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. 2016 Mar 1;6(3):e008721.
doi: 10.1136/bmjopen-2015-008721.

Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource

Gayan Perera  1 , Matthew Broadbent  2 , Felicity Callard  3 , Chin-Kuo Chang  1 , Johnny Downs  1 , Rina Dutta  1 , Andrea Fernandes  1 , Richard D Hayes  1 , Max Henderson  1 , Richard Jackson  1 , Amelia Jewell  1 , Giouliana Kadra  1 , Ryan Little  2 , Megan Pritchard  1 , Hitesh Shetty  2 , Alex Tulloch  1 , Robert Stewart  1
Affiliations

Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource

Gayan Perera et al. BMJ Open. .

Abstract

Purpose: The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development.

Participants: Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250,000 patient records accessed through CRIS.

Findings to date: Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations.

Future plans: Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20,000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.

Keywords: BIOTECHNOLOGY & BIOINFORMATICS; EPIDEMIOLOGY; MENTAL HEALTH; PSYCHIATRY.

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Figures

Figure 1
Figure 1
Diagram/map of CRIS technical architecture including natural language processing and data linkage. CRIS, Clinical Record Interactive Search; GATE, General Architecture for Text Engineering; SLaM, South London and Maudsley.
Figure 2
Figure 2
Maps contextualising deprivation levels in the South London and Maudsley (SLaM) catchment compared with London as a whole, and illustrating the distribution of recorded residences for active patients (on 31 December 2014) within London.
Figure 3
Figure 3
(A, B) Maps showing distribution of deprivation levels in the four catchment boroughs served by South London and Maudsley (SLaM), the key hospital sites and the number of active patients (on 31 December 2014) across the same geography.
Figure 4
Figure 4
Maps illustrating the distribution of recorded residences for inactive patients (on 31 December 2014) within London and SLaM catchment area. LSOA, lower super output area; SLaM, South London and Maudsley.
See this image and copyright information in PMC

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