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

Joseph 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: Joseph Hollinghurst, Rich Fry Orcid Logo, Ashley Akbari Orcid Logo, Sarah Rodgers Orcid Logo

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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
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URI: https://cronfa.swan.ac.uk/Record/cronfa44318
first_indexed 2018-09-18T18:56:58Z
last_indexed 2018-10-15T19:19:14Z
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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 Joseph Hollinghurst Joseph 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 MEDS 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 Medical School COLLEGE CODE MEDS 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 Joseph 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
Joseph 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_***_Joseph Hollinghurst
d499b898d447b62c81b2c122598870e0_***_Rich Fry
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
e81e94dea293640575619d15baf34a35_***_Sarah Rodgers
author Joseph Hollinghurst
Rich Fry
Ashley Akbari
Sarah Rodgers
author2 Joseph 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 2018-09-05T19:32:55Z
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score 11.04748

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