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Allocation of Users of Mental Health Services to Needs-Based Care Clusters

An Italian Pilot Study

Bibliographic Data

ID8906771
AuthorsAlessandro Barbato (0000-0001-7142-700X, Istituti di Ricovero e Cura a Carattere Scientifico, corresponding author), Angelo Barbato, Barbara D’avanzo (0000-0002-0361-7263, Mario Negri Institute for Pharmacological Research), Giovanni Corrao (0000-0002-1034-8444, University of Milano-Bicocca), Teresa Di Fiandra (0000-0003-1124-0600, Ministero della Salute), Lucia Ferrara (0000-0001-6955-8983, Bocconi University), Andrea Gaddini (Agenzia Regionale per la Protezione Ambientale del Piemonte), Carlotta Micaela Jarach (0000-0002-9963-1624, Mario Negri Institute for Pharmacological Research), Matteo Monzio Compagnoni (0000-0002-2105-4572, University of Milano-Bicocca), Alessio Saponaro (Regione Emilia-Romagna), Salvatore Scondotto (0000-0001-7620-3080, University of Milano-Bicocca), Valeria D Tozzi (0000-0002-0660-7853, Ministero della Salute), Antonio Lora (0000-0002-6806-5199, University of Milano-Bicocca)
Year2023
Volume60
Issue3
Pages494-503
Publication date2023-10-26
Open AccessYes
TypeARTICLE
VenueCommunity Mental Health Journal (JOURNAL)
Journal identifiersISSN: 0010-3853 • E-ISSN: 1573-2789
PublisherSpringer Science+Business Media (PUBLISHER • DE)
DOI10.1007/s10597-023-01200-3
OpenAlexW4387950391
LanguageEN
References cited19

In Italy, despite strong community-based mental health services, needs assessment is unsatisfactory. Using the Mental Health Clustering Tool (MHCT) we adopted a multidimensional and non-diagnosis dependent approach to assign mental health services users with similar needs to groups corresponding to resources required for effective care. We tested the MHCT in nine Departments of Mental Health in four Italian regions. After a brief training, 318 professionals assessed 12,938 cases with a diagnosis of schizophrenia, depression, bipolar disorder and personality disorder through the MHCT. 53% of cases were 40–59 years, half were females, 51% had a diagnosis of schizophrenia, 48% of cases were clinically severe. Clusters included different levels of clinical severity and diagnostic groups. The largest cluster was 11 (ongoing recurrent psychosis), with 18.9% of the sample, followed by cluster 3 (non-psychotic disorders of moderate severity). The MHCT could capture a variety of problems of people with mental disorders beyond the traditional psychiatric assessment, therefore depicting service population from a different standpoint. Following a brief training, MHCT assessment proved to be feasible. The automatic allocation of cases made the attribution to clusters easy and acceptable by professionals. To what extent clustering provide a sound base for care planning will be the matter of further research

Environmental health · Health care · Health psychology · Mental health · Mental health care · Political science · Psychiatry · Public health · Medicine · Mental Health and Patient Involvement · Mental Health Treatment and Access · Nursing · Psychiatric care and mental health services · Psychology · Gerontology

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