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This article presents a micro-macro integrated model/framework for the disaggregated quantitative assessment of the impacts of various shocks generated in five socio-economic and climate-driven simulations on the wine-grape sector in Veneto, Italy. (JEL Classifications: C01, C67, Q12, Q54)
This paper studies the distribution of resources within families with migrant member abroad. We derive a complete collective demand system with individual Engel effects for male and female adults and children, and the respective share of resources. The focus is on migrant-sending families in Albania, where gender and inter-generational inequalities are relevant social issues. The results show that the female share of resources is substantially lower with respect to an equal distribution and do not benefit from father’s migration. Children have a larger share of resources and benefit from their fathers migration, when women maintain control over family decisions and when the proportion of female children is larger (at the detriment of women).
Aims – In the last years, in Italy as well as in many other developed countries, there has been a growing interest for health economics by researchers. As for as the psychiatric care is concerned, more recently, many research's groups have pointed their attention on new possible funding systems for mental health services and on their effects on services' functioning. The aim of this study is to define a new list of services' costs based on services actually delivered by a Community Mental Health Service (CMHS). Methods. – All psychiatric contacts recorded by the South-Verona Psychiatric Case Register during a 7-year period (1992-1998) have been included in the study (125,623 contacts made by 2,819 patients). Contacts were grouped into 19 type of services. The cost function methodology was used to describe, also reporting elasticity values, costs' behaviour in the South-Verona CMHS. The cost of each service includes expenses for professionals involved (directly or indirectly) in the contacts with the patients and capital costs. Results. – For each service were reported a) the cost of the service as it is actually supplied in our CMHS, b) the cost per minute, c) an estimate of the cost of service delivered with standard modalities (duration equal to the mode value registered; staff composition take into account either the actual functioning of the CMHS either indication about a good clinical practice) and, finally, d) cost of the eight services included into the reimbursement system currently in use in Italy. Conclusions. – Our results showed that services' definition used in this study allow to describe different types of psychiatric care supplied from the South-Verona CMHS. The national list currently adopted for the reimbursement in Italy should allowed to describe only 28% of the registered psychiatric contacts (35,230 vs. 125,632). The urgent need for a new list of psychiatric services, accepted at a national level, was confirmed. Cost values obtained clearly show that the funding system currently used underestimates the true costs of care delivered by the CMHS. The cost function makes available a tool to test a prospective per-capita funding system as provided in the Act No. 229 of the Italian Government.
Aims – 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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