Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance
<p>Abstract</p> <p>Background</p> <p>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 a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2008-10-01
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| Series: | Reproductive Health |
| Online Access: | http://www.reproductive-health-journal.com/content/5/1/6 |
| _version_ | 1818756787939049472 |
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| author | Hardy Ellen E Cecatti Jose G Sousa Maria H Serruya Suzanne J |
| author_facet | Hardy Ellen E Cecatti Jose G Sousa Maria H Serruya Suzanne J |
| author_sort | Hardy Ellen E |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> |
| first_indexed | 2024-12-18T06:00:36Z |
| format | Article |
| id | doaj.art-c4ef1b9660dc44d88247431cd5284f7d |
| institution | Directory Open Access Journal |
| issn | 1742-4755 |
| language | English |
| last_indexed | 2024-12-18T06:00:36Z |
| publishDate | 2008-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Reproductive Health |
| spelling | doaj.art-c4ef1b9660dc44d88247431cd5284f7d2022-12-21T21:18:42ZengBMCReproductive Health1742-47552008-10-0151610.1186/1742-4755-5-6Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillanceHardy Ellen ECecatti Jose GSousa Maria HSerruya Suzanne J<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p>http://www.reproductive-health-journal.com/content/5/1/6 |
| spellingShingle | Hardy Ellen E Cecatti Jose G Sousa Maria H Serruya Suzanne J Severe maternal morbidity (near miss) as a sentinel event of maternal death. An attempt to use routine data for surveillance Reproductive Health |
| 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 |
| url | http://www.reproductive-health-journal.com/content/5/1/6 |
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