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The difficult task of predicting the costs of community-based mental health care. A comprehensive case register study

Published online by Cambridge University Press:  13 June 2011

V. Donisi ,
J. Jones ,
R. Pertile ,
D. Salazzari ,
L. Grigoletti ,
M. Tansella  and
F. Amaddeo
V. Donisi*
Affiliation:
Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Verona, Italy
J. Jones
Affiliation:
Department of Mental Health and Learning Disability, City University, London, UK
R. Pertile
Affiliation:
Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Verona, Italy
D. Salazzari
Affiliation:
Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Verona, Italy
L. Grigoletti
Affiliation:
Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Verona, Italy
M. Tansella
Affiliation:
Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Verona, Italy
F. Amaddeo
Affiliation:
Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Verona, Italy
*
*Address for correspondence: Dr V. Donisi, Ph.D., Psychologist, Section of Psychiatry and Clinical Psychology, Department of Public Health and Community Medicine, University of Verona, Policlinico G.B. Rossi, Piazzale L.A. Scuro 10, 37134 Verona, Italy. (Email: valeria.donisi@univr.it)
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Abstract

Background.

Previous studies have attempted to forecast the costs of mental health care, using clinical and individual variables; the inclusion of ecological measures could improve the knowledge of predictors of psychiatric service utilisation and costs to support clinical and strategic decision-making.

Methods.

Using a Psychiatric Case Register (PCR), all patients with an ICD-10 psychiatric diagnosis, who had at least one contact with community-based psychiatric services in the Verona Health District, Northern Italy, were included in the study (N = 4558). For each patient, one year's total cost of care was calculated by merging service contact data with unit cost estimates and clinical and socio-demographic variables were collected. A socio-economic status (SES) index was developed, as a proxy of deprivation, using census data. Multilevel multiple regression models, considering socio-demographic and clinical characteristics of patients as well as socioeconomic local characteristics, were estimated to predict costs.

Results.

The mean annual cost for all patients was 2,606.11 Euros; patients with an ongoing episode of care and with psychosis presented higher mean costs. Previous psychiatric history represented the most significant predictor of cost (36.99% R2 increase) and diagnosis was also a significant predictor but explained only 4.96% of cost variance. Psychiatric costs were uniform throughout the Verona Health District and SES characteristics alone contributed towards less than 1% of the cost variance.

Conclusions.

For all patients of community-based psychiatric services, a comprehensive model, including both patients' individual characteristics and socioeconomic local status, was able to predict 43% of variance in costs of care.

Keywords

case register studycost predictioncosts of community caresocioeconomic status
Type
Original Articles
Information
Epidemiology and Psychiatric Sciences , Volume 20 , Issue 3 , September 2011 , pp. 245 - 256
Copyright
Copyright © Cambridge University Press 2011

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