title: GUILD: GUidance for Information about Linking Data sets.
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.
authors.affiliation: Administrative Data Research Centre for England, University College London Great Ormond Street Institute of Child Health, London, UK.
authors.forename: Ruth
authors.initials: R
authors.lastname: Gilbert
authors.affiliation: Administrative Data Research Centre for England, University College London Great Ormond Street Institute of Child Health, London, UK.
authors.forename: Rosemary
authors.initials: R
authors.lastname: Lafferty
authors.affiliation: Administrative Data Research Centre for England, University College London Great Ormond Street Institute of Child Health, London, UK.
authors.forename: Gareth
authors.initials: G
authors.lastname: Hagger-Johnson
authors.affiliation: Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
authors.forename: Katie
authors.initials: K
authors.lastname: Harron
authors.affiliation: Department of Social Statistics and Demography, University of Southampton, Southampton, UK.
authors.forename: Li-Chun
authors.initials: LC
authors.lastname: Zhang
authors.affiliation: Department of Social Statistics and Demography, University of Southampton, Southampton, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Smith
authors.affiliation: Administrative Data Research Centre for Scotland, University of Edinburgh, Edinburgh, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Dibben
authors.affiliation: Administrative Data Research Centre for England, University College London Great Ormond Street Institute of Child Health, London, UK.
authors.forename: Harvey
authors.initials: H
authors.lastname: Goldstein
mesh_terms: D000068598:Data Accuracy; D000068240:Data Anonymization; D066264:Datasets as Topic; D016247:Information Storage and Retrieval / Q000592:standards*; D008498:Medical Record Linkage / Q000592:standards*; D006113:United Kingdom