Abstract

Abstract In this talk I will describe how electronic health record (EHR) data can be analysed to provide novel insights into the clinical outcomes of people with serious mental disorders and how the analysis of unstructured, free text clinical assessments using natural language processing (NLP) could improve our understanding of clinical phenotypes and their associations with clinical outcomes. I will also describe how EHR data visualisation tools could provide clinicians with actionable insights to support mental healthcare delivery in clinical practice.

Biography Dr Rashmi Patel is an NIHR Advanced Fellow at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London (KCL) and Vice President for Medical and Scientific Affairs at Holmusk, a mental healthcare data analytics company specialising in real-world evidence generation from EHR data. He has developed NLP techniques to investigate clinical outcomes in people with serious mental disorders using de-identified free text EHR data from the SLaM Biomedical Research Centre (BRC) Case Register. Dr Patel has been awarded an NIHR Advanced Fellowship to develop data visualisation tools to feedback clinical data from EHRs to frontline clinicians to improve the delivery of remote mental healthcare. His vision is to harness EHR and digital mental healthcare data to provide clinicians and patients with actionable insights to better personalise treatment delivery and improve clinical outcomes. For more information on Dr Patel, please visit: https://www.kcl.ac.uk/people/dr-rashmi-patel