Pioneering link between census data and electronic mental health records

King's College London researchers are the first research team in England, to link electronic mental health care records to census data, at an individual level.

Published in the BMJ Open the study involved linking de-identified data (with personal information removed) of 459,374 patients from South London and Maudsley NHS Foundation Trust to census data from 2011.

Researchers linked just over half (50.4%) of the records and found that certain groups—young people between 25 and 34, and those from deprived areas and minority ethnic groups—were less likely to be matched to a census record.

"This is the first time that large-scale routine mental health records have been successfully linked to individual socio-demographic data from the census in England and we achieved successful linkage for over half the records. The lower census response rate in those with severe mental illness is a potential concern, as the information is vital for service planning and the allocation of resources," says Dr. Jayati Das-Munshi.

The likelihood of matching records across the two sets of data varied with the type of mental health condition. There were lower rates of success in those with schizophrenia or with mental disorders due to substance use. The rate of successful pairing was higher in those with mental disorders caused by brain injury or disease, as did those with frequent contact with services.

The aim of the study was to address the absence of socio-economic data in electronic health care records so the social factors of severe mental illness could be examined.

The study used the Clinical Research Interactive Search (CRIS) system to extract de-identified records from South London and Maudsley NHS Foundation Trust and gauged the effect of potential biases caused by non-matched records.

Dr. Das-Munshi added, "In this study, we developed statistical methods, which will help us to minimize the impact of missing census data on future work. This new linked dataset will allow us to understand how social experiences impact the onset and outcomes of mental health conditions, at a scale which has never previously been possible in England."