Translating Maternal Mortality Review Into Quality Improvement Opportunities in Response to Pregnancy-Related Deaths in California
2019
Abstract Objective To describe quality improvement opportunities (QIOs) associated with the five leading causes of pregnancy-related death in California and the methods by which the QIOs were collected by the California Pregnancy-Associated Mortality Review committee. Design Qualitative, descriptive design using thematic analysis. Sample A total of 907 QIOs identified from 203 cases of pregnancy-related deaths from cardiovascular disease, preeclampsia/eclampsia, hemorrhage, venous thromboembolism, and sepsis that occurred in California from 2002 to 2007. Methods We coded and thematically organized QIO data using three of the four domains commonly applied in quality improvement initiatives for maternal health care: Readiness , Recognition , and Response . Data did not include reporting issues, so the Reporting domain was excluded from the analysis. We refer to the domains collectively as the 4R Framework. Results We identified key themes across the five leading causes of death. In the Readiness domain, themes were related to overall facility readiness and helping women be prepared and knowledgeable about pregnancy and childbirth. Themes that emerged as central in the Recognition domain addressed the need for clinicians to better recognize risk factors and women's signs and symptoms to ensure an accurate diagnosis. In the Response domain, three themes were predominant, and they were related to the coordination of care, timing of treatment, and follow-up care. Conclusion Results from our study show the utility and transferability of the first three domains of the 4R Framework as applied to quality improvement data from a large statewide maternal mortality review. Nursing leadership is necessary to support and guide national, statewide, and local efforts to improve the quality of maternity care through the implementation of quality improvement at the system, facility, clinician, and patient levels.
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