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Updated: May 14, 2026

Human Placental and Decidual Organ Cultures to Study Infections at the Maternal-fetal Interface
Published on: July 21, 2016
Patterns of obstetric infection rates in a large sample of US hospitals
Sarah L Goff1, Penelope S Pekow, Jill Avrunin
1Department of Medicine, Baystate Medical Center, Springfield, MA, USA. Sarah.Goffmd@baystatehealth.org
Objective:
Maternal infection is a common complication of childbirth, yet little is known about the extent to which infection rates vary among hospitals. We estimated hospital-level risk-adjusted maternal infection rates (RAIR) in a large sample of US hospitals and explored associations between RAIR and select hospital features.
Study Design:
This retrospective cohort study included hospitals in the Perspective database with >100 deliveries over 2 years. Using a composite measure of infection, we estimated and compared RAIR across hospitals using hierarchical generalized linear models. We then estimated the amount of variation in RAIR attributable to hospital features.
Results:
Of the 1,001,189 deliveries at 355 hospitals, 4.1% were complicated by infection. Patients aged 15-19 years were 50% more likely to experience infection than those aged 25-29 years. Rupture of membranes >24 hours (odds ratio [OR], 3.0; 95% confidence interval [CI], 3.24-3.5), unengaged fetal head (OR, 3.11; 95% CI, 2.97-3.27), and blood loss anemia (OR, 2.42; 95% CI, 2.34-2.49) had the highest OR among comorbidities commonly found in patients with infection. RAIR ranged from 1.0-14.4% (median, 4.0%; interquartile range, 2.8-5.7%). Hospital features such as geographic region, teaching status, urban setting, and higher number of obstetric beds were associated with higher infection rates, accounting for 14.8% of the variation observed.
Conclusion:
Obstetric RAIR vary among hospitals, suggesting an opportunity to improve obstetric quality of care. Hospital features such as region, number of obstetric beds, and teaching status account for only a small portion of the observed variation in infection rates.
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