Integrating electronic health records from different sources across the UK: lessons from a record linkage study

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Amrita Bandyopadhyay
Karen Tingay
Ashley Akbari
Lucy Griffiths
Mario Cortina-Borja
Helen Bedford
Suzanne Walton
Carol Dezateux
Ronan A Lyons


Harmonisation of different data sources from various electronic health records (EHRs) across systems enhances the potential scope and granularity of data available to health data research.

To describe data harmonisation of routine electronic healthcare records in Wales and Scotland linked to a UK longitudinal birth cohort, the Millennium Cohort Study (MCS).

Comparable secondary care data was linked, with parental consent, to MCS information for 1838 and 1431 children participating in MCS and residing in Wales and Scotland, by assigning, respectively, unique Anonymised Linkage Fields to personbased records in the privacy protecting Secure Anonymised Information Linkage (SAIL) databank at Swansea University, and by the National Health Service (NHS) Information Standards Division. Survey and non-response weights were created to account for the clustered sample, sample attrition and consent to linkage. Heterogeneous variables from the Patient Episode Dataset for Wales, Emergency Department Data Set for Wales, Scottish Medical Record 01 and Accident and Emergency dataset for Scotland were harmonised enabling data to be pooled and standardised for research.

Overall linkage to harmonised health care data was achieved for 98.9% (99.9% for Wales and 97.6% for Scotland) of consented MCS participants. 66% of children experienced at least one hospital admission (total 5747 hospital admissions) up to
their 14th birthday, while 60% attended A&E departments at least once (total 5221 attendances) between their 9th and 14th birthday. We managed date granularity by generating random dates of birth, standardising periods of data collection,
identifying inconsistencies and then mapping and bridging differences in definitions of periods of care across countries and datasets.

Combining and harmonising data from multiple sources and linking them to information from a longitudinal cohort create useful resources for population health research. These methods are reproducible and can be utilised by other researchers
and projects.

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How to Cite
Bandyopadhyay, A., Tingay, K., Akbari, A., Griffiths, L., Cortina-Borja, M., Bedford, H., Walton, S., Dezateux, C. and Lyons, R. A. (2018) “Integrating electronic health records from different sources across the UK: lessons from a record linkage study”, International Journal of Population Data Science, 3(2). doi: 10.23889/ijpds.v3i2.495.

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