Clinical Decision Support Tool to Assess Risk and Prevent Agitation Events

项目摘要/摘要 该奖项是一项为期四年的计划，旨在支持急诊医生Ambrose Wong，医学博士，MSED 向专注于传播和实施的独立研究生涯过渡 在一般的非精神科急诊环境中为精神健康危机提供服务。他的长期目标是 研究是为了改善与激越症状相关的安全性。到目前为止，王博士的培训主要集中在 急诊医学、定性方法和基于教育的干预。在一个共同导师的团队下 拥有生物统计学、精神科服务研究、健康信息学和临床试验实施方面的专业知识， 王博士将在预防和管理骚乱的前期工作的基础上，完成 以下培训目标：(1)获得临床预测建模方面的专业知识；(2)获得基础知识 预防、治疗和调查心理健康危机；(3)研究健康信息学及其发展 临床支持工具，以及(4)在临床试验中获得基本技能。该应用程序集成了正式的 通过有指导的研究活动进行课程作业和培训。 在美国，急性护理环境中的行为状况正在迅速上升，患者数量增加了50% 在过去的十年里，普通急诊科(ED)就诊于精神健康状况。激动人心， 定义为过度的精神运动活动导致暴力行为，通常是这些患者遭遇的一部分。 在普通急诊室每年发生的170万次激动发作中，83%与潜在的 严重的精神疾病。考虑到骚动的安全风险，临床医生通常使用身体束缚，这是 与高达37%的并发症风险有关，包括患者的创伤损伤甚至猝死。 因此，监管机构和专家强调早期风险评估和使用行为技术之前 就会出现骚动。然而，在紧急情况下，这些技术的实践和政策存在可变性。 这是由于缺乏关于预测需要先发制人的特定风险因素的知识。 在急诊室繁忙的环境中评估这些危险因素的干预和挑战。的目标是 该项目是开发和测试早期发现和处理，以减少事件与激荡工具(ED- Treat)，嵌入在电子健康记录中的临床决策支持系统，将指导临床医生 在早期风险评估和适当治疗下，精神健康患者容易发生躁动。我们会 首先，使用健康记录数据和我们团队的初步分析得出临床模型，预测 高危患者会出现烦躁不安，需要使用身体约束。接下来，我们将开发和完善ED- 通过临床医生和患者以用户为中心的设计技术进行治疗。最后，我们将进行一次试点 试验以测试ED治疗的可行性、保真度和床边可接受性。与NIMH的战略保持一致 在非专科环境中优先使用技术来改善精神卫生服务，这项研究将形成 为随后的全面临床试验检查ED-Treat对临床结果的影响奠定了基础。

PROJECT SUMMARY/ABSTRACT This award is a four-year plan to support Ambrose Wong, MD, MSEd, an emergency physician, in his transition towards an independent research career that focuses on dissemination and implementation of services for mental health crises in general, non-psychiatric emergency settings. The long-term goal of his research is to improve safety related to symptoms of agitation. To date, Dr. Wong's training has focused on emergency medicine, qualitative methods, and education-based interventions. Under a team of co-mentors with expertise in biostatistics, psychiatric services research, health informatics, and clinical trial implementation, Dr. Wong will build on his preliminary work on agitation prevention and management to accomplish the following training goals: (1) acquire expertise in clinical prediction modeling, (2) gain foundational knowledge in preventing, treating, and investigating mental health crises, (3) study health informatics and development of clinical support tools, and (4) obtain fundamental skills in clinical trials. The application integrates formal coursework and training through mentored research activities. Behavioral conditions in acute care settings are rapidly rising in the U.S., with a 50% increase in number of general emergency department (ED) visits for mental health conditions over the past decade. Agitation, defined as excessive psychomotor activity leading to violent behavior, is often part of these patient encounters. Of the 1.7 million agitation episodes occurring annually in general EDs, 83% are associated with an underlying serious mental illness. Given the safety risks of agitation, clinicians commonly use physical restraint, which are associated with up to 37% risk of complications including traumatic injuries and even sudden death in patients. Thus, regulatory bodies and experts emphasize early risk assessment and use of behavioral techniques before agitation occurs. However, variability in practice and policy of these techniques exists in emergency settings. This is due to lack of knowledge regarding specific risk factors that predict the need for pre-emptive intervention and challenges in assessing these risk factors in the busy environment of an ED. The objective of this project is to develop and test the Early Detection and Treatment to Reduce Events with Agitation Tool (ED- TREAT), a clinical decision support system embedded in the electronic health record that will guide clinicians in early risk assessment and appropriate treatment of mental health patients likely to develop agitation. We will first derive a clinical model using health record data and preliminary analyses by our team that predicts which at-risk patients will develop agitation and require use of physical restraint. Next, we will develop and refine ED- TREAT through user-centered design techniques with clinicians and patients. Finally, we will conduct a pilot trial to test the feasibility, fidelity, and bedside acceptability of ED-TREAT. Aligned with NIMH's strategic priorities to use technology for improving mental health delivery in non-specialty settings, this study will form the basis for a subsequent full-scale clinical trial to examine ED-TREAT's effect on clinical outcomes.