Temporal Patterns of Ectopic Pregnancy: Using the Electronic Health Record to Illuminate a Dark Corner in Women's Health

Ectopic pregnancy remains a significant contributor to pregnancy-related morbidity and mortality, yet little is known about whether its occurrence follows discernible temporal patters that could inform prediction and prevention efforts. This dissertation aimed to explore the temporal characteristics of ectopic pregnancy through three interrelated projects: development of a new theoretical framework, a scoping review of the literature on ectopic pregnancy temporal patterns, and an empirical study using electronic health records data from a ten-year period at a single academic medical center. The Nursing Genomic and epigenomic, Environment, and Microbiome (N-GEM) situation-specific theoretical framework was introduced as a novel nursing theory that positions ectopic pregnancy within dynamic, interacting systems shaped by time-sensitive biological and environmental factors. Building on this theoretical foundation, a scoping review revealed that the existing research on ectopic pregnancy seasonality is highly heterogeneous, methodologically inconsistent, and often limited by exclusionary data sources. This study leveraged electronic health record data to create a comprehensive pregnancy dataset that included non-live birth outcomes, enabling a more inclusive and temporally accurate analysis of ectopic pregnancy incidence. Although no statistically significant monthly trends in ectopic pregnancy were identified, the findings suggest that calendar month-based models may be insufficient for capturing the complexity of ectopic pregnancy risk. This work advances nursing science by integrating theory development, evidence synthesis, and informatics-based methods to better understand the temporal dimensions of reproductive health and paves the way for future interdisciplinary research into ectopic pregnancy etiology, prediction, and prevention.