Miren B Dhudasia1,2, Sagori Mukhopadhyay1,2,3, Karen M Puopolo4,2,3. 1. Section on Newborn Medicine, Pennsylvania Hospital, Philadelphia, Pennsylvania. 2. Division of Neonatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; and. 3. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. 4. Section on Newborn Medicine, Pennsylvania Hospital, Philadelphia, Pennsylvania; karen.puopolo@uphs.upenn.edu.
Abstract
BACKGROUND: Multivariate predictive models for estimating the risk of neonatal early-onset sepsis (EOS) are available as a Web-based sepsis risk calculator (SRC) and may reduce the proportion of newborns empirically treated with antibiotics after birth. EOS risk assessment based on such models would require workflow changes at most birth hospitals. METHODS: A multidisciplinary team of obstetric, neonatal, and information technology staff at a large, academic, birth hospital collaborated to implement the SRC. The obstetric electronic medical record was modified to provide a link to the SRC. Labor and delivery nurses calculated the sepsis risk at birth and alerted neonatal clinicians for risk estimates ≥0.7 cases per 1000 live births. Subsequent interventions were based on the risk estimate and newborn clinical examination. We compared the proportion of infants born at ≥36 weeks' gestation with laboratory testing and empirical antibiotics for risk of EOS during the 15-month periods before (n = 5692) and after (n = 6090) implementation. EOS cases were reviewed to assess for safety. RESULTS: Empirical antibiotic use among newborns ≤72 hours old declined by 42% (6.3% to 3.7%; relative risk 0.58 [95% confidence interval, 0.50-0.69]), and laboratory testing declined by 82% (26.9% to 4.9%; relative risk 0.18 [95% confidence interval, 0.16-0.21]). The EOS incidence was not different between the study periods, and no safety concerns were identified. CONCLUSIONS: The SRC was integrated into the workflow of a large, academic perinatal center, resulting in significant reductions in antibiotics and laboratory testing for EOS and demonstrating the potential for this approach to impact national practice.
BACKGROUND: Multivariate predictive models for estimating the risk of neonatal early-onset sepsis (EOS) are available as a Web-based sepsis risk calculator (SRC) and may reduce the proportion of newborns empirically treated with antibiotics after birth. EOS risk assessment based on such models would require workflow changes at most birth hospitals. METHODS: A multidisciplinary team of obstetric, neonatal, and information technology staff at a large, academic, birth hospital collaborated to implement the SRC. The obstetric electronic medical record was modified to provide a link to the SRC. Labor and delivery nurses calculated the sepsis risk at birth and alerted neonatal clinicians for risk estimates ≥0.7 cases per 1000 live births. Subsequent interventions were based on the risk estimate and newborn clinical examination. We compared the proportion of infants born at ≥36 weeks' gestation with laboratory testing and empirical antibiotics for risk of EOS during the 15-month periods before (n = 5692) and after (n = 6090) implementation. EOS cases were reviewed to assess for safety. RESULTS: Empirical antibiotic use among newborns ≤72 hours old declined by 42% (6.3% to 3.7%; relative risk 0.58 [95% confidence interval, 0.50-0.69]), and laboratory testing declined by 82% (26.9% to 4.9%; relative risk 0.18 [95% confidence interval, 0.16-0.21]). The EOS incidence was not different between the study periods, and no safety concerns were identified. CONCLUSIONS: The SRC was integrated into the workflow of a large, academic perinatal center, resulting in significant reductions in antibiotics and laboratory testing for EOS and demonstrating the potential for this approach to impact national practice.
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