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Negative symptoms in schizophrenia: a study in a large clinical sample of patients using a novel automated method
  1. Rashmi Patel1,
  2. Nishamali Jayatilleke2,
  3. Matthew Broadbent3,
  4. Chin-Kuo Chang2,
  5. Nadia Foskett4,
  6. Genevieve Gorrell5,
  7. Richard D Hayes2,
  8. Richard Jackson2,
  9. Caroline Johnston6,
  10. Hitesh Shetty3,
  11. Angus Roberts5,
  12. Philip McGuire1,
  13. Robert Stewart2
  1. 1Department of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
  2. 2Department of Psychological Medicine, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
  3. 3South London and Maudsley NHS Foundation Trust, Biomedical Research Centre Nucleus, London, UK
  4. 4Roche Products Limited, Welwyn Garden City, UK
  5. 5Department of Computer Science, The University of Sheffield, Portobello, Sheffield, UK
  6. 6Social Developmental and Genetic Psychiatry Department, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
  1. Correspondence to Dr Rashmi Patel; bmj{at}rpatel.co.uk

Abstract

Objectives To identify negative symptoms in the clinical records of a large sample of patients with schizophrenia using natural language processing and assess their relationship with clinical outcomes.

Design Observational study using an anonymised electronic health record case register.

Setting South London and Maudsley NHS Trust (SLaM), a large provider of inpatient and community mental healthcare in the UK.

Participants 7678 patients with schizophrenia receiving care during 2011.

Main outcome measures Hospital admission, readmission and duration of admission.

Results 10 different negative symptoms were ascertained with precision statistics above 0.80. 41% of patients had 2 or more negative symptoms. Negative symptoms were associated with younger age, male gender and single marital status, and with increased likelihood of hospital admission (OR 1.24, 95% CI 1.10 to 1.39), longer duration of admission (β-coefficient 20.5 days, 7.6–33.5), and increased likelihood of readmission following discharge (OR 1.58, 1.28 to 1.95).

Conclusions Negative symptoms were common and associated with adverse clinical outcomes, consistent with evidence that these symptoms account for much of the disability associated with schizophrenia. Natural language processing provides a means of conducting research in large representative samples of patients, using data recorded during routine clinical practice.

  • negative symptoms
  • schizophrenia
  • psychosis
  • natural language processing
  • electronic health records
  • text mining

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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