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Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance

BACKGROUND: To identify all the records within the Brazilian Hospital Information System (HIS) that contained information suggestive of severe maternal morbidity (near miss); to describe the diagnoses and procedures used; to identify variables associated with maternal death. METHODS: A descriptive p...

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Autores principales: Sousa, Maria H, Cecatti, Jose G, Hardy, Ellen E, Serruya, Suzanne J
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2583985/
https://www.ncbi.nlm.nih.gov/pubmed/18957110
http://dx.doi.org/10.1186/1742-4755-5-6
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author Sousa, Maria H
Cecatti, Jose G
Hardy, Ellen E
Serruya, Suzanne J
author_facet Sousa, Maria H
Cecatti, Jose G
Hardy, Ellen E
Serruya, Suzanne J
author_sort Sousa, Maria H
collection PubMed
description BACKGROUND: To identify all the records within the Brazilian Hospital Information System (HIS) that contained information suggestive of severe maternal morbidity (near miss); to describe the diagnoses and procedures used; to identify variables associated with maternal death. METHODS: A descriptive population study with data from the HIS and Mortality Information System (MIS) files of records of women during pregnancy, delivery and in the postpartum period in all the capital cities of the Brazilian states in 2002. Initially, records of women between 10 and 49 years of age were selected; next, those records with at least one criterion suggestive of near miss were selected. For the linkage of HIS with MIS and HIS with itself, a blocking strategy consisting of three independent steps was established. In the data analysis, near miss ratios were calculated with corresponding 95% confidence interval and the diagnoses and procedures were described; a multiple logistic regression model was adjusted. Primary and secondary diagnoses and the requested and performed procedures during hospitalization were the main outcome measures. RESULTS: The overall maternal near miss ratio was 44.3/1,000 live births. Among the records indicating near miss, 154 maternal deaths were identified. The criteria of severity most frequently found were infection, preeclampsia and hemorrhage. Logistic regression analysis resulted in 12 variables, including four significant interactions. CONCLUSION: Although some limitations, the perspective of routinely using this information system for surveillance of near miss and implementing measures to avoid maternal death is promising.
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spelling pubmed-25839852008-11-18 Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance Sousa, Maria H Cecatti, Jose G Hardy, Ellen E Serruya, Suzanne J Reprod Health Research BACKGROUND: To identify all the records within the Brazilian Hospital Information System (HIS) that contained information suggestive of severe maternal morbidity (near miss); to describe the diagnoses and procedures used; to identify variables associated with maternal death. METHODS: A descriptive population study with data from the HIS and Mortality Information System (MIS) files of records of women during pregnancy, delivery and in the postpartum period in all the capital cities of the Brazilian states in 2002. Initially, records of women between 10 and 49 years of age were selected; next, those records with at least one criterion suggestive of near miss were selected. For the linkage of HIS with MIS and HIS with itself, a blocking strategy consisting of three independent steps was established. In the data analysis, near miss ratios were calculated with corresponding 95% confidence interval and the diagnoses and procedures were described; a multiple logistic regression model was adjusted. Primary and secondary diagnoses and the requested and performed procedures during hospitalization were the main outcome measures. RESULTS: The overall maternal near miss ratio was 44.3/1,000 live births. Among the records indicating near miss, 154 maternal deaths were identified. The criteria of severity most frequently found were infection, preeclampsia and hemorrhage. Logistic regression analysis resulted in 12 variables, including four significant interactions. CONCLUSION: Although some limitations, the perspective of routinely using this information system for surveillance of near miss and implementing measures to avoid maternal death is promising. BioMed Central 2008-10-28 /pmc/articles/PMC2583985/ /pubmed/18957110 http://dx.doi.org/10.1186/1742-4755-5-6 Text en Copyright © 2008 Sousa et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Sousa, Maria H
Cecatti, Jose G
Hardy, Ellen E
Serruya, Suzanne J
Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
title Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
title_full Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
title_fullStr Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
title_full_unstemmed Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
title_short Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
title_sort severe maternal morbidity (near miss) as a sentinel event of maternal death. an attempt to use routine data for surveillance
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2583985/
https://www.ncbi.nlm.nih.gov/pubmed/18957110
http://dx.doi.org/10.1186/1742-4755-5-6
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