Literature DB >> 28416176

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

Lisa C Zuckerwise1, Heather S Lipkind2.   

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.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

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

Mesh:

Year:  2017        PMID: 28416176     DOI: 10.1053/j.semperi.2017.03.005

Source DB:  PubMed          Journal:  Semin Perinatol        ISSN: 0146-0005            Impact factor:   3.300


  6 in total

1.  Comparison of Natural Language Processing of Clinical Notes With a Validated Risk-Stratification Tool to Predict Severe Maternal Morbidity.

Authors:  Mark A Clapp; Ellen Kim; Kaitlyn E James; Roy H Perlis; Anjali J Kaimal; Thomas H McCoy; Sarah Rae Easter
Journal:  JAMA Netw Open       Date:  2022-10-03

2.  Preidentification of high-risk pregnancies to improve triaging at the time of admission and management of complications in labour room: a quality improvement initiative.

Authors:  Prabha Kumari; Mahtab Singh; Shailja Sinha; Rajeev Ranjan; Prachi Arora; Sunita Rani; Aparna Aggarwal; Kanika Aggarwal; Shefali Gupta
Journal:  BMJ Open Qual       Date:  2022-06

3.  High-risk pregnancies and their association with severe maternal morbidity in Nepal: A prospective cohort study.

Authors:  Sushma Rajbanshi; Mohd Noor Norhayati; Nik Hussain Nik Hazlina
Journal:  PLoS One       Date:  2020-12-28       Impact factor: 3.240

4.  Comparison of early warning scores for predicting clinical deterioration and infection in obstetric patients.

Authors:  David E Arnolds; Kyle A Carey; Lena Braginsky; Roxane Holt; Dana P Edelson; Barbara M Scavone; Matthew Churpek
Journal:  BMC Pregnancy Childbirth       Date:  2022-04-06       Impact factor: 3.007

5.  Impact of a standardised rapid response system on clinical outcomes of female patients: an interrupted time series approach.

Authors:  Jack Chen; Lixin Ou; Ken Hillman; Michael Parr; Arthas Flabouris; Malcolm Green
Journal:  BMJ Open Qual       Date:  2022-08

6.  Prevalence of Severe Maternal Morbidity and Factors Associated With Maternal Mortality in Ontario, Canada.

Authors:  Joel G Ray; Alison L Park; Susie Dzakpasu; Natalie Dayan; Paromita Deb-Rinker; Wei Luo; K S Joseph
Journal:  JAMA Netw Open       Date:  2018-11-02
  6 in total

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