Cost-effectiveness of early intervention in psychosis in low- and middle-income countries: economic evaluation from São Paulo, Brazil.

AIMS: The effectiveness and cost-effectiveness of early intervention for psychosis (EIP) services are well established in high-income countries but not in low- and middle-income countries (LMICs). Despite the scarcity of local evidence, several EIP services have been implemented in LMICs. Local evaluations are warranted before adopting speciality models of care in LMICs. We aimed to estimate the cost-effectiveness of implementing EIP services in Brazil. METHODS: A model-based economic evaluation of EIP services was conducted from the Brazilian healthcare system perspective. A Markov model was developed using a cohort study conducted in São Paulo. Cost data were retrieved from local sources. The outcome of interest was the incremental cost-effectiveness ratio (ICER) measured as the incremental costs over the incremental quality-adjusted life-years (QALYs). Sensitivity analyses were performed to test the robustness of the results. RESULTS: The study included 357 participants (38% female), with a mean (SD) age of 26 (7.38) years. According to the model, implementing EIP services in Brazil would result in a mean incremental cost of 4,478 Brazilian reals (R$) and a mean incremental benefit of 0.29 QALYs. The resulting ICER of R$ 15,495 (US dollar [USD] 7,640 adjusted for purchase power parity [PPP]) per QALY can be considered cost-effective at a willingness-to-pay threshold of 1 Gross domestic product (GDP) per capita (R$ 18,254; USD 9,000 PPP adjusted). The model results were robust to sensitivity analyses. CONCLUSIONS: This study supports the economic advantages of implementing EIP services in Brazil. Although cultural adaptations are required, these data suggest EIP services might be cost-effective even in less-resourced countries.

Patient needs four years after first psychiatric hospitalization in a Brazilian cohort.

Knowledge about the needs of psychiatric patients is essential for mental health care planning. However, research on met and unmet needs is still scarce, particularly in low- and middle-income countries. This study aimed to describe the patients' needs (met and unmet) at least four years after their first psychiatric hospitalization and to verify the role of demographic and clinical features as possible predictors of these needs. Patients who had their first psychiatric admission between January 1, 2006 and December 31, 2007 at an inpatient unit in the city of Ribeirão Preto, Brazil, were eligible to participate in the study. Patients were contacted and face-to-face interviews were conducted by psychologists using the Camberwell Assessment of Need. Data were analyzed using zero-inflated negative binomial regression model. Of 933 eligible patients, 333 were interviewed. The highest level of needs was related to welfare benefits (32.4%, unmet=25.5%), followed by household skills (30.3%, unmet=3.0%), psychotic symptoms (29.4%, unmet=9.0%), psychological distress (27.6%, unmet=8.4%), physical health (24.3%, unmet=5.4%), daytime activities (19.5%, unmet=16.5%), and money (16.8%, unmet=9.0%). Fewer years of schooling, living with relatives, and unemployment at the moment of the first admission were significantly associated with a higher number of both met and unmet needs in the follow-up. Unmet needs were also more often reported by patients living alone. In conclusion, socioeconomic indicators were the best predictors of needs. The unmet needs related to welfare benefits point to the need for specific social and health policies.

Patient needs four years after first psychiatric hospitalization in a Brazilian cohort

Knowledge about the needs of psychiatric patients is essential for mental health care planning. However, research on met and unmet needs is still scarce, particularly in low- and middle-income countries. This study aimed to describe the patients' needs (met and unmet) at least four years after their first psychiatric hospitalization and to verify the role of demographic and clinical features as possible predictors of these needs. Patients who had their first psychiatric admission between January 1, 2006 and December 31, 2007 at an inpatient unit in the city of Ribeirão Preto, Brazil, were eligible to participate in the study. Patients were contacted and face-to-face interviews were conducted by psychologists using the Camberwell Assessment of Need. Data were analyzed using zero-inflated negative binomial regression model. Of 933 eligible patients, 333 were interviewed. The highest level of needs was related to welfare benefits (32.4%, unmet=25.5%), followed by household skills (30.3%, unmet=3.0%), psychotic symptoms (29.4%, unmet=9.0%), psychological distress (27.6%, unmet=8.4%), physical health (24.3%, unmet=5.4%), daytime activities (19.5%, unmet=16.5%), and money (16.8%, unmet=9.0%). Fewer years of schooling, living with relatives, and unemployment at the moment of the first admission were significantly associated with a higher number of both met and unmet needs in the follow-up. Unmet needs were also more often reported by patients living alone. In conclusion, socioeconomic indicators were the best predictors of needs. The unmet needs related to welfare benefits point to the need for specific social and health policies.

The 5/95 gap in the indexation of psychiatric journals of low- and middle-income countries.

