UnityPoint Cut Maternal Sepsis Deaths to 0 with Epic Care Path

Why It Matters

Eliminating maternal sepsis deaths demonstrates how targeted EHR pathways can dramatically improve patient safety and set a new standard for obstetric care across large health networks.

Key Takeaways

• Maternal sepsis mortality fell from 3.2% to 0%.
• Epic care path used California Maternal Quality Care Collaborative criteria.
• Order set compliance rose to 86% across the system.
• Antibiotics administered within one hour for 66% of cases.
• UnityPoint handles 20,000+ deliveries yearly at 35 hospitals.

Pulse Analysis

Maternal sepsis remains a leading cause of preventable death in the United States, accounting for roughly one in ten maternal fatalities. While national rates hover around 2‑3 per 10,000 births, many hospitals lack real‑time tools to flag early signs in pregnant patients. UnityPoint’s adoption of a customized Epic care path illustrates how health systems can translate generic sepsis alerts into obstetric‑specific safeguards, aligning technology with the unique physiologic changes of pregnancy.

The care path leverages the California Maternal Quality Care Collaborative’s criteria, extending surveillance from 20 weeks gestation through three days postpartum. By routing flagged cases into a single advisory and order set, clinicians received standardized prompts for rapid assessment and antibiotic therapy. Training programs for staff and patient education reinforced the workflow, driving order‑set compliance up to 86% and ensuring antibiotics were given within an hour for two‑thirds of cases—key metrics linked to improved survival. These operational gains complement Epic’s broader predictive sepsis model, which has already averted an estimated 190 adult deaths at UnityPoint.

Beyond the immediate outcomes, UnityPoint’s success signals a scalable blueprint for other multi‑hospital systems seeking to curb maternal morbidity. The integration of validated, pregnancy‑specific criteria into existing EHR platforms reduces the need for separate software, lowering implementation costs while enhancing data consistency. As payers and regulators increasingly tie reimbursement to quality metrics, such evidence‑based pathways could become a benchmark for value‑based care. Moreover, the project underscores the growing role of artificial intelligence and decision support in obstetrics, paving the way for more nuanced, condition‑specific alerts that protect both mothers and newborns.