Resource Utilization and Costs Associated with Approaches to Identify Infants with Early-Onset Sepsis.
Resource Utilization and Costs Associated with Approaches to Identify Infants with Early-Onset Sepsis.
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资源利用和与识别早期败血症婴儿的方法相关的成本。
DOI：
10.1177/23814683231226129
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发表时间：
2024-01
影响因子：
--
通讯作者：
Owens, Douglas K.
中科院分区：
文献类型：
--
作者：
Guan, Grace;Joshi, Neha S.;Frymoyer, Adam;Achepohl, Grace D.;Dang, Rebecca;Taylor, N. Kenji;Salomon, Joshua A.;Goldhaber-Fiebert, Jeremy D.;Owens, Douglas K.
Objective.根据美国儿科学会（AAP）2018年的建议，比较3种替代筛查方法的资源利用和相关成本，以确定≥35周胎龄出生婴儿的早发性脓毒症（EOS）。研究设计. AAP推荐的3种方法的基于决策树的成本分析：1）分类风险评估（根据绒毛膜炎暴露状态分类），2）新生儿败血症计算器（基于围产期风险因素的多变量预测模型），3）加强临床观察（基于系列临床检查的评估）。我们评估了卫生系统的资源利用和直接成本（2022美元）。结果与新生儿败血症计算器（每1,000例活产112天和3.6%）和加强临床观察（每1,000例活产99天和3.1%）相比，分类风险评估导致最大的新生儿重症监护室使用（每1,000例活产210天）和抗生素暴露（6.8%）。虽然3种方法的每例活产医院成本相似-分类风险评估成本为1，360美元，新生儿败血症计算器成本为1，317美元，加强临床观察成本为1，310美元-接受分类风险评估干预的婴儿成本约为其他2种策略的两倍。结果对数据参数的变化具有稳健性。结论新生儿败血症计算器和加强的临床观察方法可能优于分类风险评估，因为它们减少了接受干预的婴儿数量，从而减少了抗生素暴露和相关费用。所有3种方法对所有活产的成本相似，先前的文献表明了相似的健康结果。纳入新生儿期抗生素暴露的下游影响应在成本效益分析中进行评估。在2018年美国儿科学会推荐的3种方法中，用于识别≥35周出生的婴儿中的早发性脓毒症，与新生儿脓毒症计算器和加强临床观察方法相比，分类风险评估方法导致接受评估以排除早发性脓毒症的婴儿数量约为两倍。虽然在整个活产人群中，3种方法的住院费用相似，但与分类风险评估方法相比，新生儿败血症计算器和加强临床观察方法减少了抗生素暴露、新生儿重症监护室入院以及与作为筛查方法一部分的干预相关的住院费用。这是抽象的视觉表现。
Objective. To compare resource utilization and costs associated with 3 alternative screening approaches to identify early-onset sepsis (EOS) in infants born at ≥35 wk of gestational age, as recommended by the American Academy of Pediatrics (AAP) in 2018. Study Design. Decision tree–based cost analysis of the 3 AAP-recommended approaches: 1) categorical risk assessment (categorization by chorioamnionitis exposure status), 2) neonatal sepsis calculator (a multivariate prediction model based on perinatal risk factors), and 3) enhanced clinical observation (assessment based on serial clinical examinations). We evaluated resource utilization and direct costs (2022 US dollars) to the health system. Results. Categorical risk assessment led to the greatest neonatal intensive care unit usage (210 d per 1,000 live births) and antibiotic exposure (6.8%) compared with the neonatal sepsis calculator (112 d per 1,000 live births and 3.6%) and enhanced clinical observation (99 d per 1,000 live births and 3.1%). While the per-live birth hospital costs of the 3 approaches were similar—categorical risk assessment cost $1,360, the neonatal sepsis calculator cost $1,317, and enhanced clinical observation cost $1,310—the cost of infants receiving intervention under categorical risk assessment was approximately twice that of the other 2 strategies. Results were robust to variations in data parameters. Conclusion. The neonatal sepsis calculator and enhanced clinical observation approaches may be preferred to categorical risk assessment as they reduce the number of infants receiving intervention and thus antibiotic exposure and associated costs. All 3 approaches have similar costs over all live births, and prior literature has indicated similar health outcomes. Inclusion of downstream effects of antibiotic exposure in the neonatal period should be evaluated within a cost-effectiveness analysis. Of the 3 approaches recommended by the American Academy of Pediatrics in 2018 to identify early-onset sepsis in infants born at ≥35 weeks, the categorical risk assessment approach leads to about twice as many infants receiving evaluation to rule out early-onset sepsis compared with the neonatal sepsis calculator and enhanced clinical observation approaches. While the hospital costs of the 3 approaches were similar over the entire population of live births, the neonatal sepsis calculator and enhanced clinical observation approaches reduce antibiotic exposure, neonatal intensive care unit admission, and hospital costs associated with interventions as part of the screening approach compared with the categorical risk assessment approach. This is a visual representation of the abstract.
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影响因子：
1.8
作者：
Fuchs A;Bielicki J;Mathur S;Sharland M;Van Den Anker JN
通讯作者：
Van Den Anker JN
影响因子：
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作者：
Alm, Bernt;Erdes, Laslo;Wennergren, Goeran
通讯作者：
Wennergren, Goeran
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2
作者：
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通讯作者：
Getahun, Darios
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作者：
Kiser, Courtney;Nawab, Ursula;Aghai, Zubair H.
通讯作者：
Aghai, Zubair H.
影响因子：
2.9
作者：
Joshi, Neha S.;Huynh, Karen;Frymoyer, Adam
通讯作者：
Frymoyer, Adam