Digital Innovation, Simulation, and Collaboration using Virtual Environment Realities (DISCOVER) for Pediatric Diagnostic

使用虚拟环境现实 (DISCOVER) 进行儿科诊断的数字创新、模拟和协作

• 批准号: 10769298
• 负责人: Maya L Dewan
• 金额: $ 50万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10769298
• 关键词: Digital; Innovation; Simulation; Collaboration; using

Project Summary More than a third of pediatric adverse events have been attributed to diagnostic error—the failure to establish an accurate and timely explanation of a child’s health problem. Within the pediatric intensive care unit (PICU), a high-stakes, complex, team-driven environment, diagnostic error rates vary between 8% and 25%. To improve diagnostic accuracy, clinical decision support (CDS) tools, including artificial intelligence and machine learning algorithms, have been developed but have failed to be adopted within the PICU. Implementation of CDS into an active high-risk clinical context without a comprehensive understanding of how providers and staff interface with the system can lead to patient safety consequences. These consequences can include disrupted workflows, alert fatigue, and inaccurate documentation that can lead to direct patient harm. We propose leveraging a currently built highly realistic immersive virtual reality PICU clinical environment to assess implementation strategies on clinician acceptance of CDS tools to improve diagnostic excellence within a patient safety learning lab. We will evaluate three aims using a systems-engineering approach combining the expertise of LiveWell, an award-winning design collaborative with user-centered design and human factors expertise, with the clinical knowledge, implementation science expertise, and world-renowned virtual simulation program of Cincinnati Children’s Hospital Medical Center (CCHMC). We will: redesign how clinicians interface with CDS tools for diagnosis-intensive events within the pediatric critical care environment including admission and clinical deterioration; develop and implement design-informed CDS tools for diagnosis and to evaluate their appropriateness/acceptability and impact on diagnostic uncertainty, accuracy, and timeliness within a digital twin immersive virtual reality simulation; and establish best practice guidance for implementation of CDS tools in the critical care environment to improve diagnostic excellence. Outcomes will include 1) appropriateness, acceptability, and adoption of design informed CDS tools; 2) impact on diagnostic accuracy and timeliness in the simulated clinical environment; and 3) a proactive implementation plan for the integration of design informed CDS tools to improve diagnostic excellence into the critical care environment.

项目摘要 超过三分之一的儿科不良事件被归因于诊断错误-失败 建立对儿童健康问题的准确和及时的解释。在儿科 重症监护病房(PICU)，一个高风险、复杂、团队驱动的环境，诊断错误 房价从8%到25%不等。为了提高诊断的准确性，临床决策支持(CDS) 包括人工智能和机器学习算法在内的工具已经开发出来，但 都未能在PICU内被采纳。CDS在活跃的高危临床中的实施 如果不全面了解提供商和员工如何与 系统会导致患者的安全后果。这些后果可能包括中断 工作流程、警觉疲劳和不准确的文档可能会导致直接伤害患者。我们 建议利用目前构建的高度逼真的沉浸式虚拟现实PICU临床 评估临床医生接受CDS工具以改进的实施策略的环境 在患者安全学习实验室中实现卓越的诊断。我们将评估三个目标使用 结合获奖设计LiveWell专业知识的系统工程方法 与以用户为中心的设计和人为因素专业知识、临床知识、 辛辛那提的实施科学专业知识和世界知名的虚拟仿真计划 儿童医院医学中心。我们将：重新设计临床医生与CDS的交互方式 儿科重症监护环境中诊断密集型事件的工具包括 入院和临床恶化；开发和实施设计知情的CDS工具 并评估其适当性/可接受性以及对诊断的影响 数字孪生沉浸式虚拟现实模拟中的不确定性、准确性和及时性；以及 为在重症监护环境中实施CDS工具建立最佳实践指南 以提高诊断的精确性。结果将包括1)适当性、可接受性和 采用设计知情的CDS工具；2)对诊断准确性和及时性的影响 模拟临床环境；以及3)主动实施计划，整合 设计知情的CDS工具，以提高重症监护环境中的诊断能力。