To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The present study investigated the relationship between suicide mortality and contact with a community mental health centre (CMHC) among the adult population in the Veneto Region (northeast Italy, population 4.9 million). Specifically, it estimated the effects of age, gender, time elapsed since the first contact with a CMHC, calendar year of diagnosis and diagnostic category on suicide mortality and modality.
The regional mortality archive was linked to electronic medical records for all residents aged 18–84 years who had been admitted to a CMHC in the Veneto Region in 2008. In total, 54 350 subjects diagnosed with a mental disorder were included in the cohort and followed up for a period of 10 years, ending in 2018. Years of life lost (YLL) were computed and suicide mortality was estimated as a mortality rate ratio (MRR).
During the follow-up period, 4.4% of all registered deaths were from suicide, but, given the premature age of death (mean 52.2 years), suicide death accounted for 8.7% of YLL; this percentage was particularly high among patients with borderline personality disorder (27.2%), substance use disorder (12.1%) and bipolar disorder (11.5%) who also presented the highest suicide mortality rates. Suicide mortality rates were halved in female patients (MRR 0.45; 95% CI 0.37–0.55), highest in patients aged 45–54 years (MRR 1.56; 95% CI 1.09–2.23), and particularly elevated in the 2 months following first contact with CMHCs (MRR 10.4; 95% CI 5.30–20.3). A sensitivity analysis restricted to patients first diagnosed in 2008 confirmed the results. The most common modalities of suicide were hanging (47%), jumping (18%), poisoning (13%) and drowning (10%), whereas suicide from firearm was rare (4%). Gender, age at death and time since first contact with CMHCs influenced suicide modality.
Suicide prevention strategies must be promptly initiated after patients’ first contact with CMHCs. Patients diagnosed with borderline personality disorder, substance use disorder and bipolar disorder may be at particularly high risk for suicide.
Socio-relational aspects are essential for mental wellbeing (MWB), especially in the oldest old age. Our study aims to explore the socio-relational aspects related to MWB in accordance with the experiences of the oldest old of four European countries; and to examine how these differ between Mediterranean and Nordic people. A total of 117 participants aged 80+ years old were recruited, and 23 focus groups were performed. Qualitative content analysis identified five main themes. Family seemed to be the most important driver of the MWB of the oldest old, followed by relationships with close friends. Participants felt better when they had a sense of being needed, cared for, and connected. Loneliness and isolation negatively affected MWB, although solitude was appreciated. Differences appeared between Mediterranean and Nordic regions. Initiatives to promote positive interactions with family and friends, as well as social activities within the community, may contribute to strengthening MWB in the oldest old.
Considerable variations in the incidence of psychosis have been observed across countries, in terms of age, gender, immigration status, urbanicity and socioeconomic deprivation.
To evaluate the incidence rate of first-episode psychosis in a large area of north-eastern Italy and the distribution of the above-mentioned risk factors in individuals with psychoses.
Epidemiologically based survey. Over a 3-year period individuals with psychosis on first contact with services were identified and diagnosed according to ICD-10 criteria.
In total, 558 individuals with first-episode psychosis were identified during 3 077 555 person-years at risk. The annual incidence rate per 100 000 was 18.1 for all psychoses, 14.3 for non-affective psychoses and 3.8 for affective psychoses. The rate for all psychoses was higher in young people aged 20–29 (incidence rate ratio (IRR) = 4.18, 95% CI 2.77–6.30), immigrants (IRR = 2.26, 95% CI 1.85–2.75) and those living in the most deprived areas (IRR = 2.09, 95% CI 1.54–2.85).
The incidence rate in our study area was lower than that found in other European and North American studies and provides new insights into the factors that may increase and/or decrease risk for developing psychosis.
Objective - After a review of recent developments in the economic evaluation of mental health care, the study described in this paper suggests a methodology for the measurement and evaluation of costs in the Italian psychiatric system. Method and results - To conduct such an evaluation it is necessary to identify all relevant services, collect data on patients' receipt or utilization of health services (direct costs) and other services and resources within the socio- economic system (indirect costs), and to attach monetary values for the costs. A detailed unit cost list (LICU) was constructed for facilities available at South-Verona Community Psychiatric Service (CPS), as well as in many other community-based psychiatric services in Italy. This list covers psychiatric services, other public and private health services, criminal justice services, voluntary organisations and self-help groups. The procedure for calculating costs in three of these facilities (hospital inpatient service, psychiatric outpatient service and rehabilitation groups) are described in this paper in detail. A new instrument (ICAP) was developed to collect the data required to calculate the costs of community care for individual patients. In order to check the applicability and comprehensibility of the instrument, and the time ne- eded for its administration, the ICAP was tested with five patients. Conclusions - It will be interesting to utilise ICAP and LICU in a larger sample. The methodology described here would provide the basis for epidemiologically-based studies, as well as exploration of the factors which predict cost differences (such as socio-demographic characteristics, diagnosis, psychiatric history, ecc). It is important to emphasise the insights for policy and practice which can flow for the merged examination of costs, needs and outcomes. This research is presently in progress in South-Verona.
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 – 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.
