Projects per year
Methods: Data were obtained from pseudonymised EHRs of 1,835 people with FEP in South London. Exposure to cannabis, cocaine, MDMA or amphetamines was identified using TextHunter NLP software. Data on subsequent hospital admission in the 5 years following presentation were obtained. Their relationship with illicit substance misuse was analysed using multivariable negative binomial regression with age, gender and ethnicity as covariates.
Results: Cannabis was the most frequently documented illicit substance (58.5% of patients) followed by cocaine (24.4%), amphetamines (3.7%) and MDMA (3.1%). Cannabis (IRR 1.58, 95% CI 1.37 to 1.83) and cocaine (1.36, 1.17 to 1.59) were significantly associated with increased number of hospital admissions while MDMA was associated with a reduction in number of hospital admissions (0.59, 0.40 to 0.86) and amphetamines with no significant difference (1.05, 0.77 to 1.45).
Conclusion: Cannabis and cocaine use are associated with a significant increase in number of hospital admissions following presentation to mental health services with psychosis. These findings highlight the importance of illicit substances in determining clinical outcomes in psychosis and the need to address their use when planning treatment.
|Number of pages||1|
|Journal||Early Intervention in Psychiatry|
|Publication status||Published - 17 Sept 2018|
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- 2 Finished
Linking electronic health records with passive smartphone activity data to predict outcomes in psychotic disorders
14/02/2018 → 13/02/2021
Symptom dimensions in first episode psychosis: predicting clinical outcomes using natural language processing
3/10/2016 → 2/10/2018