Critical Care Obstetrics and Gynecology

Recent Trends in Severe Maternal Morbidity (SMM) UPMC Harrisburg PA, 2016-2020

Objectives: This study describes the current burden, trends and identifies the leading causes of Severe Maternal Morbidity (SMM) at UPMC Harrisburg Hospital. Additionally, the study provides recommendations for high priority, system-wide areas of improvement to advance the provision of maternal care.  

Methods: This retrospective, population-based study analyzed SMM indicators as delineated by CDC guidelines and identified corresponding obstetric diagnosis and procedure codes from electronic medical records. The study population includes women with pregnancy and/or delivery-related hospitalizations within 42 days after delivery. The data was categorized by SMM indicator, maternal age, race/ethnicity, delivery mode, BMI, and transfusion.

Results: From October 2016 to October 2020, 479 patients experienced at least one SMM indicator. Blood transfusions were the most common (80%), followed by sepsis (3%), and HELLP and/or eclampsia (3%). There was a statistically significant difference in average maternal age between SMM patients with and without transfusions (28.7 vs. 30.8, p=0.0073). The study suggests that a higher BMI (≥30) is associated to 50% of the non-transfusion related morbidities. However, delivery mode is not a contributing factor.

Conclusion: Additional efforts are needed in this sector of public health given the increasing trends in maternal morbidity. Providing point-of-contact identification is critical to preventing maternal morbidity by SMM and requires adaptations to the present medical care system. Establishing a dedicated EMR database as the preferred medical record system for reporting and tracking SMM cases can streamline the process and help identify trending issues. Modifications to the database to allow simpler reporting of SMM indicators and patient trend analysis would benefit maternal care. There are multiple opportunities at the hospital level for reform and advancement to reduce the increasing rate of SMM.

Author(s):

Catherine Baye Easton, Kendyl Schreiber, Yijin Wert, Holly Thomas, Brian Cohen, Abigail Lukasik and Courtney Potteiger

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