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Using activity data to explore the influence of case-load size on care patterns

Department of Psychiatry

Helen Doll, DPhil, HRSU

Department of Public Health and Primary Care, University of Oxford, Oxford

Tom Fahy, MD

Department of Forensic Mental Health Science, Institute of Psychiatry, King's College London

Matthew Fiander, PhD

Department of Mental Health, St George's, University of London

Peter Tyrer, MD

Division of Neuroscience and Psychological Medicine, Imperial College, London, UK

Correspondence: Professor Tom Burns, Social Psychiatry, University Department of Psychiatry, Warneford Hospital, Headington, Oxford OX3 7JX, UK. Tel: +44 (0)1865 226474; fax +44 (0)1865 793101; email: tom.burns{at}psych.ox.ac.uk

Declaration of interest P.T. is editor of the British Journal of Psychiatry but had no part in the evaluation of this paper for publication.

Background A limited case-load size is considered crucial for some forms of intensive case management and many countries have undertaken extensive reorganisation of mental health services to achieve this. However, there has been limited empirical work to explore this specifically.

Aims To test whether there is a discrete threshold for changes in intensive case management practice determined by case-load size.

Method `Virtual' case-load sizes were calculated for patients from their actual contacts over a 2-year period and were compared with the proportions of contacts devoted to medical and non-medical care (as a proxy for a more comprehensive service model).

Results There were 39 025 recordings for 545 patients over 2 years, with a mean rate of contacts per full-time case manager per month of 48 (range 35–60). There was no variation in the proportion of non-medical contacts when case-load sizes were over 1:20 but there was a convincing linear relationship when sizes were between 1:10 and 1:20.

Conclusions Case-load size between 1:10 and 1:20 does affect the practice of case management. However, there is no support for a paradigm shift in practice at a discrete level.

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