Components of emergency department pediatric readiness associated with short- and long-term survival among children: a mixed methods evaluation

与儿童短期和长期生存相关的急诊儿科准备的组成部分：混合方法评估

• 批准号: 10731344
• 负责人: Craig D. Newgard
• 金额: $ 66.49万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-10 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10731344
• 关键词: Accident and Emergency department; Acute; Address; Admission activity; Automobile Driving; Budgets; Caring; Cause of Death; Child; Child Care; Childhood; Childhood Injury; Complement; Critically ill children; Data; Data Science; Death Records; Emergency Care; Emergency Department evaluation; Emergency department visit; Emergency medical service; Equipment; Evaluation; Expert Opinion; General Hospitals; Grant; Guidelines; Health system; Hospital Mortality; Hospitalized Child; Hospitals; Human Resources; Injury; Institute of Medicine (U.S.); Interview; Link; Machine Learning; Measures; Medical; Methods; National Health Policy; National Institute of Child Health and Human Development; Outcome; Outcome Measure; Participant; Patients; Policies; Process; Public Health; Qualitative Methods; R24; Readiness; Reporting; Research Design; Research Infrastructure; Resources; Safety; Sampling; Structure; Translating; Trauma; Triage; United States Health Resources and Services Administration; Vital Statistics; care coordination; care systems; child services; clinical practice; cohort; design; hospital organization; improved; informant; machine learning method; mortality; multidisciplinary; novel; pediatric department; pediatric emergency; preventable death; programs; public health priorities; rural setting; survival prediction; trauma care; trauma centers

Proposed Approach: We will use a mixed methods study design to identify the components of emergency department (ED) pediatric readiness most predictive of short- and long-term survival among children. This project will help EDs prioritize implementation of ED readiness to save pediatric lives. We will use existing research infrastructure, data science methods, the ability to follow children to one year, novel analytics, and an interdisciplinary team to address this critical public health need. Importance: Injury and acute illness are the leading causes of death in children. We have recently shown that high ED pediatric readiness in US trauma centers and general hospitals is independently associated with improved survival, but the components of ED readiness driving survival are unknown. It is also unclear whether other organizational factors or ED processes of care improve survival among children. Answers to these questions will guide EDs in prioritizing the implementation of ED readiness, especially in smaller hospitals and rural settings with limited resources and budgets. This project is designed to inform the national trauma center verification criteria, the national field triage guidelines, the National Pediatric Readiness Project, and the Emergency Medical Services for Children program. Objectives: There are three specific aims: Specific Aim 1: We will build two multi-state cohorts of children receiving emergency care and use machine learning to identify the components of ED pediatric readiness predictive of short- and long-term survival. Specific Aim 2. Empirically develop a global measure of ED pediatric readiness and compare it to the weighted Pediatric Readiness Score for predicting short- and long-term survival in children. Specific Aim 3: Use a positive deviance approach to identify ED pediatric readiness factors and processes of care associated with improved survival among children receiving emergency care. Study Design & Setting: We will build two cohorts of children using emergency services from 1/1/2018 to 12/31/2022 in 928 EDs in 11 states (ED cohort) and 678 trauma centers in 50 states (Trauma cohort). We will link state vital statistics death records to the cohorts to track outcomes to one year and assess 152 unique components of ED readiness using machine learning methods. We will also conduct 150 interviews in 30 hospitals across the US using positive deviance methods as a complement to the quantitative analyses. Participants: Injured children 0–17 years using emergency services, including 15.6 million children with ED visits, 606,810 hospitalized children, and 264,865 children admitted to US trauma centers. Outcome measures: We will evaluate in-hospital mortality (primary) and 1-year mortality (secondary) at the patient-level. We will also evaluate the observed versus expected mortality at the ED-level to facilitate the positive deviance analysis.

建议的方法：我们将使用混合方法研究设计来确定 急诊科（ED）儿科准备最佳地预测短期和长期生存 孩子们。该项目将有助于ED STAIRSE级实施ED准备就绪，以挽救小儿生命。我们 将使用现有的研究基础架构，数据科学方法，跟随儿童到一年的能力， 新颖的分析和一个跨学科团队，以满足这一关键的公共卫生需求。 重要性：受伤和急性疾病是儿童死亡的主要原因。我们最近有 表明美国创伤中心和普通医院的高埃德儿科准备就绪 与提高的生存有关，但是ED阅读驱动生存的组成部分尚不清楚。它 还不清楚其他组织因素或ED护理过程是否可以改善 孩子们。这些问题的答案将指导ED在优先级实施ED准备就绪， 特别是在较小的医院和资源和预算有限的粗糙环境中。这个项目是 旨在告知国家创伤中心验证标准，国家野外三角指南， 国家儿科准备项目和儿童紧急医疗服务计划。 目标：有三个具体目标： 特定目标1：我们将建立两个接受急诊和使用机器的儿童的多状态人群 学会识别ED儿科准备的组成部分，可预测短期和长期生存的预测。 具体目的2。凭经验开发了ED儿科准备的全球量度，并将其与加权进行比较 小儿准备时间得分用于预测儿童短期和长期生存。 特定目的3：使用积极的偏差方法来识别ED儿科准备因素和过程 与接受急诊护理的儿童的生存改善相关的护理。 研究设计与环境：我们将使用2018年1月1日至 12/31/2022在11个州（ED队列）和678个创伤中心的928 ED中，在50个州（创伤队列）。我们将 将州生命统计的死亡记录与同类人群联系起来，以跟踪成果至一年，评估152独特 使用机器学习方法的ED准备成分。我们还将在30次进行150次访谈 美国各地的医院使用正偏差方法作为定量分析的完整。 参与者：使用紧急服务0-17岁的受伤儿童，包括1560万儿童 ED访问，606,810名住院儿童和264,865名儿童进入美国创伤中心。 结果指标：我们将评估院内死亡率（初级）和1年死亡率（次要） 在患者级别。我们还将评估ED级别的观察到的与预期死亡率 促进积极的偏差分析。