Negative symptoms in schizophrenia: a study in a large clinical sample of patients using a novel automated method

TY - JOUR

T1 - Negative symptoms in schizophrenia

T2 - a study in a large clinical sample of patients using a novel automated method

AU - Patel, Rashmi

AU - Jayatilleke, Nishamali Lakshani

AU - Broadbent, Matthew

AU - Chang, Chin-Kuo

AU - Foskett, Nadia

AU - Gorrell, Genevieve

AU - Hayes, Richard Derek

AU - Jackson, Richard George

AU - Johnston, Caroline

AU - Shetty, Hitesh

AU - Roberts, Angus

AU - McGuire, Philip

AU - Stewart, Robert James

PY - 2015/9/8

Y1 - 2015/9/8

N2 - 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.

AB - 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.

U2 - 10.1136/bmjopen-2015-007619

DO - 10.1136/bmjopen-2015-007619

M3 - Article

SN - 2044-6055

VL - 5

JO - BMJ Open

JF - BMJ Open

IS - 9

M1 - e007619

ER -