Improving Pediatric Field Trauma Triage

改善儿科现场创伤分诊

• 批准号: 10740719
• 负责人: Taylor McCormick
• 金额: $ 15.14万
• 依托单位: DENVER HEALTH AND HOSPITAL AUTHORITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10740719
• 关键词: Improving; Pediatric; Field; Trauma; Triage

PROJECT SUMMARY Unintentional injury is the leading cause of death among children in the United States. Several studies demonstrate decreased mortality when severely injured children are transported to high-level (levels 1 and 2) and designated pediatric trauma centers, compared with low-level (levels 3 or greater) and non-trauma centers. Field trauma triage aims to identify patients who require high-level trauma center resources, with 95% sensitivity and 65% specificity goals set by the American College of Surgeons Committee on Trauma (ACSCOT). The ACSCOT and the Centers for Disease Control and Prevention (CDC) publish field triage criteria, which are widely used by emergency medical service (EMS) agencies nationally. These criteria were developed and updated through expert consensus primarily for adults, and have been shown to undertriage severely injured children, with a reported sensitivity as low as 65%. In a 2020 systematic review, the Pediatric Trauma Society Research Committee stated the data supporting field triage criteria are “minimal and of low quality,” specifically calling for new research to establish individual criteria and combinations of criteria to determine where an injured child should be transported. While the need for refined pediatric field triage criteria is clear, progress has been limited by the lack of large-scale, linked prehospital and outcome data and implementation failures including missing and inaccurate physiologic measurements (e.g. blood pressure and mental status), and overreliance on provider judgement as the sole determinant of trauma center need. To address these gaps and improve the prehospital triage of injured children, we will perform a descriptive analysis of undertriage of children in 7 states using AHRQ Healthcare Cost and Utilization (HCUP) databases, derive and validate refined pediatric field triage using predictive modeling of a robust population-based dataset containing prehospital and outcome data from Los Angeles County, and conduct a mixed-methods study evaluating implementation outcomes of the refined criteria in an urban EMS system. This proposal directly addresses AHRQ priority populations including pediatric, minority, rural, and low-income, and is directly responsive to AHRQ research priorities of improving health care patient safety by identifying potential harm from and disparities in undertriage, designing and evaluating interventions to improve patient safety, and harnessing data (including HCUP databases) to improve health care quality and patient outcomes. Successful completion of this work will advance this field of study by describing the potential health impact of accurate field triage, establishing preliminary implementation outcomes in preparation for a large, hybrid effectiveness- implementation trial to evaluate the refined criteria, and identifying key barriers to prehospital care of injured children to inform future adaptations and implementation strategies. During this award, I will obtain the training, mentorship, and experience in large-scale data analytics, predictive modeling, and D&I science necessary to become an independent health services researcher focused on improving emergency care for children.

项目概要 意外伤害是美国儿童死亡的主要原因。多项研究 当严重受伤的儿童被送往高层（1 级和 2 级）时，死亡率降低 和指定的儿科创伤中心，与低级别（3级或更高）和非创伤中心相比 中心。现场创伤分诊旨在识别需要高水平创伤中心资源的患者，95% 美国外科医生学会创伤委员会设定的敏感性和 65% 特异性目标 （阿斯科特）。 ACSCOT 和疾病控制与预防中心 (CDC) 发布现场分类 标准，被全国紧急医疗服务 (EMS) 机构广泛使用。这些标准是 通过主要针对成人的专家共识制定和更新，并已被证明未分类 严重受伤的儿童，据报告敏感性低至 65%。在 2020 年的系统评价中，儿科 创伤协会研究委员会表示，支持现场分类标准的数据“很少且低” 质量”，特别呼吁进行新的研究来建立单独的标准和标准组合，以 确定受伤儿童应被送往何处。虽然需要完善的儿科现场分诊标准 很明显，由于缺乏大规模、相互关联的院前和结果数据，进展受到限制 实施失败，包括生理测量缺失和不准确（例如血压和血压） 精神状态），以及过度依赖提供者的判断作为创伤中心需求的唯一决定因素。到 为了解决这些差距并改善受伤儿童的院前分诊，我们将进行描述性的 使用 AHRQ 医疗保健成本和利用率 (HCUP) 数据库对 7 个州的儿童分类不足进行分析， 使用基于人群的强大数据集的预测模型导出并验证精细的儿科现场分诊 包含来自洛杉矶县的院前和结果数据，并进行混合方法研究 评估城市环境管理体系中细化标准的实施结果。这个建议直接 解决 AHRQ 优先人群，包括儿科、少数民族、农村和低收入人群，并直接 响应 AHRQ 研究重点，通过识别潜在危害来改善医疗保健患者的安全 分类不足和差异，设计和评估干预措施以提高患者安全，以及 利用数据（包括 HCUP 数据库）来提高医疗保健质量和患者治疗效果。成功的 这项工作的完成将通过描述准确领域对健康的潜在影响来推进这一研究领域 分类，确定初步实施结果，为大规模的混合有效性做好准备- 实施试验以评估细化标准，并确定伤员院前救护的主要障碍 儿童为未来的调整和实施策略提供信息。在此期间，我将获得培训， 大规模数据分析、预测建模和 D&I 科学方面的指导和经验 成为一名独立的卫生服务研究员，专注于改善儿童的紧急护理。