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Dr Rina Dutta Reader in Suicidology and Psychiatry

Organisation: Kings College London

Fellowship(s):
  • Clinician Scientist Fellowship
  • 4
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About me

Rina is Reader in Suicidology and Psychiatry at Kings College London.

She has a PhD in Psychological Medicine and Psychiatry. Prior to her Clinician Scientist Fellowship award she was an MRC Research Training Fellow at King’s College London. Since 2009 she has been Consultant Psychiatrist to the National Affective Disorders Service Healthcare Professionals Clinic at the Maudsley Hospital. Her specialism is general psychiatry with sub-specialisation in liaison psychiatry.

Rina fellowship project focuses on electronic patient records. She aims to study how patients behave in the lead up to a serious suicide attempts and so learn to identify new early warning signs. She says her research has the potential to save lives.

By 2018, all NHS patient records should become electronic. Some NHS trusts have already shifted their patients’ records into an electronic format. Rina will be using these digital, anonymous patient records to find new ways to predict and prevent serious suicide attempts.

Rina says her project will improve care and save lives. The knowledge she hopes to gain has the potential to improve patient risk assessments and so reduce the chances of suicide attempts. 'Everyday across the country, psychiatrists and multidisciplinary teams do countless risk assessments to prevent suicide attempts, but it is still so unpredictable that assessments are frequently inaccurate,' says Rina.

'Suicide is something you simply would not do if your mind was healthy. It’s a terrible moment in time that results in mortality and ultimately lifelong pain and suffering for family, friends and carers. If we can predict it, we can prevent it. We can save lives and help people regain their mental health. Now we have access to the information we need, we absolutely must do this research.'

Working with a small research team and guided by patient feedback, Rina will be using natural language processing and proven IT strategies. She will be searching the data for new early warning signs that can be used to stop a serious suicide attempt, which could be 'anything from a key phrase said to the doctor, or it could be the way the person uses a service – like being late for appointments, or repeatedly visiting A&E.

'We have a high level of detail we can access,' Rina explains. 'Everything is anonymous but what we can search for are subtle markers related to symptoms, behaviour and health service use. I think this is where vital indicators may be found.'

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