PDF(Pubmed)
Abstract：
Background Neonatal intensive care units (NICU) provide essential medical care to neonates; however, they are associated with hospital-acquired infections, less maternal-newborn bonding, and high costs. Implementing strategies to lower NICU admission rates and shorten NICU length of stay (LOS) is essential. This study uses causal-inference methods to evaluate the impact of care managers using new technology to identify and risk stratify pregnancies on NICU admissions and NICU LOS. The NICU LOS will decrease as a result of the use of new technology by care managers. Study design This retrospective study utilized delivery claims data of pregnant women from the CareFirst BlueCross BlueShield Community Health Plan District of Columbia from 2013 to 2022, which includes the pre-intervention period before the use of new technology by care managers and the post-intervention period with the use of new technology by care managers. Our sample had 4,917 deliveries whose maternal comorbidities were matched with their neonate\'s outcomes. Methods To evaluate the impact of the technological intervention, both Generalized Linear Models (GLMs) and Bayesian Structural Time-Series (BSTS) models were used. Results Our findings from the GLM models suggest an overall average reduction in the odds of NICU admissions of 29.2% and an average decrease in NICU LOS from 7.5%-58.5%. Using BSTS models, we estimate counterfactuals for NICU admissions and NICU LOS, which suggest an average reduction in 48 NICU admissions and 528 NICU days per year. Conclusion Equipping care managers with better technological tools can lead to significant improvements in neonatal health outcomes as indicated by a reduction in NICU admissions and NICU LOS.
摘要：
背景：新生儿重症监护病房（NICU）为新生儿提供基本的医疗护理；然而，它们与医院获得性感染有关，产妇与新生儿的联系较少，和高成本。实施降低NICU入院率和缩短NICU住院时间（LOS）的策略至关重要。本研究使用因果推断方法来评估护理管理人员使用新技术识别和风险分层怀孕对NICU入院和NICULOS的影响。由于护理管理人员使用新技术，NICU的LOS将减少。研究设计这项回顾性研究利用了2013年至2022年哥伦比亚CareFirstBlueCrossBlueShield社区卫生计划区孕妇的分娩索赔数据，其中包括护理管理人员使用新技术之前的干预前阶段和护理管理人员使用新技术的干预后阶段。我们的样本有4,917例分娩，其产妇合并症与新生儿结局相匹配。方法评估技术干预的影响，使用广义线性模型(GLM)和贝叶斯结构时间序列(BSTS)模型。结果我们从GLM模型的发现表明，NICU入院几率总体平均降低29.2%，NICU住院时间平均降低7.5%-58.5%。使用BSTS模型，我们估计NICU入院和NICULOS的反事实，这表明每年平均减少48例NICU住院时间和528天。结论为护理管理人员配备更好的技术工具可以显着改善新生儿健康结局，如减少NICU入院人数和NICULOS所示。
