Validation of physician certified verbal autopsy using conventional autopsy: a large study of adult non-external causes of death in a metropolitan area in Brazil.

BACKGROUND: Reliable mortality data are essential for the development of public health policies. In Brazil, although there is a well-consolidated universal system for mortality data, the quality of information on causes of death (CoD) is not even among Brazilian regions, with a high proportion of ill-defined CoD. Verbal autopsy (VA) is an alternative to improve mortality data. This study aimed to evaluate the performance of an adapted and reduced version of VA in identifying the underlying causes of non-forensic deaths, in São Paulo, Brazil. This is the first time that a version of the questionnaire has been validated considering the autopsy as the gold standard. METHODS: The performance of a physician-certified verbal autopsy (PCVA) was evaluated considering conventional autopsy (macroscopy plus microscopy) as gold standard, based on a sample of 2060 decedents that were sent to the Post-Mortem Verification Service (SVOC-USP). All CoD, from the underlying to the immediate, were listed by both parties, and ICD-10 attributed by a senior coder. For each cause, sensitivity and chance corrected concordance (CCC) were computed considering first the underlying causes attributed by the pathologist and PCVA, and then any CoD listed in the death certificate given by PCVA. Cause specific mortality fraction accuracy (CSMF-accuracy) and chance corrected CSMF-accuracy were computed to evaluate the PCVA performance at the populational level. RESULTS: There was substantial variability of the sensitivities and CCC across the causes. Well-known chronic diseases with accurate diagnoses that had been informed by physicians to family members, such as various cancers, had sensitivities above 40% or 50%. However, PCVA was not effective in attributing Pneumonia, Cardiomyopathy and Leukemia/Lymphoma as underlying CoD. At populational level, the PCVA estimated cause specific mortality fractions (CSMF) may be considered close to the fractions pointed by the gold standard. The CSMF-accuracy was 0.81 and the chance corrected CSMF-accuracy was 0.49. CONCLUSIONS: The PCVA was efficient in attributing some causes individually and proved effective in estimating the CSMF, which indicates that the method is useful to establish public health priorities.

Accuracy of a probabilistic record-linkage methodology used to track blood donors in the Mortality Information System database.

The probabilistic record linkage (PRL) is based on a likelihood score that measures the degree of similarity of several matching variables. Screening test results for different diseases are available for the blood donor population. In this paper, we describe the accuracy of a PRL process used to track blood donors from the Fundação Pró-Sangue (FPS) in the Mortality Information System (SIM), in order that future studies might determine the blood donor's cause of death. The databases used for linkage were SIM and the database made up of individuals that were living (200 blood donors in 2007) and dead (196 from the Hospital das Clinicas de São Paulo that died in 2001-2005). The method consists of cleaning and linking the databases using three blocking steps comparing the variables "Name/Mother's Name/ Date of Birth" to determine a cut-off score. For a cut-off score of 7.06, the sensitivity and specificity of the method is 94.4% (95%CI: 90.0-97.0) and 100% (95%CI: 98.0-100.0), respectively. This method can be used in studies that aim to track blood donors from the FPS database in SIM.

Accuracy of a probabilistic record-linkage methodology used to track blood donors in the Mortality Information System database / Acurácia da metodologia de relacionamento probabilístico de registros na identificação de doadores de sangue no banco de dados do Sistema de Informações sobre Mortalidade / La exactitud del método probabilístico de relación para identificar a donantes de sangre en la base de datos del Sistema de Información sobre Mortalidad

The probabilistic record linkage (PRL) is based on a likelihood score that measures the degree of similarity of several matching variables. Screening test results for different diseases are available for the blood donor population. In this paper, we describe the accuracy of a PRL process used to track blood donors from the Fundação Pró-Sangue (FPS) in the Mortality Information System (SIM), in order that future studies might determine the blood donor’s cause of death. The databases used for linkage were SIM and the database made up of individuals that were living (200 blood donors in 2007) and dead (196 from the Hospital das Clinicas de São Paulo that died in 2001-2005). The method consists of cleaning and linking the databases using three blocking steps comparing the variables “Name/Mother’s Name/ Date of Birth” to determine a cut-off score. For a cut-off score of 7.06, the sensitivity and specificity of the method is 94.4% (95%CI: 90.0-97.0) and 100% (95%CI: 98.0-100.0), respectively. This method can be used in studies that aim to track blood donors from the FPS database in SIM.

O relacionamento probabilístico se baseia em um escore que é calculado levando em consideração a similaridade do pareamento de diversas variáveis. Dados de resultados de testes de triagem para diferentes doenças estão disponíveis para a população de doadores de sangue. Neste artigo descrevemos a acurácia de um processo de relacionamento probabilístico para identificar doadores de sangue da Fundação Pró-Sangue (FPS) no Sistema de Informações sobre Mortalidade (SIM). Os bancos utilizados para o relacionamento foram o SIM e o banco formado por indivíduos vivos (200 doadores de sangue em 2007) e mortos (196 pacientes do Hospital das Clínicas de São Paulo que morreram entre 2001-2005). O método consistiu em limpar e relacionar probabilísticamente os bancos em três passos de blocagem comparando as variáveis “Nome/Nome Mãe /Data de Nascimento” para determinar um escore de corte. Para um escore de corte de 7,06 a sensibilidade e especificidade do método é de 94,4% (IC95%: 90-97) e 100% (IC95%: 98-100), respectivamente. Este método pode ser utilizado em estudos para identificar pacientes da FPS no SIM.

La relación probabilística (RP) se basa en una puntuación que se calcula en función de la similitud entre variables de emparejamiento. Los resultados de los tests sobre diferentes enfermedades están a disposición de la población de donantes de sangre. En el presente artículo se describe la precisión de un proceso de RP para identificar a donantes de sangre de la Fundação Pró-Sangue (FPS) en el Sistema de Información de Mortalidad (SIM). Se llevó a cabo la RP del SIM y de un banco compuesto por individuos vivos (200 donantes de sangre en 2007) y muertos (196 pacientes del Hospital de Clínicas de São Paulo, que murieron entre 2001 y 2005). El método consistió en depurar los bancos de datos y RP en tres etapas de bloqueo, comparando las variables nombre, nombre de la madre y fecha de nacimiento para determinar un punto de corte. Para el punto de corte 7:06, la especificidad y sensibilidad del método fue de un 94,4% (IC95%: 90,0-97,0) y 100% (IC95%: 98,0-100,0), respectivamente. Este método puede ser utilizado en más estudios con el fin de identificar a los pacientes FPS en el SIM.