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Mental health clustering and diagnosis in psychiatric in-patients

  • Liam Trevithick (a1), Jon Painter (a1) and Patrick Keown (a1)
Abstract
Aims and method

This paper investigates the relationship between cluster (Mental Health Clustering Tool, MHCT) and diagnosis in an in-patient population. We analysed the diagnostic make-up of each cluster and the clinical utility of the diagnostic advice in the Department of Health's Mental Health Clustering Booklet. In-patients discharged from working-age adult and older people's services of a National Health Service trust over 1 year were included. Cluster on admission was compared with primary diagnosis on discharge.

Results

Organic, schizophreniform, anxiety disorder and personality disorders aligned to one superclass cluster. Alcohol and substance misuse, and mood disorders distributed evenly across psychosis and non-psychosis superclass clusters. Two-thirds of diagnoses fell within the MHCT ‘likely’ group and a tenth into the ‘unlikely’ group.

Clinical implications

Cluster and diagnosis are best viewed as complimentary systems to describe an individual's needs. Improvements are suggested to the MHCT diagnostic advice in in-patient settings. Substance misuse and affective disorders have a more complex distribution between superclass clusters than all other broad diagnostic groups.

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Copyright
This is an open-access article published by the Royal College of Psychiatrists and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
Correspondence to Patrick Keown (patrick.keown@ncl.ac.uk)
Footnotes
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Declaration of interest

None.

Footnotes
References
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1 Self, R, Rigby, A, Legget, C, Paxton, R. Clinical Decision Support Tool: A rational needs-based approach to making clinical decisions. J Ment Health 2008; 17: 3348.
2 Wing, JK, Curtis, RH, Beevor, AS. HoNOS: Health of the Nation Outcome Scales Trainers' Guide. Royal College of Psychiatrists' Research Unit, 1996.
3 Department of Health. The Mental Health Clustering Booklet v 3.0 2013/14. Department of Health, 2013.
4 World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. World Health Organization, 1992.
5 Bekas, S, Michev, O. Payment by results: validating care cluster allocation in the real world. Psychiatrist 2013; 37: 349–55.
6 Tyrer, P, Johnson, T. Establishing the severity of personality disorder. Am J Psychiatry 1996; 153: 1593–7.
7 Kirkbride, JB, Errazuriz, A, Croudace, TJ, Morgan, C, Jackson, D, Boydell, J, et al. Incidence of schizophrenia and other psychoses in England, 1950–2009: a systematic review and meta-analyses. PLoS ONE 2012; 7: e31660.
8 McGorry, PD. Early intervention in psychotic disorders: beyond debate to solving problems. Br J Psychiatry 2005; 187 (suppl 48): s10810.
9 Royal College of Psychiatrists. Mental Health Clustering Tool (MHCT) – Frequently Asked Questions. RCPsych 2011; 4.1.
10 NHS England. Practice Guidance Note Regarding: Allocation of Patients with a Bipolar Diagnosis to a Cluster. NHS England, in press.
11 Self, R, Painter, J. Study: To improve and demonstrate the structural properties of the care clusters that form the basis of the PbR currency development programme (Care Pathways and Packages Project). CPPP, 2009.
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BJPsych Bulletin
  • ISSN: 2056-4694
  • EISSN: 2056-4708
  • URL: /core/journals/bjpsych-bulletin
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Mental health clustering and diagnosis in psychiatric in-patients

  • Liam Trevithick (a1), Jon Painter (a1) and Patrick Keown (a1)
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