Validation and Implementation of Clinical Decision Support for Managing Children with Mild Head Injuries and Intracranial Injury

项目概要/摘要 轻度创伤性脑损伤（mTBI）是儿童的主要健康问题，导致约60万例 美国每年的急诊量。然而，有有限的证据表明， 管理14%的mTBI儿童，这些儿童在计算机断层扫描上发现了颅内损伤 显像对这些患者进行准确的风险分层至关重要， 临床关注和重症监护室（ICU）监测高危儿童，同时避免心理 与可避免的ICU入院相关的危害和大量资源利用。若干条证据 这表明目前基于医生完形的实践不是基于证据的，可能会使一些儿童处于危险之中， 这是一种伤害，与可避免的ICU入院率高有关。为了解决这一证据缺口， 申请人Jacob Greenberg博士最近利用大型多中心数据集进行开发和内部验证 儿童颅内损伤决策辅助（CHIIDA）评分，以分层神经功能下降的风险， 患者然而，自发采用风险模型是罕见的，反映了缺乏外部验证和重点 执行研究。认识到这些挑战，本申请提出了一种混合有效性- 使用现代多中心数据集和研究对CHIIDA评分进行外部验证的实施研究 将其应用到电子健康记录中。这个为期两年的F32博士后奖学金将追求这些 通过以下具体目标实现目标：1）外部验证CHIIDA管理儿童的模式 2a）定义实施电子临床的社会技术背景 mTBI和颅内损伤儿童护理中的决策支持;以及2b）采用以人为本的设计 开发和评估用于mTBI儿童风险分层的原型电子临床决策支持工具 和颅内损伤 这项研究支持卫生保健研究和质量机构（AHRQ）的使命， 将可用的、基于证据的临床决策支持纳入电子健康记录，以提高安全性， 医疗服务质量。与这一目标相一致，这项研究的结果最终将导致一个集群- 基于CHIIDA模型的电子临床决策支持的随机试验。同时对 拟议的培训计划将为申请人提供定性研究方法方面的宝贵技能， 实施科学、生物医学信息学和风险模型验证。因此，这位F32博士后 奖学金将支持申请人的目标，成为一个独立的卫生服务研究人员致力于 制定和实施以证据为基础的计划，以提高医疗保健安全和质量。

PROJECT SUMMARY/ABSTRACT Mild traumatic brain injury (mTBI) is a major health problem in children, leading to approximately 600,000 emergency department visits each year in the United States. However, there is limited evidence guiding the management of the 14% of children with mTBI that have intracranial injury identified on computed tomography imaging. Accurate risk stratification of these patients is of paramount importance to ensure appropriately close clinical attention and intensive care unit (ICU) monitoring for high-risk children, while avoiding the psychological harm and substantial resource utilization associated with avoidable ICU admission. Several lines of evidence suggest that current practice based on physician gestalt is not evidence-based, may place some children at risk of harm, and is associated with high rates of avoidable ICU admission. To address this evidence gap, the Applicant, Dr. Jacob Greenberg, recently utilized a large multicenter dataset to develop and internally validate the Children's Intracranial Injury Decision Aid (CHIIDA) score to stratify the risk of neurological decline in these patients. However, spontaneous uptake of risk models is rare, reflecting a lack of external validation and focused implementation studies. Recognizing these challenges, this application proposes a hybrid effectiveness- implementation study to both externally validate the CHIIDA score using a modern multicenter dataset and study its implementation into the electronic health record. This two-year F32 postdoctoral fellowship will pursue these objectives through the following specific aims: 1) externally validate the CHIIDA model for managing children with mTBI and intracranial injury; 2a) define the sociotechnical context for implementing electronic clinical decision support in the care of children with mTBI and intracranial injury; and 2b) employ human-centered design to develop and evaluate a prototype electronic clinical decision support tool for risk-stratifying children with mTBI and intracranial injury. This study supports the Agency for Healthcare Research and Quality's (AHRQ) mission of implementing usable, evidence-based clinical decision support into the electronic health record to improve the safety and quality of healthcare delivery. Consistent with this goal, this study's results will ultimately lead to a cluster- randomized trial of electronic clinical decision support based on the CHIIDA model. At the same time, the proposed training plan will provide the Applicant with valuable skills in qualitative research methods, implementation science, biomedical informatics, and risk model validation. Consequently, this F32 postdoctoral fellowship will support the Applicant's goal of becoming an independent health services researcher committed to developing and implementing evidence-based programs to improve healthcare safety and quality.