Predicting Appropriate Admission of Bronchiolitis Patients in the Emergency Room

摘要 毛细支气管炎是导致幼儿住院的最常见疾病。岁以下儿童 第二，细支气管炎每年的住院费用总额为17.3亿元。每年在美国，287,000 由于细支气管炎而出现急诊（艾德）就诊，住院率为32- 40%。 由于缺乏管理细支气管炎的证据和客观标准，艾德处置决定（医院 入院或出院回家）往往是主观作出的，从而导致显著的实践差异。研究 审查入院需求表明，艾德高达29%的入院是不必要的。约6%的艾德 因细支气管炎出院导致艾德在入院时复发。这些不适当的处置浪费有限 医疗保健资源，增加患者和父母的痛苦，使患者面临医源性风险，并恶化 结果。 临床指南旨在减少实践差异，改善临床医生的决策。现有 细支气管炎指南对患者预后的改善有限。方法上的缺陷包括 指南没有为艾德决定入院或出院提供具体的门槛， 详细程度，未考虑患者和疾病特征（包括合并症）的差异。 预测模型经常用于补充临床指南，减少实践差异， 改善临床医生的决策。在真实的时间中使用，预测模型可以提供支持的客观标准 通过历史数据制定个性化的疾病管理计划并指导入院决策。然而，在这方面， 艾德中毛细支气管炎患者的现有预测模型具有局限性，包括准确性低， 假设实际的艾德处置决策是适当的。到目前为止，还没有关于 有适当的准入。没有一个模型是建立在适当的承认的基础上的， 实际入院是必要的，实际艾德出院是不安全的。 为填补差距，拟议项目将：（1）制定适当医院的操作定义 （2）建立一个新的预测模型，并测试其准确性， （3）进行模拟，以估计 使用模型对毛细支气管炎结局的影响。该项目将产生一个新的预测模型， 可操作，以指导和改善ED中细支气管炎患者的处置决策。 模型将减少医源性风险，患者和父母的痛苦，医疗保健使用和成本，并改善 毛细支气管炎患者的结局。如果模型被证明是准确的，并与改善的结果相关联， 未来的研究将测试在随机对照试验中使用它的影响， 现有的电子医疗记录，以促进实时决策。

Abstract Bronchiolitis is the most common illness leading to hospitalization in young children. For children under age two, bronchiolitis incurs an annual total inpatient cost of $1.73 billion. Each year in the U.S., 287,000 emergency department (ED) visits occur because of bronchiolitis, with a hospital admission rate of 32-40%. Due to a lack of evidence and objective criteria for managing bronchiolitis, ED disposition decisions (hospital admission or discharge to home) are often made subjectively resulting in significant practice variation. Studies reviewing admission need suggest that up to 29% of admissions from the ED are unnecessary. About 6% of ED discharges for bronchiolitis result in ED returns with admission. These inappropriate dispositions waste limited healthcare resources, increase patient and parental distress, expose patients to iatrogenic risks, and worsen outcomes. Clinical guidelines are designed to reduce practice variation and improve clinicians’ decision making. Existing guidelines for bronchiolitis offer limited improvement in patient outcomes. Methodological shortcomings include that the guidelines provide no specific thresholds for ED decisions to admit or to discharge, have an insufficient level of detail, and do not account for differences in patient and illness characteristics including co-morbidities. Predictive models are frequently used to complement clinical guidelines, reduce practice variation, and improve clinicians’ decision making. Used in real time, predictive models can present objective criteria supported by historical data for an individualized disease management plan and guide admission decisions. However, existing predictive models for bronchiolitis patients in the ED have limitations, including low accuracy and the assumption that the actual ED disposition decision was appropriate. To date, no operational definition of appropriate admission exists. No model has been built based on appropriate admissions, which include both actual admissions that were necessary and actual ED discharges that were unsafe. To fill the gap, the proposed project will: (1) Develop an operational definition of appropriate hospital admission for bronchiolitis patients in the ED. (2) Develop and test the accuracy of a new model to predict appropriate hospital admission for a bronchiolitis patient in the ED. (3) Conduct simulations to estimate the impact of using the model on bronchiolitis outcomes. The project will produce a new predictive model that can be operationalized to guide and improve disposition decisions for bronchiolitis patients in the ED. Broad use of the model would reduce iatrogenic risk, patient and parental distress, healthcare use, and costs and improve outcomes for bronchiolitis patients. If the model proves to be accurate and associated with improved outcomes, future study will test the impact of using it in a randomized controlled trial following its implementation into an existing electronic medical record to facilitate real-time decision making.