="Michael K" last="Reiter">Michael K. Reiter</name><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ahalt, Stanley" sort="Ahalt, Stanley" uniqKey="Ahalt S" first="Stanley" last="Ahalt">Stanley Ahalt</name><affiliation><nlm:aff id="af1"><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af5"><addr-line>RENCI, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24201028</idno><idno type="pmc">3932473</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3932473</idno><idno type="RBID">PMC:3932473</idno><idno type="doi">10.1136/amiajnl-2013-002165</idno><date when="2013">2013</date><idno type="wicri:Area/Pmc/Corpus">000365</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Privacy preserving interactive record linkage (PPIRL)</title><author><name sortKey="Kum, Hye Chung" sort="Kum, Hye Chung" uniqKey="Kum H" first="Hye-Chung" last="Kum">Hye-Chung Kum</name><affiliation><nlm:aff id="af1"><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af2"><addr-line>Department of Health Policy and Management, Texas A&M Health Science Center, College Station, Texas, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af4"><addr-line>Department of Pediatrics, College of Medicine Baylor Scott & White, Texas A&M Health Science Center, Temple, Texas, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Krishnamurthy, Ashok" sort="Krishnamurthy, Ashok" uniqKey="Krishnamurthy A" first="Ashok" last="Krishnamurthy">Ashok Krishnamurthy</name><affiliation><nlm:aff id="af1"><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af5"><addr-line>RENCI, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Machanavajjhala, Ashwin" sort="Machanavajjhala, Ashwin" uniqKey="Machanavajjhala A" first="Ashwin" last="Machanavajjhala">Ashwin Machanavajjhala</name><affiliation><nlm:aff id="af6"><addr-line>Department of Computer Science, Duke University, Durham, North Carolina, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Reiter, Michael K" sort="Reiter, Michael K" uniqKey="Reiter M" first="Michael K" last="Reiter">Michael K. Reiter</name><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ahalt, Stanley" sort="Ahalt, Stanley" uniqKey="Ahalt S" first="Stanley" last="Ahalt">Stanley Ahalt</name><affiliation><nlm:aff id="af1"><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af3"><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="af5"><addr-line>RENCI, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></nlm:aff></affiliation></author></analytic><series><title level="j">Journal of the American Medical Informatics Association : JAMIA</title><idno type="ISSN">1067-5027</idno><idno type="eISSN">1527-974X</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Objective</title><p>Record linkage to integrate uncoordinated databases is critical in biomedical research using <italic>Big Data</italic>. Balancing privacy protection against the need for high quality record linkage requires a human–machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic <italic>Big Data</italic>.</p></sec><sec><title>Methods</title><p>In the computer science literature, private record linkage is the most published area. It investigates how to apply a known linkage function safely when linking two tables. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Recently, a more flexible computerized third-party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on: (1) decoupling data via encryption, (2) obfuscation via chaffing (adding fake data) and universe manipulation; and (3) minimum information disclosure via recoding.</p></sec><sec><title>Results</title><p>We synthesize this literature to formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties and then analyze the literature using this framework.</p></sec><sec><title>Conclusions</title><p>Human-based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human–machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility.</p></sec></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Am Med Inform Assoc</journal-id><journal-id journal-id-type="iso-abbrev">J Am Med Inform Assoc</journal-id><journal-id journal-id-type="hwp">amiajnl</journal-id><journal-id journal-id-type="publisher-id">jamia</journal-id><journal-title-group><journal-title>Journal of the American Medical Informatics Association : JAMIA</journal-title></journal-title-group><issn pub-type="ppub">1067-5027</issn><issn pub-type="epub">1527-974X</issn><publisher><publisher-name>BMJ Publishing Group</publisher-name><publisher-loc>BMA House, Tavistock Square, London, WC1H 9JR</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24201028</article-id><article-id pub-id-type="pmc">3932473</article-id><article-id pub-id-type="publisher-id">amiajnl-2013-002165</article-id><article-id