Document Type

Dissertation

Degree

Doctor of Nursing Practice

Major

Nursing

Date of Defense

7-11-2019

Graduate Advisor

Susan Dean-Baar, PhD, RN, CENP, FAAN

Committee

Melissa Ehmke, DNP, RN, CLC

Elizabeth Dykeman, MSN, RN

Abstract

Problem: This quality improvement project aimed to improve the knowledge and confidence of the mother/baby nursing staff during postpartum hemorrhages through in situ simulation. PPH is a leading cause of maternal death. Hospitals across the U.S. lack a standard approach to managing obstetric emergencies; the complications of childbirth are often identified too late. Multidisciplinary simulation-based team training has been associated with improved outcomes in obstetrics.

Methods: A convenience sample of 26 registered nurses (RNs) that care for postpartum patients attended a one-hour instructor-led presentation followed by in situ simulations of postpartum hemorrhage. A knowledge assessment and confidence survey were administered pre-intervention and post-intervention. The pre-intervention and post-intervention scores were compared to determine knowledge and confidence gained following didactic and simulation exercises. A team of three observers rated each simulation exercise using the TeamSTEPPS Modified Team Performance Observation Tool (TPOT).

Results: The overall mean scores for the post-intervention confidence survey and knowledge assessment were statistically significantly higher than the mean scores for the pre-intervention confidence survey and knowledge assessment thus indicating overall improvement in participants’ knowledge gained and retained regarding a postpartum hemorrhage and improved confidence with their approach to managing a postpartum hemorrhage following didactic education and simulation exercises. Five of the seven simulation exercises had mean observer TPOT ratings greater than 4.0 (on a 5-point scale).

Implications for Practice: The ultimate goal is to expand the multidisciplinary team’s competence and confidence with all obstetric emergencies through simulation to improve maternal outcomes.

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