A predictive model to allocate frequent service users of community-based mental health services to different packages of care.
OBJECTIVE
To develop predictive models to allocate patients into frequent and low service users groups within the Italian Community-based Mental Health Services (CMHSs). To allocate frequent users to different packages of care, identifying the costs of these packages.


METHODS
Socio-demographic and clinical data and GAF scores at baseline were collected for 1250 users attending five CMHSs. All psychiatric contacts made by these patients during six months were recorded. A logistic regression identified frequent service users predictive variables. Multinomial logistic regression identified variables able to predict the most appropriate package of care. A cost function was utilised to estimate costs.


RESULTS
Frequent service users were 49%, using nearly 90% of all contacts. The model classified correctly 80% of users in the frequent and low users groups. Three packages of care were identified: Basic Community Treatment (4,133 Euro per six months); Intensive Community Treatment (6,180 Euro) and Rehabilitative Community Treatment (11,984 Euro) for 83%, 6% and 11% of frequent service users respectively. The model was found to be accurate for 85% of users.


CONCLUSIONS
It is possible to develop predictive models to identify frequent service users and to assign them to pre-defined packages of care, and to use these models to inform the funding of psychiatric care.
Grigoletti
Laura
L
Department of Medicine and Public Health, Section of Psychiatry and Clinical Psychology, University of Verona, Verona, Italy. laura.grigoletti@univr.it
Amaddeo
Francesco
F
Grassi
Aldrigo
A
Boldrini
Massimo
M
Chiappelli
Marco
M
Percudani
Mauro
M
Catapano
Francesco
F
Fiorillo
Andrea
A
Perris
Francesco
F
Bacigalupi
Maurizio
M
Albanese
Paolo
P
Simonetti
Simona
S
De Agostini
Paola
P
Tansella
Michele
M
D003156:Community Mental Health Services / Q000600:supply & distribution*; D005260:Female; D006801:Humans; D007558:Italy; D008297:Male; D015233:Models, Statistical