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Semin Perinatol. 2017 Apr;41(3):161-165. doi: 10.1053/j.semperi.2017.03.005. Epub 2017 Apr 14.

Maternal early warning systems-Towards reducing preventable maternal mortality and severe maternal morbidity through improved clinical surveillance and responsiveness.

Author information

1
Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, P.O. Box 208063, New Haven, CT 06520.
2
Division of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, P.O. Box 208063, New Haven, CT 06520. Electronic address: heather.lipkind@yale.edu.

Abstract

Despite increasing awareness of obstetric safety initiatives, maternal mortality and severe maternal morbidity in the United States have continued to increase over the past 20 years. Since results from large-scale surveillance programs suggest that up to 50% of maternal deaths may be preventable, new efforts are focused on developing and testing early warning systems for the obstetric population. Early warning systems are a set of specific clinical signs or symptoms that trigger the awareness of risk and an urgent patient evaluation, with the goal of reducing severe morbidity and mortality through timely diagnosis and treatment. Early warning systems have proven effective at predicting and reducing mortality and severe morbidity in medical, surgical, and critical care patient populations; however, there has been limited research on how to adapt these tools for use in the obstetric population, where physiologic changes of pregnancy render them inadequate. In this article, we review the available obstetric early warning systems and present evidence for their use in reducing maternal mortality and severe maternal morbidity. We also discuss considerations and strategies for implementation and acceptance of these early warning systems for clinical use in obstetrics.

KEYWORDS:

critical vital signs; early warning systems; maternal mortality; patient safety

PMID:
28416176
DOI:
10.1053/j.semperi.2017.03.005
[Indexed for MEDLINE]

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