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

Amaddeo, F.

Donisi, V.

Grigoletti, L.

Jones, J.

Pertile, R.

Salazzari, D.

Tansella, M.

English

City Research Online

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

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%R2increase) 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.</jats:sec

V. Donisi

J. Jones

R. Pertile

D. Salazzari

L. Grigoletti

M. Tansella

F. Amaddeo

Crossref

Epidemiology and Psychiatric Sciences

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

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. 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.
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.
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

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

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