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。适用于未成年儿童 第二，毛细支气管炎每年的住院总费用为17.3亿美元。在美国，每年有28.7万人 急诊科就诊的原因是毛细支气管炎，住院率为32%-40%。 由于缺乏处理毛细支气管炎的证据和客观标准，急诊科处理决定(医院 入院或出院)通常是主观作出的，导致实践上的重大变化。研究 审查入学需要表明，多达29%的入学申请是不必要的。约6%的边缘 毛细支气管炎的出院导致ED在入院时返回。这些不恰当的处置浪费有限 医疗资源，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 毛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 指引没有为教育署作出接纳或释放的决定提供具体的门槛，有不足之处 详细程度，不考虑患者和疾病特征的差异，包括共病。 预测模型经常被用来补充临床指南，减少实践差异，以及 提高临床医生的决策水平。实时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体化的疾病管理计划，指导入院决策。然而， 急诊室现有的毛细支气管炎患者预测模型存在局限性，包括准确性低和 假设实际的ED处置决定是适当的。到目前为止，没有可操作的定义 存在适当的入院条件。还没有建立基于适当招生的模型，其中包括两者 实际需要的入院和不安全的实际急救出院。 为了填补这一空白，拟议的项目将：(1)制定适当医院的业务定义 急诊科毛细支气管炎患者入院。(2)开发和检验新模型的预测精度 急诊科毛细支气管炎患者的适当入院。(3)进行模拟以估计 使用该模型对毛细支气管炎预后的影响。该项目将产生一种新的预测模型，可以 用于指导和改进急诊科毛细支气管炎患者的处置决策。广泛使用 该模式将降低医源性风险、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预后。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，在它被实施到 现有的电子病历，便于实时决策。

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.