Understanding the prodrome to severe mental disorders is critical for prevention. Understanding their nature (duration, symptom evolution and presentation) is essential for early detection and intervention. Much of the existing knowledge is based on “look-back” interviews and small cohorts, which suffer from recall bias, limited generalisability and are not integrated into real-world clinical practice.
Electronic health records (EHRs) from secondary mental healthcare systems (e.g., South London and Maudsley NHS Trust) offer large-scale, contemporaneously recorded clinical data ideal for retrospective studies. This enables researchers to study prodromal features more contemporaneously, avoiding recall error. By using NLP to extract data from clinical notes, we have a dataset that allows us to analyse a wide array of prodromal symptoms (syndromes and substance use), grouped into clusters, and tracked monthly up to 12 years before a patient's first diagnosis.
I will present a programme of work using these data to characterise prodromal features that comprise the prodromes to psychosis, bipolar disorder and depression.
Title: Using electronic health records to characterise the prodromes to severe mental disorders
Speaker: Dominic Oliver, United Kingdom
GetDigial webinar series: digital approaches are fundamentally changing traditional ways of diagnosis, monitoring, management, and treatment of brain disorders worldwide. GetDigital is a webinar series on mHealth organised by the ECNP Digital Health Applied to the Clinical Research of Brain Disorders Network.
This online series aim at sharing and distributing new and high-quality research to researchers and clinicians, educating Early Career Scientists across Europe, and foster collaborations across research groups.
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