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Use of linkage to improve the completeness of the SIM and SINASC in the Brazilian capitals

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posted on 2017-12-05, 09:37 authored by Lívia Teixeira de Souza Maia, Wayner Vieira de Souza, Antonio da Cruz Gouveia Mendes, Aline Galdino Soares da Silva

ABSTRACT OBJECTIVE To analyze the contribution of linkage between databases of live births and infant mortality to improve the completeness of the variables common to the Mortality Information System (SIM) and the Live Birth Information System (SINASC) in Brazilian capitals in 2012. METHODS We studied 9,001 deaths of children under one year registered in the SIM in 2012 and 1,424,691 live births present in the SINASC in 2011 and 2012. The databases were related with linkage in two steps – deterministic and probabilistic. We calculated the percentage of incompleteness of the variables common to the SIM and SINASC before and after using the technique. RESULTS We could relate 90.8% of the deaths to their respective declarations of live birth, most of them paired deterministically. We found a higher percentage of pairs in Porto Alegre, Curitiba, and Campo Grande. In the capitals of the North region, the average of pairs was 84.2%; in the South region, this result reached 97.9%. The 11 variables common to the SIM and SINASC had 11,278 incomplete fields cumulatively, and we could recover 91.4% of the data after linkage. Before linkage, five variables presented excellent completeness in the SINASC in all Brazilian capitals, but only one variable had the same status in the SIM. After applying this technique, all 11 variables of the SINASC became excellent, while this occurred in seven variables of the SIM. The city of birth was significantly associated with the death component in the quality of the information. CONCLUSIONS Despite advances in the coverage and quality of the SIM and SINASC, problems in the completeness of the variables can still be identified, especially in the SIM. In this perspective, linkage can be used to qualify important information for the analysis of infant mortality.

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