OBJECTIVE: To investigate the relationship between science production and the indexation level of low- and middle-income countries (LAMIC) journals in international databases. METHOD: Indicators of productivity in research were based on the number of articles produced over the 1994-2004 period. A survey in both Medline and ISI/Thomson was conducted to identify journals according to their country of origin. A WPA Task Force designed a collaborative process to assess distribution and quality of non-indexed LAMIC journals. RESULTS: Twenty LAMIC were found to present more than 100 publications and a total of 222 indexed psychiatric journals were found, but only nine were from LAMIC. The Task Force received 26 questionnaires from editors of non-indexed journals, and concluded that five journals would meet criteria for indexation. CONCLUSION: Barriers to indexation of journals contribute to the difficulties in achieving fair representation in the main literature databases for the scientific production in these countries.

Challenges to reduce the '10/90 gap': mental health research in Latin American and Caribbean countries.

OBJECTIVE: To analyze the status of mental health research in 30 Latin American and Caribbean countries (LAC). METHOD: Medline and PsycInfo databases were searched to identify the LAC authors. Their publications were classified according to the topic, type of research and target population studied. Scientific indicators of these countries were assessed in other two different databases: Essential Scientific Information and Atlas of Science Project, both from Institute for Scientific Information. RESULTS: Indexed-publications were concentrated in six countries: Argentina, Brazil, Chile, Colombia, Mexico and Venezuela. Most studies dealt with the burdensome mental disorders but neglected important topics such as violence and other mental health priorities. CONCLUSION: Mental health research is mostly concentrated in a few LAC countries, but these countries would contribute to reduce the research gap, if they provide research training to their neighbors and engage in bi- or multi-lateral research collaboration on common region priorities.

The scientific production in health and biological sciences of the top 20 Brazilian universities.

Brazilian scientific output exhibited a 4-fold increase in the last two decades because of the stability of the investment in research and development activities and of changes in the policies of the main funding agencies. Most of this production is concentrated in public universities and research institutes located in the richest part of the country. Among all areas of knowledge, the most productive are Health and Biological Sciences. During the 1998-2002 period these areas presented heterogeneous growth ranging from 4.5% (Pharmacology) to 191% (Psychiatry), with a median growth rate of 47.2%. In order to identify and rank the 20 most prolific institutions in these areas, searches were made in three databases (DataCAPES, ISI and MEDLINE) which permitted the identification of 109,507 original articles produced by the 592 Graduate Programs in Health and Biological Sciences offered by 118 public universities and research institutes. The 20 most productive centers, ranked according to the total number of ISI-indexed articles published during the 1998-2003 period, produced 78.7% of the papers in these areas and are strongly concentrated in the Southern part of the country, mainly in São Paulo State.

The scientific production in health and biological sciences of the top 20 Brazilian universities

Brazilian scientific output exhibited a 4-fold increase in the last two decades because of the stability of the investment in research and development activities and of changes in the policies of the main funding agencies. Most of this production is concentrated in public universities and research institutes located in the richest part of the country. Among all areas of knowledge, the most productive are Health and Biological Sciences. During the 1998-2002 period these areas presented heterogeneous growth ranging from 4.5 percent (Pharmacology) to 191 percent (Psychiatry), with a median growth rate of 47.2 percent. In order to identify and rank the 20 most prolific institutions in these areas, searches were made in three databases (DataCAPES, ISI and MEDLINE) which permitted the identification of 109,507 original articles produced by the 592 Graduate Programs in Health and Biological Sciences offered by 118 public universities and research institutes. The 20 most productive centers, ranked according to the total number of ISI-indexed articles published during the 1998-2003 period, produced 78.7 percent of the papers in these areas and are strongly concentrated in the Southern part of the country, mainly in São Paulo State.

Decision support system for the diagnosis of schizophrenia disorders.

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

Comorbidity and global functioning (DSM-III-R Axis V) in a Brazilian sample of cocaine users.

We assessed the mental disorders rate in treatment-seeking, nonintravenous cocaine users in a Brazilian outpatient clinic, and evaluated how comorbidity affects global functioning. Fifty male nonintraveneous cocaine users from an outpatient clinic were interviewed with semistructured instruments based on DSM-III-R criteria. All subjects met the DSM-III-R criteria for "cocaine abuse" or "dependence" during the last 6 months. The lifetime Axis I or Axis II disorders rate was 69%, with a higher prevalence of anxiety disorders (31%) and depressive disorders (20%). By using a multivariate analysis, the number of personality disorders, the number of psychiatric diagnoses, and the presence of depressive and anxiety disorders were found as significant factors associated with poor global functioning among nonintraveneous cocaine addicts.