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Objective – The aims of this study are: (1) to estimate patients' costs in Italian non hospital Residential Facilities (RF); (2) to analyse the relationship between the costs of care received by residents and patients' or facilities characteristics. Method – The PROGRES study included all Italian private and public RF (1370) with more than 4 beds. Of those, 265 were selected through stratified random sampling to be included in phase 2. Data were obtained through a schedule filled in by the facility manager. Additional information about costs related to the use of Community Psychiatric Service (CPS) by residents has also been collected. The cost components of residential accommodation include the costs of the RF, of the CPS, of general medical care, of the informal assistance provided by family or friends, and other non-medical costs. Results – The mean annual cost of stay in RFs was approximately 34,000 Euro, and it was related to the RF size and to staffing levels. Both RF and CPS are more expensive in the north of Italy, as compared to the center and the south. Costs were lower for older patients. CPS costs are lower when RF staffing levels are higher. Conclusions – In general, patients in RFs cost between 20,000 and 40,000 Euro per year; to this sum, additional 2,000-6,000 Euros per year should be added to include the costs of care provided outside the facility. Both RFs and CPS have different costs depending on the geographical area where the facilities are located, and staffing levels. Changes in CPS costs seem to be related to patients' characteristics.
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.
Aims — To investigate the prevalence of psychotherapy intervention in five Italian Centres for Mental Health. Analysing sociodemographic characteristics, geographical differences, frequencies of psychotherapy interventions, and the costs of these interventions. Methods — Five Italian Community—based Psychiatric Services collected data from 1250 patients during October 2002. Socio—demographic and clinical characteristics and GAF scores were collected at baseline. All psychiatric contacts during the following six months were recorded and categorised into 24 service contact categories. A comparison between patients who received or did not receive psychotherapy was made. Results — The socio—demographic characteristics of patients are very similar to those found in previous studies; there is a great difference in the number of psychotherapy treatments between the five areas. Psychotherapy patients use different services compared to the other patients, and their care cost less. Conclusions — This study provides a description of the provision of psychotherapy by Italian Mental Health Services. Further research is required into this topic.
Aims – The Diagnostic Interview for Psychoses (DIP) is a comprehensive interview schedule for psychotic disorders, linked to the OPCRIT diagnostic algorithm, bridging the gap between fully structured, lay-administered schedules and semistructured, psychiatrist-administered interviews. Here we describe the validity, reliability and applications of the Italian version of the DIP. Methods – The interview was translated into Italian and its content validity tested by back translation. Sixty patients, drawn from among those who contacted the South-Verona Community Mental Health Service, were included in the study. Each patient was first assessed independently by two raters, one of whom conducted the interview, while the other assumed the role of observer. Subsequently (median: 89 days), 44 of these patients were re-interviewed by a third rater, who made an independent assessment. Diagnostic validity was assessed in 18 cases, interviewed with the DIP and using the SCAN as ‘gold standard. Results – The mean duration of the interview was 37 minutes for the inter-rater interviews and 39 minutes for the retest interviews. Good to excellent inter-rater reliability was demonstrated for both ICD-10 and DSM-IV diagnoses, while in the test-retest reliability pairwise agreement was high for half of the items. Diagnostic validity was good, with twelve out of the 18 DIP-OPCRIT diagnoses (67%) matching the SCAN diagnosis. Conclusions – Overall, the results support the reliability and validity of the Italian translation of the DIP. The Italian version will be useful both in routine practice to establish standard reference diagnoses of psychosis and in the research field, where it can be used by academic researchers in clinical trials and epidemiological studies.
Aim – 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, identifing 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. Conclusion – 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.
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