Amartya Sen, who received the Nobel Prize for Economics, has demonstrated that the incidence of deprivation, in terms of capability, can be surprisingly high even in the most developed countries of the world. The study of socio-economic inequalities, in relation to the utilisation of health services, is a priority for epidemiological research. Socio-economic status (SES) has no universal definition. Within the international research literature, SES has been related to social class, social position, occupational status, educational attainment, income, wealth and standard of living. Existing research studies have shown that people from a more deprived social background, with a lower SES, are more likely to have a higher psychiatric morbidity. Many studies show that SES influences psychiatric services utilization, however the real factors linking SES and mental health services utilisation remain unclear. In this editorial we discuss what is currently known about the relationship between SES and the use of mental health services. We also make an argument for why we believe there is still much to uncover in this field, to understand fully how individuals are influenced by their personal socio-economic status, or the neighbourhood in which they live, in terms of their use of mental health services. Further research in this area will help clarify what interventions are required to provide greater equality in access to mental health services.
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.
Mortality among psychiatric patients has been found to be higher than the general population, not only in those long-term residents in old-fashioned psychiatric hospitals or attending hospital-based psychiatric services (Harris & Barraclough, 1998) but also in those treated in modern community-based systems of care (Amaddeo et al., 1995; Grigoletti et al., 2009).
The use of information systems and computer science applications in the health sector is now entrenched and widespread. In mental health services there are the typical applications of information systems concerning administrative, clinical and research issues, as well as innovative applications concerning diagnostic procedures, self-help, communication and delivery of psychotherapy.
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.
Background. Cost evaluation research in the mental health field is being increasingly recognized as a way to achieve a more effective deployment of scarce resources. However, there is a paucity of studies that seek to identify predictors of psychiatric service utilization and costs. This paper aims to critically review the published research in the field of psychiatric service utilization and costs, and discusses current methodological developments in this field.
Method. Sixteen studies were identified and are critically reviewed.
Results. No single variable alone can explain variations in costs between patients; instead, a range of different clinical and non-clinical variables provides a greater explanation of cost variations. Having a history of previous psychiatric service use is the most consistent predictor of higher psychiatric costs. Only one study considers indirect costs incurred by users, their families and friends and society as a whole, with the remaining 15 studies focusing on direct mental health care costs. There is a lack of studies that consider the future psychiatric service utilization and costs of care of children and older people. The cross-validation of predictive models is not yet routine, with only four of the studies including a cross-validation procedure.
Conclusions. The predictive approach in mental health cost evaluation has relevance for both mental health policy and practice. However, there is a paucity of studies that focus on children, older people and indirect costs. Furthermore, there remain a number of methodological challenges to address.
Analysis of the patterns of variation in health care costs and the determinants of these costs (including treatment differences) is an increasingly important aspect of research into the performance of mental health services.
To encourage both investigators of the variation in health care costs and the consumers of their investigations to think more critically about the precise aims of these investigations and the choice of statistical methods appropriate to achieve them.
We briefly describe examples of regression models that might be of use in the prediction of mental health costs and how one might choose which one to use for a particular research project.
If the investigators are primarily interested in explanatory mechanisms then they should seriously consider generalised linear models (but with careful attention being paid to the appropriate error distribution). Further insight is likely to be gained through the use of two-part models. For prediction we recommend regression on raw costs using ordinary least-square methods. Whatever method is used, investigators should consider how robust their methods might be to incorrect distributional assumptions (particularly in small samples) and they should not automatically assume that methods such as bootstrapping will allow them to ignore these problems.
Few studies have investigated factors which predict inappropriate terminations (drop-out) of clinical contact with mental health services.
To identify patient and treatment characteristics associated with dropping out of contact with community-based psychiatric services (CPS).
A 3-month cohort of patients attending the CPS was followed up for 2 years, to identify drop-outs.
We identified 495 patients who had had at least one psychiatric contact of whom 261 had complete ratings for the Global Assessment of Functioning and the Verona Service Satisfaction Scale. In the year after the index contact, 70 terminated contact with the CPS; of these, 44 were rated as having inappropriate terminations (the ‘drop-out’ group) and 26 had appropriate terminations of contact. Drop-outs were younger, less likely to be married and their previous length of contact with services was shorter. No drop-outs had a diagnosis of schizophrenia. Multivariate analysis revealed predictors of dropping out.
In a CPS targeted to patients with severe mental illnesses, those who drop out of care are younger patients without psychoses who are generally satisfied with their treatment.
Psychiatric case registers are systematic health information systems of a geographically delimited area that record the contacts with designated medical and social services of patients or clients from the area. The information is stored in a linked and cumulative file so that the care of any individual or group can be followed over time, no matter how complex the pattern of service attendance (Wing, 1989). They represent the evolution of older systems for recording data of clinical relevance, such as disease registers to which hospitals and physicians used to report all cases of a certain diagnosis and hospital-based registers, which in general are based on aggregate data concerning patients who received care by a particular hospital or clinic (Häfner & an der Heiden, 1986).
Bennett & Trute (1983) pointed out that the term “information” has substantially wider connotations than the term “data”. In order to become “information”, data have to be placed within a framework and interpreted. This is true for all medical information systems, including those that collect limited data set, such as those about births, deaths, admissions to hospital, etc. (Wing, 1986).
A WHO Working Group held in Mannheim provided an agreed definition of a Psychiatric Case Register (PCR) which resulted in the following: “a Psychiatric Case Register is a patient-centered longitudinal record of contacts with a defined set of psychiatric services, originating from a defined population” (WHO, 1983).