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.

Barbato, A., D'Avanzo, B., Corrao, G., Di Fiandra, T., Ferrara, L., Gaddini, A., et al. (2023). Allocation of Users of Mental Health Services to Needs-Based Care Clusters: An Italian Pilot Study. COMMUNITY MENTAL HEALTH JOURNAL [10.1007/s10597-023-01200-3].

Allocation of Users of Mental Health Services to Needs-Based Care Clusters: An Italian Pilot Study

Corrao, Giovanni;Monzio Compagnoni, Matteo
;
Lora, Antonio
Ultimo
2023

Abstract

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.
Articolo in rivista - Articolo scientifico
Determinants of Health; Epidemiology; MHCT; Prevention; Public Health; Public Mental Health;
English
26-ott-2023
2023
open
Barbato, A., D'Avanzo, B., Corrao, G., Di Fiandra, T., Ferrara, L., Gaddini, A., et al. (2023). Allocation of Users of Mental Health Services to Needs-Based Care Clusters: An Italian Pilot Study. COMMUNITY MENTAL HEALTH JOURNAL [10.1007/s10597-023-01200-3].
File in questo prodotto:
File Dimensione Formato  
Barbato-2023-Comm Mental health J-VoR.pdf

accesso aperto

Descrizione: Original Article
Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Licenza: Creative Commons
Dimensione 1.55 MB
Formato Adobe PDF
1.55 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/452139
Citazioni
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
Social impact