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Defining a conceptual framework for near-miss maternal morbidity
Maternal mortality is the major indicator used to monitor maternal health in the United States. For every woman who dies, however, many suffer serious life-threatening complications of pregnancy. Yet relatively little attention has been given to identifying a general category of morbidities that could be called near misses. Characterizing near-miss morbidity is valuable for monitoring the quality of hospital-based obstetric care and for assessing the incidence of life-threatening complications. Cases of near-miss morbidity also provide an appropriate comparison group both for dinical case review and for epidemiologic analysis. This paper presents an initial framework and a process for the definition and identification of near-miss morbidity that minimizes loss of information yet has practical utility. A clinical review team classified 22 of 186 women as near misses and 164 as other severe morbidity. A quantitative score classified 28 women as near misses and 156 as other severe morbidity. Precise classification of near-miss morbidity is the first step in analyzing factors that may differentiate survival from death on the continuum from morbidity to mortality. Ultimately, a methodology for the identification and analysis of near-miss morbidity will allow for integrated morbidity and mortality reviews that can then be institutionalized. The results will serve as important models for other researchers, state health agencies, and regionalized perinatal systems that are engaged in morbidity and mortality surveillance.
Maternal mortality is the major indicator used to monitor maternal health in the United States. For every woman who dies, however, many suffer serious life-threatening complications of pregnancy. Yet relatively little attention has been given to identifying a general category of morbidities that could be called near misses. Characterizing near-miss morbidity is valuable for monitoring the quality of hospital-based obstetric care and for assessing the incidence of life-threatening complications. Cases of near-miss morbidity also provide an appropriate comparison group both for dinical case review and for epidemiologic analysis. This paper presents an initial framework and a process for the definition and identification of near-miss morbidity that minimizes loss of information yet has practical utility. A clinical review team classified 22 of 186 women as near misses and 164 as other severe morbidity. A quantitative score classified 28 women as near misses and 156 as other severe morbidity. Precise classification of near-miss morbidity is the first step in analyzing factors that may differentiate survival from death on the continuum from morbidity to mortality. Ultimately, a methodology for the identification and analysis of near-miss morbidity will allow for integrated morbidity and mortality reviews that can then be institutionalized. The results will serve as important models for other researchers, state health agencies, and regionalized perinatal systems that are engaged in morbidity and mortality surveillance.
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