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Scoping Review on the Use of Early Warning Trigger Tools for Women in Labor
Objective:
To identify existing obstetric trigger tools, evaluate their sensitivity and specificity to correctly identify women in need of care escalation, and describe clinicians' experiences of using these tools while caring for women in labor.
Data Sources:
Iterative searches of three databases, CINAHL, PubMed, and SCOPUS, in October 2019 and June 2020 using the keywords maternal surveillance system, obstetric∗, early warning scores, early warning systems, and trigger tools.
Study Selection:
Primary quantitative and qualitative studies on the utility or implementation of trigger tools for women in labor that were written in English. Through the initial search, I identified 208 articles and included 11 full-text articles in this review.
Data Extraction:
I extracted data related to aims, population, methodology, outcomes, and key findings for each study and entered them into a matrix based on the Joanna Briggs Institute Review Guidelines.
Data Synthesis:
Quantitative researchers found that the sensitivity and specificity to correctly identify women in need of care escalation of tools varied and recommended that institutions should consider the burdens of false positives versus the risks of false negatives when choosing a tool for their contexts. Qualitative researchers described clinicians' experiences with the use of trigger tools and systems-level barriers to implementation, including lack of training, poor management of implementation, increased workload due to redundant charting, and belief that tools were not appropriate for women with low-risk pregnancies. Greater rates of false positives led clinicians to use trigger tools only for women with high-risk pregnancies rather than as a screening tool for all women.
Conclusion:
Trigger tools may help with early identification of worsening clinical condition, but further research is needed to refine and improve tools, as well as understand best practices for tool implementation. Systems-level factors should be considered in tool selection.

