文章基本信息

标题：Exploring barriers and solutions in advancing cross-centre population data science
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作者：Kerina H Jones ; Sharon M Heys ; Helen Daniels 等
期刊名称：International Journal of Population Data Science
电子版ISSN：2399-4908
出版年度：2019
卷号：4
期号：1
页码：1-10
DOI：10.23889/ijpds.v4i1.1109
出版社：Swansea University
其他摘要：IntroductionIt is widely acknowledged that population health and administrative data, especially when linked at the individual level, hold great value for research. Cross-centre working between data centres providing access to such data has the potential to further increase this value by effectively expanding the data available for research. However, there is limited published information on how to address the challenges and achieve success. The aim of this paper is to explore perceived barriers and solutions to inform developments in cross-centre working across data centres. MethodsWe carried out a narrative literature review on data sharing and cross centre working. We used a mixed methods approach to assess the opinions of members of the public on cross-centre data sharing, and the views and experiences of among data centre staff connected with the UK Farr Institute for Health Informatics Research. ResultsThe literature review uncovered a myriad of practical and cultural issues. Our engagement with a public group suggested that cross-centre working involving anonymised data being moved between established centres is considered acceptable. The main themes emerging from discussions with data centre staff were dedicated resourcing, practical issues, information governance and culture. ConclusionIn seeking to advance cross-centre working between data centres, we conclude that there is a need for dedicated resourcing, indicators to recognise data reuse, collaboration to solve common issues, and balancing necessary barrier removal with incentivisation. This will require on-going commitment, engagement and an academic culture change.
其他关键词：Population Data Science;cross-centre working;data sharing