Advancing methodology and linkages in electronic health records for mental health research

In 2018, the Medical Research Council provided funding totalling £10 million to nine UK universities, including UCL, to further our understanding and treatment of mental health disorders through the Mental Health Pathfinder grants. In particular, these grants were intended to support studies which help build the systems, infrastructure, and insight that will help researchers make the best use of Big Data to help unlock the secret to better diagnosis, treatment and ultimately prevention of mental health conditions.

UCL’s proposal, led by Professor David Osborn, aims to enhance UCL’s Electronic Mental Health Record capacity through new linkage, new data discovery methods, involving large databases of adults and/or children in primary and secondary care. This will determine the effectiveness, precision and safety of mental health interventions.

On this grant, I am advancing two objectives, namely, the strategic linkage of the Clinical Record Interactive Search (CRIS) Research Database at Camden & Islington NHS Foundation Trust to other datasets to expand and enhance the research capabilities of the existing Research Database. I am also investigating machine learning (ML)/natural language processing (NLP) approaches to applying semantic annotation to unstructured clinical free-text to enhance the use of routinely collected data for epidemiological and service evaluation studies.