[Declared maternal death and the linkage between health information systems]
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Updated: Jul 16, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Maria Helena de Sousa1, José Guilherme Cecatti, Ellen Elizabeth Hardy
1Departamento de Tocoginecologia, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Rua Alexander Fleming 101, 13083-881 Campinas, SP, Brasil.
Objective:
To describe the characteristics of maternal mortality according to the Mortality Information System in relation to the data corresponding to these records that are in other systems.
Methods:
This was a descriptive study using two information systems on vital data and another on the hospital system, for the 26 state capitals and the Federal District of Brazil, in 2002. Initially, the maternal mortality ratios were calculated and information on declared maternal deaths were obtained. From these data, the Mortality Information System was probabilistically linked with the Live Birth Information System and the Hospital Information System, using the "Reclink II" software, with a multiple-step blocking strategy. For paired records, the diagnoses and hospital procedures brought together by the best-known criteria for severe maternal morbidity were detailed.
Results:
A total of 339 maternal deaths were recorded in 2002. The official and adjusted maternal mortality ratios were, respectively, 46.4 and 64.9 (deaths per 100,000 live births). By correlating with data from the live birth system, 46.5% of the maternal deaths could be located; and from the hospital information, 55.2%. The most frequent admission diagnosis was infection (13.9%) and the most frequent procedure was intensive care unit admission (39.0%).
Conclusions:
There were low percentage linkages between the records from the three sources studied. However, the possible failures and/or impossibilities in the linkages indicated may separately or jointly explain these low percentages.
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