Improved Recognition of Maternal Deaths Using Modern Data Analytics

Abstract

Objective: To use a data-fusion approach to improve ascertainment of maternal deaths not detected with standard surveillance strategies.

Methods: We conducted a retrospective cohort study from the electronic health records of a tertiary medical center from 2011 to 2018. Cases of maternal death were identified in two ways: 1) using a standard medical informatics service query of hospital data and 2) using the TriNetX discovery tool as patients with a vital status of "deceased" and evidence of antecedent pregnancy exposure based on such factors as obstetric diagnostic codes or obstetric-related procedures. Potential cases of maternal death identified by the latter method underwent chart review to confirm timing of death compared with timing of last appreciable pregnancy, and to characterize the details of these deaths. The primary outcome was pregnancy-associated mortality during pregnancy or within the first postpartum year in the discovery cohort compared with the hospital-identified cohort. Secondary outcomes included causes of death and comorbidities.

Results: During the study period, the standard service query identified 23 maternal deaths. The discovery tool identified 18 additional patients confirmed on subsequent chart review to represent pregnancy-associated deaths, a 78% increase in ascertainment of which a greater proportion represented postpartum deaths. The majority (61%) of newly ascertained mortalities were related to cardiac causes or other medical comorbidities. Although many hospital-ascertained cases were associated with deaths after delivery of a living newborn, more deaths after early pregnancy loss or termination were identified through the discovery tool.

Conclusion: Improved recognition of pregnancy-associated deaths can be achieved with modern data analytics.