scholarly journals The Right to ‘Have a Say’ in the Deinstitutionalisation of Mental Health in Slovenia

2021 ◽  
Vol 9 (3) ◽  
pp. 190-200 ◽  
Author(s):  
Mojca Urek

In a time when the deinstitutionalisation of mental health services has become a global and European platform and one of the main forms of care provision, a theme such as the transition of care from large institutions down to a more personal community level care might seem outlived, but the fact is that in some European countries the discussion has revolved for almost 35 years around the most basic question concerning the closure of large, asylum‐type mental health institutions. In this article, I provide a historical overview and analysis of deinstitutionalisation processes in the field of mental health in Slovenia from mid‐1980s onwards, interpreted in terms of achievements and gaps in community‐based care and in user participation in these processes. It demonstrates some of the innovative participatory practices and their potential to transform services. A thematic data analysis was used to analyse the data collected from various primary (a focus group) and secondary sources (autobiographies, newspaper articles, round table reports, blogs) that all bear witness to the different periods of deinstitutionalisation and the user perspective in it.

2006 ◽  
Vol 15 (4) ◽  
pp. 295-306 ◽  
Author(s):  
Laura Grigoletti ◽  
Francesco Amaddeo ◽  
Aldrigo Grassi ◽  
Massimo Boldrini ◽  
Marco Chiappelli ◽  
...  

SummaryAims – To obtain a new, well-balanced mental health funding system, through the creation of i) a list of psychiatric interventions provided by Italian Community-based Psychiatric Services (CPS), and associated costs; ii) a new prospective funding system for patients with a high use of resources, based on packages of care. Methods – Five Italian Community-based Psychiatric Services collected data from 1250 patients during October 2002. Socio-demographical and clinical characteristics and GAF scores were collected at baseline. All psychiatric contacts during the following six months were registered and categorised into 24 service contact types. Using elasticity equation and contact characteristics, we estimate the costs of care. Cluster analysis techniques identified packages of care. Logistic regression defined predictive variables of high use patients. Multinomial Logistic Model assigned each patient to a package of care. Results – The sample's socio-demographic characteristics are similar, but variations exist between the different CPS. Patients were then divided into two groups, and the group with the highest use of resources was divided into three smaller groups, based on number and type of services provided. Conclusions – Our findings show how is possible to develop a cost predictive model to assign patients with a high use of resources to a group that can provide the right level of care. For these patients it might be possible to apply a prospective per-capita funding system based on packages of care.Declaration of Interest: None


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