Sedler Jennifer, Khaki I Sheevaun, Phillipi Carrie A, Dukhovny Dmitry, DeVane Kenneth, Gievers Ladawna
Department of Pediatrics, Stanford University, Palo Alto, Calif.
Department of Pediatrics, Oregon Health and Science University, Portland, Ore.
Pediatr Qual Saf. 2020 Sep 25;5(5):e347. doi: 10.1097/pq9.0000000000000347. eCollection 2020 Sep-Oct.
Factors affecting exclusive breastfeeding rates are complex. Evaluations for early-onset sepsis can negatively impact breastfeeding success. We sought to determine whether implementing an algorithm utilizing the sepsis risk score (SRS) in chorioamnionitis-exposed newborns would increase exclusive breastfeeding rates. We collaborated with healthcare systems experts to analyze and understand our outcomes.
We describe a retrospective cohort study of chorioamnionitis-exposed newborns 35 weeks and older gestation in the Mother-Baby Unit at our institution following a quality improvement project that implemented an SRS algorithm. We compared exclusive breastfeeding rates over 2 time periods, 33 months before and 15 months after SRS algorithm implementation. We completed bivariate comparisons using chi-square and Mann-Whitney U tests to understand the factors contributing to exclusive breastfeeding rates. In a secondary analysis, breastfeeding rates and demographic patterns were examined using p-charts.
Following algorithm implementation, exclusive breastfeeding rates increased from 49% to 58% ( = 0.10) in chorioamnionitis-exposed newborns. Factors associated with increased exclusive breastfeeding included Caucasian race, English as the primary language, private insurance, vaginal delivery, and positive group B status. In the secondary analysis, the proportion of non-Hispanic mothers increased from 63% to 80% during the study.
Despite SRS implementation, exclusive breastfeeding rates increased but not significantly, and certain sociodemographic factors remain associated with exclusive breastfeeding. Secondary analysis revealed an overall demographic shift affecting the dataset, highlighting the importance of thorough data analysis when evaluating a quality improvement project.
影响纯母乳喂养率的因素很复杂。早发型败血症的评估可能会对母乳喂养的成功产生负面影响。我们试图确定在暴露于绒毛膜羊膜炎的新生儿中实施利用败血症风险评分（SRS）的算法是否会提高纯母乳喂养率。我们与医疗系统专家合作分析并理解我们的结果。
我们描述了一项回顾性队列研究，该研究针对我们机构母婴病房中孕周35周及以上且暴露于绒毛膜羊膜炎的新生儿，这是在实施SRS算法的质量改进项目之后进行的。我们比较了两个时间段的纯母乳喂养率，即SRS算法实施前33个月和实施后15个月。我们使用卡方检验和曼 - 惠特尼U检验完成双变量比较，以了解影响纯母乳喂养率的因素。在二次分析中，使用p图检查母乳喂养率和人口统计学模式。
实施算法后，暴露于绒毛膜羊膜炎的新生儿纯母乳喂养率从49%提高到了58%（ = 0.10）。与纯母乳喂养率增加相关的因素包括白人种族、以英语为主要语言、私人保险、阴道分娩以及B族链球菌检测呈阳性。在二次分析中，研究期间非西班牙裔母亲的比例从63%增加到了80%。
尽管实施了SRS，但纯母乳喂养率有所提高但不显著，并且某些社会人口学因素仍然与纯母乳喂养相关。二次分析揭示了影响数据集的总体人口结构变化，突出了在评估质量改进项目时进行全面数据分析的重要性。
