Using a Claims-Based Framework to Identify Severe Maternal Morbidities in a Commercially Insured US Population

Area of Science:

• Obstetrics and Gynecology
• Public Health
• Health Services Research

Background:

• Severe maternal morbidities (SMMs) represent significant health risks, with many being preventable.
• Understanding the circumstances and variations in SMMs is critical for developing effective quality improvement strategies.
• Existing metrics often rely on inpatient samples, necessitating broader analyses.

Purpose of the Study:

• To evaluate a framework for benchmarking severe maternal morbidities (SMMs).
• To identify opportunities for quality improvement in maternal healthcare.
• To analyze geographic variations in SMM rates using administrative claims data.

Main Methods:

• Retrospective analysis of de-identified administrative claims data for commercially insured women in the US.
• Inclusion of longitudinal data linking inpatient delivery episodes and the 6-week postpartum period.
• Calculation of SMM rates per 10,000 deliveries across 5 domains: Hemorrhage/Transfusion, Preeclampsia/Eclampsia, Cardiovascular, Sepsis, and Thromboembolism/Cerebrovascular.

Main Results:

• Identified significant geographic variation in SMM rates across US states.
• Demonstrated a 3-fold difference in hemorrhage rates between Alabama and Oregon.
• Confirmed the utility of administrative claims data for calculating SMM rates and identifying variations.

Conclusions:

• Administrative claims data are valuable for monitoring SMM rates and geographic disparities.
• Differentiating SMMs by onset (preadmission, inpatient, postpartum) is crucial for targeted interventions.
• Local and hospital-level interventions, alongside postdischarge monitoring, can reduce SMM prevalence and postpartum complications.