Applied natural language processing in mental health big data
Robert Stewart, Sumithra Velupillai
Abstract
‘Big data’ has transformative potential in mental health research, including the use of data from electronic health records and the ‘unlocking’ of text-field information contained here through natural language processing (NLP). Over the last 10 years, we have made substantial progress in applying NLP within the Clinical Record Interactive Search (CRIS) platform to enhance research at the South London and Maudsley Trust (SLaM): a large mental healthcare provider serving an urban catchment of around 1.3 million residents. CRIS provides a deidentified copy of SLaM’s electronic health record [ 1 ], accessed within a robust data security and governance framework, currently drawing data from over 500,000 patients and having supported over 200 published research papers. A number of other UK mental healthcare providers now have CRIS-like capability, extending the potential for multi-site projects.