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Exploring the predictors of early readmission to psychiatric hospital

Published online by Cambridge University Press:  23 February 2015

A. D. Tulloch Open the ORCID record for A. D. Tulloch [Opens in a new window] ,
A. S. David Open the ORCID record for A. S. David [Opens in a new window]  and
G. Thornicroft
A. D. Tulloch*
Affiliation:
King's College London, King's Health Partners, Institute of Psychiatry, PO29, De Crespigny Park, London SE5 8AF, UK
A. S. David
Affiliation:
King's College London, King's Health Partners, Institute of Psychiatry, PO29, De Crespigny Park, London SE5 8AF, UK
G. Thornicroft
Affiliation:
King's College London, King's Health Partners, Institute of Psychiatry, PO29, De Crespigny Park, London SE5 8AF, UK
*
*Address for correspondence: Dr A. D. Tulloch, King's College London, King's Health Partners, Institute of Psychiatry, PO29, De Crespigny Park, London SE5 8AF, UK. (Email: alex.tulloch@kcl.ac.uk)
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Abstract

Background.

Aims of this study are to explore the associations of readmission to psychiatric hospital over time, to develop a statistical model for early readmission to psychiatric hospital and to assess the feasibility of predicting early readmission.

Method.

The sample comprised 7891 general psychiatric discharges in South London, taken from a large anonymised repository of electronic patient records. We initially explored time to readmission using Cox regression – this included investigation of time-dependent effects. Subsequently, we used logistic regression to create a predictive model for 90-day readmission. We investigated the effect on readmission of a set of variables that included demographic variables, diagnosis and legal status during the index admission, previous service use, housing variables and individual item scores on the Health of the Nation Outcome Scales (HoNOS) at admission and at discharge.

Results.

Fifteen per cent of those discharged were readmitted within 90 days. Cox regression demonstrated that the estimated baseline hazard of readmission declined steeply after discharge and that the effects of several predictors, especially diagnosis, changed over time – most notably, personality disorder was associated with increased readmission relative to schizophrenia at the time of discharge, but did not significantly differ by 1-year postdischarge. In the logistic regression, increased readmission was associated with personality disorder diagnosis; shorter length of the index admission (excepting zero length admissions); number of discharges in the preceding 2 years; and having a high score at discharge on the HoNOS overactive and aggressive behaviour item, cognitive problems item or hallucinations and delusions items. Detention under Section 3 or a forensic section of the Mental Health Act during the index admission was associated with reduced readmission. The coefficient of discrimination for the logistic regression, which is equivalent to r2, was 0.04 and the estimated area under the receiver operating curve was 0.65.

Conclusions.

The association found between early readmission and personality disorder diagnosis merits further investigation, as does the possible trade-off between reduction in length of stay and increased readmission. Other novel findings such as the associations found with HoNOS item scores also merit replication. As with previous studies, we found that the rate of readmission declines steeply after hospital discharge, so that the period immediately subsequent to discharge is a period of comparatively high risk. However, prediction of early readmission within this high-risk group remains challenging – it seems most likely that many unmeasured influences operate subsequent to the time of discharge.

Keywords

Hospitalpatient readmissionpsychiatricPsychiatric Department
Type
Original Articles
Information
Epidemiology and Psychiatric Sciences , Volume 25 , Issue 2 , April 2016 , pp. 181 - 193
Copyright
Copyright © Cambridge University Press 2015 

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