No Cover Image

Journal article 891 views 104 downloads

Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data

Joe Hollinghurst, Rich Fry Orcid Logo, Ashley Akbari Orcid Logo, Sarah Rodgers Orcid Logo

International Journal of Population Data Science, Volume: 3, Issue: 4

Swansea University Authors: Joe Hollinghurst, Rich Fry Orcid Logo, Ashley Akbari Orcid Logo, Sarah Rodgers Orcid Logo

  • 44318.pdf

    PDF | Version of Record

    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

    Download (225.22KB)

Check full text

DOI (Published version): 10.23889/ijpds.v3i4.893

Published in: International Journal of Population Data Science
ISSN: 2399-4908
Published: Banff, Canada Swansea University 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa44318
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2018-09-18T18:56:58Z
last_indexed 2018-10-15T19:19:14Z
id cronfa44318
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2018-10-15T15:54:28.7207341</datestamp><bib-version>v2</bib-version><id>44318</id><entry>2018-09-18</entry><title>Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data</title><swanseaauthors><author><sid>d7c51b69270b644a11b904629fe56ab0</sid><firstname>Joe</firstname><surname>Hollinghurst</surname><name>Joe Hollinghurst</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>d499b898d447b62c81b2c122598870e0</sid><ORCID>0000-0002-7968-6679</ORCID><firstname>Rich</firstname><surname>Fry</surname><name>Rich Fry</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>aa1b025ec0243f708bb5eb0a93d6fb52</sid><ORCID>0000-0003-0814-0801</ORCID><firstname>Ashley</firstname><surname>Akbari</surname><name>Ashley Akbari</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>e81e94dea293640575619d15baf34a35</sid><ORCID>0000-0002-4483-0845</ORCID><firstname>Sarah</firstname><surname>Rodgers</surname><name>Sarah Rodgers</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2018-09-18</date><deptcode>FGMHL</deptcode><abstract/><type>Journal Article</type><journal>International Journal of Population Data Science</journal><volume>3</volume><journalNumber>4</journalNumber><publisher>Swansea University</publisher><placeOfPublication>Banff, Canada</placeOfPublication><issnElectronic>2399-4908</issnElectronic><keywords/><publishedDay>5</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-09-05</publishedDate><doi>10.23889/ijpds.v3i4.893</doi><url/><notes/><college>COLLEGE NANME</college><department>Medicine, Health and Life Science - Faculty</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>FGMHL</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2018-10-15T15:54:28.7207341</lastEdited><Created>2018-09-18T16:42:04.6601286</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Joe</firstname><surname>Hollinghurst</surname><order>1</order></author><author><firstname>Rich</firstname><surname>Fry</surname><orcid>0000-0002-7968-6679</orcid><order>2</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>3</order></author><author><firstname>Sarah</firstname><surname>Rodgers</surname><orcid>0000-0002-4483-0845</orcid><order>4</order></author></authors><documents><document><filename>0044318-15102018155207.pdf</filename><originalFilename>44318.pdf</originalFilename><uploaded>2018-10-15T15:52:07.0230000</uploaded><type>Output</type><contentLength>201647</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2018-10-15T00:00:00.0000000</embargoDate><documentNotes>This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by-nc-nd/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2018-10-15T15:54:28.7207341 v2 44318 2018-09-18 Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data d7c51b69270b644a11b904629fe56ab0 Joe Hollinghurst Joe Hollinghurst true false d499b898d447b62c81b2c122598870e0 0000-0002-7968-6679 Rich Fry Rich Fry true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false e81e94dea293640575619d15baf34a35 0000-0002-4483-0845 Sarah Rodgers Sarah Rodgers true false 2018-09-18 FGMHL Journal Article International Journal of Population Data Science 3 4 Swansea University Banff, Canada 2399-4908 5 9 2018 2018-09-05 10.23889/ijpds.v3i4.893 COLLEGE NANME Medicine, Health and Life Science - Faculty COLLEGE CODE FGMHL Swansea University 2018-10-15T15:54:28.7207341 2018-09-18T16:42:04.6601286 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Joe Hollinghurst 1 Rich Fry 0000-0002-7968-6679 2 Ashley Akbari 0000-0003-0814-0801 3 Sarah Rodgers 0000-0002-4483-0845 4 0044318-15102018155207.pdf 44318.pdf 2018-10-15T15:52:07.0230000 Output 201647 application/pdf Version of Record true 2018-10-15T00:00:00.0000000 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. true eng http://creativecommons.org/licenses/by-nc-nd/4.0/
title Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
spellingShingle Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
Joe Hollinghurst
Rich Fry
Ashley Akbari
Sarah Rodgers
title_short Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
title_full Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
title_fullStr Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
title_full_unstemmed Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
title_sort Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data
author_id_str_mv d7c51b69270b644a11b904629fe56ab0
d499b898d447b62c81b2c122598870e0
aa1b025ec0243f708bb5eb0a93d6fb52
e81e94dea293640575619d15baf34a35
author_id_fullname_str_mv d7c51b69270b644a11b904629fe56ab0_***_Joe Hollinghurst
d499b898d447b62c81b2c122598870e0_***_Rich Fry
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
e81e94dea293640575619d15baf34a35_***_Sarah Rodgers
author Joe Hollinghurst
Rich Fry
Ashley Akbari
Sarah Rodgers
author2 Joe Hollinghurst
Rich Fry
Ashley Akbari
Sarah Rodgers
format Journal article
container_title International Journal of Population Data Science
container_volume 3
container_issue 4
publishDate 2018
institution Swansea University
issn 2399-4908
doi_str_mv 10.23889/ijpds.v3i4.893
publisher Swansea University
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
published_date 2018-09-05T03:55:33Z
_version_ 1763752787350388736
score 11.01628

Similar Items