Biases arising from linked administrative data for epidemiological research: a conceptual framework from registration to analyses

Shaw, R. J. et al. (2022) Biases arising from linked administrative data for epidemiological research: a conceptual framework from registration to analyses. European Journal of Epidemiology, 37(12), pp. 1215-1224. (doi: 10.1007/s10654-022-00934-w) (PMID:36333542) (PMCID:PMC9792414)

[img] Text
282453.pdf - Published Version
Available under License Creative Commons Attribution.



Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people’s life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.

Item Type:Articles
Additional Information:Funding: This research was supported by the National Institute for Health Research (NIHR) (GHRG /16/137/99) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. The Social and Public Health Sciences Unit is core funded by the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). CIDACS is supported by grants from CNPq/MS/Gates Foundation (401739/2015–5) and the Wellcome Trust, UK (202912/Z/16/Z). RJS is funded by Health Data Research UK (SS005). SVK is funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02). MA is funded by the Economic and Social Research Council (ES/T000120/1). KH is funded by the Wellcome Trust (Grant 212953/Z/18/Z). This research was supported in part by the NIHR Great Ormond Street Hospital Biomedical Research Centre and the Health Data Research UK (grant No. LOND1), which is funded by the UK Medical Research Council and eight other funders.
Glasgow Author(s) Enlighten ID:Katikireddi, Professor Vittal and Campbell, Dr Desmond and Shaw, Dr Richard and Leyland, Professor Alastair and Allik, Dr Mirjam and Dundas, Professor Ruth
Authors: Shaw, R. J., Harron, K. L., Pescarini, J. M., Junior, E. P. P., Allik, M., Siroky, A. N., Campbell, D., Dundas, R., Ichihara, M. Y., Leyland, A. H., Barreto, M. L., and Katikireddi, S. V.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
Journal Name:European Journal of Epidemiology
ISSN (Online):1573-7284
Published Online:05 November 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in European Journal of Epidemiology 37(12): 1215-1224
Publisher Policy:Reproduced under a Creative Commons license

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172690Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiOffice of the Chief Scientific Adviser (CSO)SCAF/15/02SHW - Public Health
3048230021Inequalities in healthAlastair LeylandMedical Research Council (MRC)MC_UU_00022/2HW - MRC/CSO Social and Public Health Sciences Unit
3048230071Inequalities in healthAlastair LeylandOffice of the Chief Scientific Adviser (CSO)SPHSU17HW - MRC/CSO Social and Public Health Sciences Unit
300390Strengthening data linkage to reduce health inequalities in low and middle income countries: building on the Brazilian 100 million cohortAlastair LeylandNational Institute for Health Research (NIHR)16/137/99SHW - MRC/CSO Social & Public Health Sciences Unit
306624Comparing health outcomes for looked after children and children in the general population in Scotland using linked administrative dataMirjam AllikEconomic and Social Research Council (ESRC)ES/T000120/1SHW - MRC/CSO Social & Public Health Sciences Unit