Hospital-Based Severe Maternal Morbidity Surveillance and Review

Abstract

Background: Learning from promising maternal health interventions is limited by the lack of standardized outcome measures needed for their evaluation. We describe the development and utilization of Maryland’s severe maternal morbidity (SMM) surveillance by the Maryland Maternal Health Innovation (MDMOM) program. Methods: To ascertain the development, attributes, and data collected by SMM surveillance, we use 2020–2024 MDMOM program records and 2023 surveillance data. Hospital reports and MDMOM’s 2023 maternal health care provider survey data are used to document policy and practice changes attributable to participation in SMM surveillance. Data collected from MDMOM’s “Learning from Adverse Events in Maryland” trainees are analyzed to explore knowledge score changes (Wilcoxon signed-rank test) and training satisfaction. Results: SMM surveillance is a simple, flexible, stable, high-quality system for identifying areas of care in need of improvement. Before October 2024, when state legislation mandated all hospitals to participate, 24 of 32 hospitals (80% of the state’s annual deliveries) engaged in SMM surveillance. The data are used to assess SMM levels and contributors, disparities (eg, intensity of care practices and outcome differences between patient groups), and preventability. Knowledge scores improved after the training on SMM surveillance findings ( P <0.001). Data can be used for quality improvement and to generate PCOR hypotheses. Conclusions: Maryland established hospital-based SMM surveillance, demonstrated its value, and gained legislative support for statewide scale-up. This model surveillance system can be replicated in other states, aiming to better understand and address SMM and SMM disparities.