pub-id-type="doi">10.1136/amiajnl-2013-002165</article-id><article-categories><subj-group subj-group-type="heading"><subject>Review</subject></subj-group></article-categories><title-group><article-title>Privacy preserving interactive record linkage (PPIRL)</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kum</surname><given-names>Hye-Chung</given-names></name><xref ref-type="aff" rid="af1">1</xref><xref ref-type="aff" rid="af2">2</xref><xref ref-type="aff" rid="af3">3</xref><xref ref-type="aff" rid="af4">4</xref></contrib><contrib contrib-type="author"><name><surname>Krishnamurthy</surname><given-names>Ashok</given-names></name><xref ref-type="aff" rid="af1">1</xref><xref ref-type="aff" rid="af3">3</xref><xref ref-type="aff" rid="af5">5</xref></contrib><contrib contrib-type="author"><name><surname>Machanavajjhala</surname><given-names>Ashwin</given-names></name><xref ref-type="aff" rid="af6">6</xref></contrib><contrib contrib-type="author"><name><surname>Reiter</surname><given-names>Michael K</given-names></name><xref ref-type="aff" rid="af3">3</xref></contrib><contrib contrib-type="author"><name><surname>Ahalt</surname><given-names>Stanley</given-names></name><xref ref-type="aff" rid="af1">1</xref><xref ref-type="aff" rid="af3">3</xref><xref ref-type="aff" rid="af5">5</xref></contrib></contrib-group><aff id="af1"><label>1</label><addr-line>Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA</addr-line></aff><aff id="af2"><label>2</label><addr-line>Department of Health Policy and Management, Texas A&M Health Science Center, College Station, Texas, USA</addr-line></aff><aff id="af3"><label>3</label><addr-line>Department of Computer Science, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></aff><aff id="af4"><label>4</label><addr-line>Department of Pediatrics, College of Medicine Baylor Scott & White, Texas A&M Health Science Center, Temple, Texas, USA</addr-line></aff><aff id="af5"><label>5</label><addr-line>RENCI, UNC-CH, Chapel Hill, North Carolina, USA</addr-line></aff><aff id="af6"><label>6</label><addr-line>Department of Computer Science, Duke University, Durham, North Carolina, USA</addr-line></aff><author-notes><corresp><label>Correspondence to</label> Dr Hye-Chung Kum, Department of Health Policy and Management, Texas A&M Health Science Center, 1266 TAMU, College Station, TX 77843, USA; <email>kum@srph.tamhsc.edu</email></corresp></author-notes><pub-date pub-type="ppub"><month>3</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>7</day><month>11</month><year>2013</year></pub-date><volume>21</volume><issue>2</issue><fpage>212</fpage><lpage>220</lpage><history><date date-type="received"><day>3</day><month>7</month><year>2013</year></date><date date-type="rev-recd"><day>5</day><month>9</month><year>2013</year></date><date date-type="accepted"><day>6</day><month>10</month><year>2013</year></date></history><permissions><copyright-statement>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</copyright-statement><copyright-year>2014</copyright-year></permissions><self-uri xlink:title="pdf" xlink:type="simple" xlink:href="amiajnl-2013-002165.pdf"></self-uri><abstract><sec><title>Objective</title><p>Record linkage to integrate uncoordinated databases is critical in biomedical research using <italic>Big Data</italic>. Balancing privacy protection against the need for high quality record linkage requires a human–machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic <italic>Big Data</italic>.</p></sec><sec><title>Methods</title><p>In the computer science literature, private record linkage is the most published area. It investigates how to apply a known linkage function safely when linking two tables. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Recently, a more flexible computerized third-party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on: (1) decoupling data via encryption, (2) obfuscation via chaffing (adding fake data) and universe manipulation; and (3) minimum information disclosure via recoding.</p></sec><sec><title>Results</title><p>We synthesize this literature to formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties and then analyze the literature using this framework.</p></sec><sec><title>Conclusions</title><p>Human-based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human–machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility.</p></sec></abstract><kwd-group><kwd>privacy preserving interactive record linkage (PPIRL)</kwd><kwd>decoupled data</kwd><kwd>entity resolution</kwd><kwd>medical record linkage</kwd><kwd>privacy</kwd><kwd>Electronic Health Records (EHR)</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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