GUILD: GUidance for Information about Linking Data sets. (28th March 2017)

• Record Type: Journal Article
• Authors: Gilbert, Ruth; Lafferty, Rosemary; Hagger-Johnson, Gareth; Harron, Katie; Zhang, Li-Chun; Smith, Peter; Dibben, Chris; Goldstein, Harvey
• Is Part Of: Journal of public health. Volume 40:Number 1(2018:Mar.)
• Page Start: 191
• Page End: 198
• Publication Date: 2017-03-28
• Subjects: epidemiology -- health services -- management and policy; Public health -- Periodicals; Public health -- Great Britain -- Periodicals; Medical policy -- Periodicals; Medical policy -- Great Britain -- Periodicals; 362.1
• DOI: 10.1093/pubmed/fdx037
• Languages: English
• ISSNs: 1741-3842

Abstract

Abstract: Record linkage of administrative and survey data is increasingly used to generate evidence to inform policy and services. Although a powerful and efficient way of generating new information from existing data sets, errors related to data processing before, during and after linkage can bias results. However, researchers and users of linked data rarely have access to information that can be used to assess these biases or take them into account in analyses. As linked administrative data are increasingly used to provide evidence to guide policy and services, linkage error, which disproportionately affects disadvantaged groups, can undermine evidence for public health. We convened a group of researchers and experts from government data providers to develop guidance about the information that needs to be made available about the data linkage process, by data providers, data linkers, analysts and the researchers who write reports. The guidance goes beyond recommendations for information to be included in research reports. Our aim is to raise awareness of information that may be required at each step of the linkage pathway to improve the transparency, reproducibility, and accuracy of linkage processes, and the validity of analyses and interpretation of results.