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

项目摘要/摘要 轻度创伤性脑损伤(MTBI)是儿童的主要健康问题，导致约60万人 在美国，每年都有急诊科就诊。然而，指导这一进程的证据有限 14%的儿童mTBI患者在CT检查中发现有颅内损伤 成像。对这些患者进行准确的风险分层是至关重要的，以确保适当的封闭 临床关注和重症监护病房(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。有几条证据 表明目前基于医生格式塔的做法没有证据，可能会将一些儿童置于危险之中 危害很大，而且与可避免的ICU入院率高有关。为了解决这一证据差距， 申请者雅各布·格林伯格博士最近利用大型多中心数据集开发和内部验证 儿童颅内损伤决策辅助(CHIIDA)评分对这些患者神经功能下降的风险进行分层 病人。然而，自发接受风险模型的情况很少见，这反映出缺乏外部验证和关注 实施研究。认识到这些挑战，该应用程序提出了一种混合效果- 使用现代多中心数据集外部验证CHIIDA评分的实施研究和研究 将其实施到电子健康记录中。这个为期两年的F32博士后奖学金将攻读以下课程 目标通过以下具体目标：1)外部验证CHIIDA儿童管理模式 2)确定实施电子临床的社会技术背景 2)采用以人为中心的设计，为儿童脑外伤和颅脑损伤的护理提供决策支持 多发性脑损伤危险分层儿童电子临床决策支持工具原型的开发与评价 和颅内损伤。 这项研究支持医疗研究和质量机构(AHRQ)实施 将可用的、基于证据的临床决策支持纳入电子健康记录，以提高安全性和 医疗保健服务的质量。与这一目标一致，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随机试验。同时， 拟议的培训计划将为申请者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 奖学金将支持申请者成为一名承诺的独立卫生服务研究人员的目标 开发和实施循证计划，以提高医疗保健的安全和质量。

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.