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ZENODO
Project deliverable . 2021
License: CC BY
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Project deliverable . 2021
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Improving Nurse Management of the Second Stage of Labor

Authors: Dent, Mimi;

Improving Nurse Management of the Second Stage of Labor

Abstract

Background: There is global concern that cesarean sections (CS) are overused because of the rapid increase in CS rates without corresponding decreases in maternal or neonatal morbidity and mortality (Caughey et al., 2014). In 1996, national CS rates were 20.7%, peaking at 32% in 2015 (Caughey, 2017). The Healthy People 2020 goal of a 23.9% CS rate for nulliparous term singleton term (NTSV) women was identified as a national benchmark and primary strategy to safely decrease CS rates (Bell et al., 2017; Vadnais et al., 2017). Methodology: The Iowa Model Revised: Evidence-Based Practice to Promote Excellence in Health Care was the framework used. Guidelines to support second stage nursing management were created by integrating unit policies with research evidence. Eighteen registered nurses (RNs) attended an instructional course (IC), the intervention, to improve nurse management of second stage of labor. Results of pre- and post-knowledge tests and pre- and post-intervention labor variables were compared. Results: RN knowledge increased, evidenced by mean pre- and posttest scores of 6.17 and 9.06 respectively, t (17) = -6.43, p < .001. Second stage labor outcomes also improved with more position changes and percentages of normal spontaneous vaginal deliveries (NSVD). Eightyseven percent (n = 28/32) of patients cared for by IC RNs delivered by NSVD compared to 81.8% (n =18/22) cared for by non-IC RNs. Recommendations: Based on the positive response to the IC and improved clinical outcomes, regularly scheduled, interactive, evidence-based nursing education focused on strategies to improve second stage management should be provided. Keywords: birth, obstetric; labor, second stage; term birth

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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