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Natural language processing: unlocking the potential of electronic health record data to support transdiagnostic psychiatric research

  • Rashmi Patel
    Correspondence
    Correspondence to: Rashmi Patel, King’s College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
    Affiliations
    Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Holmusk Technologies Inc, New York, NY, USA
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  • Matthew Wickersham
    Affiliations
    Weill-Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program, New York, NY, USA
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  • Rudolf N. Cardinal
    Affiliations
    Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK; Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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  • Paolo Fusar-Poli
    Affiliations
    Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
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  • Christoph U. Correll
    Affiliations
    Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Charité – Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin, and Berlin Institute of Health, Berlin, Germany

    Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA

    Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
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Published:September 08, 2022DOI:https://doi.org/10.1016/j.bpsc.2022.09.002
Natural language processing: unlocking the potential of electronic health record data to support transdiagnostic psychiatric research
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      Mental disorders bring a substantial burden of illness and disability, but their underlying etiology and pathophysiology remains poorly characterized. Here, we outline the potential for data derived from natural language processing (NLP) of electronic health records (EHRs) to support transdiagnostic approaches to characterize mental disorders.

      Keywords

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      References

        • Lee P.H.
        • Anttila V.
        • Won H.
        • Feng Y.C.A.
        • Rosenthal J.
        • Zhu Z.
        • et al.
        Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders.
        Cell. 2019; 179 (e11): 1469-1482
        View in Article
        • Pahwa M.
        • Sleem A.
        • Elsayed O.H.
        • Good M.E.
        • El-Mallakh R.S.
        New Antipsychotic Medications in the Last Decade.
        Curr Psychiatry Rep. 2021; 23: 87
        View in Article
        • McGorry P.
        • Nelson B.
        Why we need a transdiagnostic staging approach to emerging psychopathology, early diagnosis, and treatment.
        JAMA Psychiatry. 2016; 73: 191-192
        View in Article
        • Patel R.
        • Wee S.N.
        • Ramaswamy R.
        • Thadani S.
        • Tandi J.
        • Garg R.
        • et al.
        NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data.
        BMJ Open. 2022; 12e057227
        View in Article
        • Jackson R.G.
        • Patel R.
        • Jayatilleke N.
        • Kolliakou A.
        • Ball M.
        • Gorrell G.
        • et al.
        Natural language processing to extract symptoms of severe mental illness from clinical text: The Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project.
        BMJ Open. 2017; 7https://doi.org/10.1136/bmjopen-2016-012012
        View in Article

      6. Henry S, Yetisgen M, Uzuner O (2021): Chapter 13: Natural Language Processing in Mental Health Research and Practice. In: Tenenbaum JD, Ranallo PA, editors. Mental Health Informatics: Enabling a Learning Mental Healthcare System. Cham: Springer International Publishing, pp 317–353.

        View in Article
        • Patel R.
        • Jayatilleke N.
        • Broadbent M.
        • Chang C.K.
        • Foskett N.
        • Gorrell G.
        • et al.
        Negative symptoms in schizophrenia: A study in a large clinical sample of patients using a novel automated method.
        BMJ Open. 2015; 5https://doi.org/10.1136/bmjopen-2015-007619
        View in Article
        • Mascio A.
        • Stewart R.
        • Botelle R.
        • Williams M.
        • Mirza L.
        • Patel R.
        • et al.
        Cognitive Impairments in Schizophrenia: A Study in a Large Clinical Sample Using Natural Language Processing.
        Frontiers in Digital Health. 2021; 3https://doi.org/10.3389/fdgth.2021.711941
        View in Article
        • Fernandes A.C.
        • Dutta R.
        • Velupillai S.
        • Sanyal J.
        • Stewart R.
        • Chandran D.
        Identifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing.
        Sci Rep. 2018; 8: 7426
        View in Article
        • Irving J.
        • Patel R.
        • Oliver D.
        • Colling C.
        • Pritchard M.
        • Broadbent M.
        • et al.
        Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.
        Schizophr Bull. 2021; 47: 405-414
        View in Article

      Article Info

      Publication History

      Accepted: September 5, 2022
      Received: August 30, 2022

      Publication stage

      In Press Journal Pre-Proof

      Identification

      DOI: https://doi.org/10.1016/j.bpsc.2022.09.002

      Copyright

      © 2022 Published by Elsevier Inc on behalf of Society of Biological Psychiatry.

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