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The influence of patient variables on polypharmacy and combined high dose of antipsychotic drugs prescribed for in-patients

Royal College of Psychiatrists' Research Unit, 83 Victoria Street, London SW1H 0HW

Carol Paton, Chief Pharmacist

Oxleas NHS Trust

Maria Harrington, Multi-Centre Clinical Audit Programme Manager

Royal College of Psychiatrists' Research Unit

Maria Konsolaki, Statistician

Royal College of Psychiatrists' Research Unit

Tom Sensky, Reader in Psychological Medicine

Imperial College School of Medicine

Chike Okocha, Consultant Psychiatrist and Senior Lecturer in Psychiatry

Queen Elizabeth Hospital

Declaration of interest

C.P. has very occasionally received speaker fees from Eli Lilly and Pfizer. Over the past year she has been involved with research projects funded by Novartis, Eli Lilly and Janssen-Cilag, but has not received any personal income from those projects. T.S. has been paid honoraria by numerous pharmaceutical companies for contributing to educational events. In 2000 he attended a meeting as a participant in an advisory board for Pfizer. The views expressed do not necessarily reflect those of the Royal College of Psychiatrists.

See editorial pp. 401-402, and pp. 414-420, this issue.

AIMS AND METHOD

A 1-day census, involving 3576 psychiatric in-patients prescribed anti-psychotic medication, was conducted as a prelude to a multi-centre audit. The aim was to explore the extent to which a number of patient variables explain antipsychotic polypharmacy and the use of high doses of these drugs.

RESULTS

Prescriptions of more than one type of antipsychotic drug were made for 50.5% of patients. Patient factors that influenced the probability of polypharmacy were: younger age, being male, detained under the Mental Health Act and on a rehabilitation or forensic ward, and a diagnosis of schizophrenia. The effect of ethnicity was not significant. Polypharmacy was the most powerful factor influencing the probability of being prescribed a high dose. Identified patient variables accounted for only 18% of the variance in dose prescribed.

CLINICAL IMPLICATIONS

The patient and clinician factors that account for the unexplained variance need to be identified.

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