Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom.
Collaboration
Data linkage
Geohealth
Health geography
International
Journal
Applied spatial analysis and policy
ISSN: 1874-463X
Titre abrégé: Appl Spat Anal Policy
Pays: Netherlands
ID NLM: 101631768
Informations de publication
Date de publication:
2021
2021
Historique:
received:
20
11
2020
accepted:
20
04
2021
pubmed:
5
5
2021
medline:
5
5
2021
entrez:
4
5
2021
Statut:
ppublish
Résumé
Globally, geospatial concepts are becoming increasingly important in epidemiological and public health research. Individual level linked population-based data afford researchers with opportunities to undertake complex analyses unrivalled by other sources. However, there are significant challenges associated with using such data for impactful geohealth research. Issues range from extracting, linking and anonymising data, to the translation of findings into policy whilst working to often conflicting agendas of government and academia. Innovative organisational partnerships are therefore central to effective data use. To extend and develop existing collaborations between the institutions, in June 2019, authors from the Leeds Institute for Data Analytics and the Alan Turing Institute, London, visited the Geohealth Laboratory based at the University of Canterbury, New Zealand. This paper provides an overview of insight shared during a two-day workshop considering aspects of linked population-based data for impactful geohealth research. Specifically, we discuss both the collaborative partnership between New Zealand's Ministry of Health (MoH) and the University of Canterbury's GeoHealth Lab and novel infrastructure, and commercial partnerships enabled through the Leeds Institute for Data Analytics and the Alan Turing Institute in the UK. We consider the New Zealand Integrated Data Infrastructure as a case study approach to population-based linked health data and compare similar approaches taken by the UK towards integrated data infrastructures, including the ESRC Big Data Network centres, the UK Biobank, and longitudinal cohorts. We reflect on and compare the geohealth landscapes in New Zealand and the UK to set out recommendations and considerations for this rapidly evolving discipline.
Identifiants
pubmed: 33942015
doi: 10.1007/s12061-021-09381-8
pii: 9381
pmc: PMC8081771
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1025-1040Informations de copyright
© The Author(s) 2021, corrected publication 2021.
Déclaration de conflit d'intérêts
Conflicts of InterestThe authors have no conflicts of interest to declare.
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