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 三分之一以上的小儿不良事件归因于诊断错误 - 失败 建立对孩子的健康问题的准确，及时的解释。在小儿内 重症监护病房（PICU），高风险，复杂的，团队驱动的环境，诊断错误 利率在8％至25％之间。为了提高诊断准确性，临床决策支持（CD） 已经开发了包括人工智能和机器学习算法在内的工具，但是 在PICU中未能采用。将CD实施到活跃的高风险临床中 上下文没有全面了解提供者和员工如何与 系统会导致患者的安全后果。这些后果可能包括破坏 工作流程，警报疲劳和不准确的文件，可能导致直接患者伤害。我们 利用当前建造的高度现实的沉浸式虚拟现实PICU临床的提案 评估CDS工具临床接受策略以改进的环境 患者安全学习实验室内的诊断卓越。我们将使用一个 系统工程方法结合了屡获殊荣的设计Livewell的专业知识 与以用户为中心的设计和人为因素专业知识的合作，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模拟计划 儿童医院医疗中心（CCHMC）。我们将：重新设计临床医生如何与CD互动 小儿重症监护环境中诊断密集型事件的工具 入学和临床定义；开发和实施设计信息的CDS工具 诊断并评估其适当性/可接受性和对诊断的影响 数字双胞胎沉浸式虚拟现实模拟中的不确定性，准确性和及时性；和 在重症监护环境中建立实施CDS工具的最佳实践指南 提高卓越诊断。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； 3）积极的实施计划 设计了知情的CDS工具，以改善对重症监护环境的诊断卓越。