What 7 Million Births Reveal About Maternal Risk in the U.S.

A new study developed by Premier and U.S. Department of Health and Human Services (HHS) Office on Women’s Health (OWH) is offering new insight into one of healthcare’s most pressing challenges: identifying which pregnant patients are most at risk for severe complications before those complications occur.

Published in "The Lancet Regional Health – Americas", the study analyzed more than 7.1 million inpatient delivery hospitalizations across 864 hospitals in 49 states to better understand the factors associated with severe maternal morbidity (SMM), a term used to describe unexpected outcomes of labor and delivery that can result in significant short- or long-term health consequences.

The research comes at a critical time for maternal health in the U.S. despite growing awareness and national attention, rates of severe maternal morbidity remain high, with providers continuing to face challenges identifying patients at risk early enough to intervene.

Why Maternal Risk Is Harder to Predict than it Seems

One of the biggest challenges in maternal health is that risk rarely presents in a straightforward way.

Pregnant patients often have multiple overlapping conditions that can influence outcomes differently depending on severity, timing and access to care. Chronic diseases, pregnancy-related complications and broader social and clinical factors can all contribute to increased risk. Yet many traditional maternal risk models rely on binary approaches that categorize patients as either having risk or not.

In practice, that can oversimplify maternal care.

Not all conditions contribute equally to severe outcomes, and not all complications carry the same level of clinical severity. Existing models may also fail to fully capture pregnancy-specific complexities or the ways multiple conditions interact across the continuum of care.

The result is a gap between how maternal risk is measured and how it presents in clinical settings.

A More Precise Approach to Maternal Risk Identification

To address these challenges, researchers developed a new maternal Prenatal Risk Index (m-PRI), designed to provide a more nuanced view of maternal risk.

Unlike traditional models, the m-PRI weights maternal conditions based on how strongly they are associated with increasingly severe maternal outcomes. Rather than treating all complications equally, the model accounts for differences in severity, helping providers better identify which patients may require earlier intervention or closer monitoring.

The model ultimately incorporated 28 maternal risk factors and demonstrated improved predictive performance compared to existing maternal comorbidity scoring systems. Notably, nearly all patients who experienced severe maternal morbidity in the study had a nonzero m-PRI score, suggesting the tool may improve identification of high-risk patients who might otherwise be overlooked.

While the study represents an important advancement in maternal risk stratification, it also reflects a broader effort by Premier to help health systems improve maternal and infant outcomes through data, analytics and collaborative performance improvement initiatives.

Expanding Maternal Health Improvement Beyond the Study

Improving maternal outcomes requires more than identifying risk. Health systems also need the infrastructure to turn insight into action through standardized measurement, evidence-based care practices and coordinated performance improvement efforts.

Over the last several years, collaboratives and data-sharing initiatives have played an increasingly important role in helping providers better understand maternal risk, reduce variation in care and scale best practices across organizations.

Premier has been involved in this work for decades through partnerships with hospitals, health systems and federal agencies focused on improving maternal and infant outcomes. One example was the American Excess Insurance Exchange (AEIX) Perinatal Improvement Collaborative, which helped participating hospitals implement evidence-based maternal safety practices, leverage standardized data and strengthen performance improvement efforts aimed at improving maternal and infant outcomes.

More recently, Premier launched the Perinatal Improvement Collaborative (PIC) to help health systems use standardized data and performance improvement methodologies to reduce preventable maternal and neonatal harm and deaths. That work later expanded through a partnership with the HHS Office on Women’s Health to create the HHS Perinatal Improvement Collaborative, which now connects more than 250 hospitals and health systems nationwide.

Participating organizations capture and evaluate more than 150 clinical and non-clinical measures, including social determinants of health data, to better understand drivers of preventable harm and disparities in maternal and infant outcomes. The collaborative also supports the implementation of evidence-based practices and standardized care bundles designed to improve care delivery across participating sites.

Premier is also supporting maternal health improvement through technologies that help providers identify and monitor at-risk patients across the continuum of care. Solutions such as Quality Continuum integrate acute and non-acute patient data to support earlier intervention, continuity of care and more proactive management of maternal health risks.

Moving Maternal Health Forward

Improving maternal outcomes will require more than any single study, model or initiative. It will take continued collaboration across providers, health systems, policymakers and industry organizations to better understand risk, scale evidence-based practices and ensure patients receive timely, coordinated care.

As health systems continue to navigate growing maternal health challenges, efforts that combine data, clinical insight and collaborative improvement strategies may play an increasingly important role in helping providers move from reactive care to earlier, more proactive intervention.