New Algorithm Sheds Light on Why Severe Maternal Morbidity Happens

Cracking the Code: Why Do Severe Maternal Complications Happen?

For years, hospitals and researchers have tracked severe maternal morbidity (SMM)—life-threatening complications during childbirth—but the true underlying causes often remained hidden. A recent study published in Obstetrics & Gynecology introduces a breakthrough: a new hierarchical algorithm that can accurately pinpoint the main culprit behind each SMM case, transforming how we understand and tackle maternal health crises.

Developing a Smarter Tool

The research team spent eight years creating and perfecting the algorithm, using data from over 150,000 SMM cases across millions of deliveries. By analyzing records from California, Oregon, Washington, and national datasets, they ensured the tool works at scale, even when reviewing each individual medical chart isn’t possible.

Their algorithm uses hospital codes to assign a single, primary underlying condition to every SMM case. Impressively, it matched expert medical review over 94% of the time.

The Biggest Culprits: Hemorrhage, Hypertension, Infection

When the algorithm was unleashed on state and national data, clear patterns emerged:

Hemorrhage (severe bleeding) was the number one cause, responsible for about half of all SMM cases.

Hypertensive disorders (including preeclampsia and eclampsia) and infections together made up another 30% of cases.

Surprisingly, cardiovascular conditions—while the leading cause of maternal death—were uncommon as a root cause of SMM.

This finding is powerful: while maternal deaths are most often caused by heart problems, the complications most likely to bring women close to death during delivery are different and potentially more preventable with timely care.

Rethinking Maternal Safety Strategies

The study highlights an important lesson: improving SMM rates may not directly lower maternal deaths, and vice versa. Hemorrhage and hypertension are often acute and treatable during delivery, while fatal heart complications tend to strike postpartum. Policies and hospital practices must recognize this difference for effective action.

Limitations and the Way Forward

While this new approach marks a huge step, the researchers acknowledge some limitations. The algorithm can only use available hospital data, and some events—like substance use or mental health crises—can slip through the cracks. Still, the tool sets a new standard for tracking and targeting the causes of severe maternal complications on a population level.

Key Takeaways:

New algorithm identifies primary cause for each severe maternal complication, matching expert review 94% of the time.

Hemorrhage, hypertensive disorders, and infection account for up to 80% of SMM cases.

Cardiovascular disease is the top cause of maternal death but less common as an immediate cause of SMM.

Improving SMM rates alone may not impact maternal mortality rates—and vice versa.

This tool can help hospitals and policymakers better target life-saving interventions.

Citation:

Main EK, McCormick EK, Tomlinson MW, et al. Development and Application of an Algorithm to Identify the Primary Underlying Condition for Cases of Severe Maternal Morbidity. Obstetrics & Gynecology. 2026;147(6):892–901. doi:10.1097/AOG.0000000000006299