Analysis of the completeness of self-harm and suicide records in Pernambuco, Brazil, 2014-2016.

INTRODUCTION: Suicides and suicide attempts are major public health problems, and coping strategies are hampered by insufficient or inadequate notifications. Data accuracy influences the formulation of public and mental health policies and suicide prevention strategies. The objective of this study was to analyze the completeness of self-harm and suicide records in the state of Pernambuco, Brazil, 2014-2016. METHODS: This is an evaluative study with a descriptive design. The data were collected from suicide attempt records from the Notifiable Diseases Information System and suicide records from the Mortality Information System. Probabilistic linkage was used to relate these databases, and the degree of completeness of the variables was calculated. Completeness was classified into the following categories: good (≥ 75.1%), regular (50.1%-75.0%), low (25.1%-50.0%), and very low (≤ 25.0%). RESULTS: In the analyzed period, 1,404 notifications of self-harm were studied, with an overall mean completeness of 86.2%. In addition, 1,050 suicide records were analyzed, with an overall mean completeness of 95.8%. Most variables referring to suicide attempts had good completeness, with the exception of the variables "occupation" and "education." The completeness of all suicide-related variables was rated as good. After linkage, a significant improvement was observed in the degree of completeness of the variable "occupation". CONCLUSION: The results of this study showed that the completeness of self-harm and suicide variables improved from the first to the last year. The integration of data from different information systems provides an opportunity to improve suicide prevention programs and the quality of available information. Continuous efforts to increase the completeness and reliability of suicide surveillance systems are fundamental to describe the epidemiological profile and, consequently, plan preventive actions, in addition to contributing to the development and reformulation of strategies aimed at reducing morbidity and mortality related to suicidal behavior.

Validation of SmartVA using conventional autopsy: A study of adult deaths in Brazil.

Background: Accurate cause of death data are essential to guide health policy. However, mortality surveillance is limited in many low-income countries. In such settings, verbal autopsy (VA) is increasingly used to provide population-level cause of death data. VAs are now widely interpreted using the automated algorithms SmartVA and InterVA. Here we use conventional autopsy as the gold standard to validate SmartVA methodology. Methods: This study included adult deaths from natural causes in São Paulo and Recife for which conventional autopsy was indicated. VA was conducted with a relative of the deceased using an amended version of the SmartVA instrument to suit the local context. Causes of death from VA were produced using the SmartVA-Analyze program. Physician coded verbal autopsy (PCVA), conducted on the same questionnaires, and Global Burden of Disease Study data were used as additional comparators. Cause of death data were grouped into 10 broad causes for the validation due to the real-world utility of VA lying in identifying broad population cause of death patterns. Findings: The study included 2,060 deaths in São Paulo and 1,079 in Recife. The cause specific mortality fractions (CSMFs) estimated using SmartVA were broadly similar to conventional autopsy for: cardiovascular diseases (46.8% vs 54.0%, respectively), cancers (10.6% vs 11.4%), infections (7.0% vs 10.4%) and chronic respiratory disease (4.1% vs 3.7%), causes accounting for 76.1% of the autopsy dataset. The SmartVA CSMF estimates were lower than autopsy for "Other NCDs" (7.8% vs 14.6%) and higher for diabetes (13.0% vs 6.6%). CSMF accuracy of SmartVA compared to autopsy was 84.5%. CSMF accuracy for PCVA was 93.0%. Interpretation: The results suggest that SmartVA can, with reasonable accuracy, predict the broad cause of death groups important to assess a population's epidemiological transition. VA remains a useful tool for understanding causes of death where medical certification is not possible.

[Infant mortality due to avoidable causes in a city in Northeastern Brazil]. / Mortalidade infantil por causas evitáveis em uma cidade do Nordeste do Brasil.

This is a cross-sectional study that aimed to describe the occurrence of infant mortality in Recife (PE) between 2000 and 2009, second to avoidable causes. The population composed of cases of deaths between 2000 and 2009 among the infants of mothers living in Recife. Deaths were classified as avoidable by using the List of avoidable causes of deaths resulting from interventions within the Brazilian National Health System (SUS). Descriptive statistics were used for data analysis. A decrease in the infant mortality coefficient from 20.4 to 12.1 per 1.000 live births was observed (reduction of 40.6%). From the total of 3.743 deaths registered, 2.861 (76.4%) were classified as avoidable. It was notable that 61.2% of the deaths could have been avoided through appropriate care for the woman during the pregnancy. An approach in which avoidability is analyzed may assist in discussions relating to organization, quality and access to healthcare service, and in identifying deaths that could have been avoided through appropriate mother-child healthcare.