A Mixed Reality Conscious Sedation Simulator for Learning to Manage Variability

用于学习管理变异性的混合现实意识镇静模拟器

• 批准号: 8113546
• 负责人: John Patrick Quarles
• 金额: $ 18.5万
• 依托单位: UNIVERSITY OF TEXAS SAN ANTONIO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-15 至 2013-03-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8113546
• 关键词: Address; Adverse event; Advisory Committees; Age; American; Apnea; Appearance; Area; Cessation of life; Characteristics; Childhood; Conscious Sedation; Decision Making; Dose; Drug Kinetics; Education; Effectiveness; Ethical Issues; Ethnic Origin; Event; Face; Feedback; Florida; Future; Goals; Health Sciences; Height; Human; Imagery; Injury; Interview; Learning; Lip structure; Manikins; Medical; Medical Education; Medical Students; Methods; Modeling; Neurologic; Outcome; Output; Pain Threshold; Patients; Pharmaceutical Preparations; Pharmacodynamics; Physiological; Pilot Projects; Process; Propofol; Race; Recording of previous events; Research; Sedation procedure; Simulate; Societies; Students; System; Technology; Texas; Time; Training; Training Programs; Training and Education; Universities; Ventilatory Depression; Virtual System; Weight; adverse outcome; base; drug sensitivity; experience; high risk; improved; lectures; minimal risk; models and simulation; patient safety; prevent; sedative; simulation; skills; tool; virtual; virtual reality

DESCRIPTION (provided by applicant): Inter-patient variability is a major contributing factor to adverse outcomes in conscious sedation procedures. For example, two patients of similar height, weight, and age may react very differently to the same sedative, resulting in over sedation or under sedation. In many of these cases, patients who are assessed to be at minimal risk are actually at high risk. Then, problems, such as unexpected respiratory depression, cause an adverse outcome, such as neurologic damage or death. Current training programs mainly train students through lectures and real world experience, which logistically cannot bring students to competency in an acceptable amount of time. To address this problem, this proposal aims to develop an immersive mixed reality (MR) based training simulator for educating students about variability in conscious sedation procedures. Approach: Specifically, the proposed simulation will augment a mannequin patient simulator with a simulation model of variability, an immersive virtual reality patient, and conceptual visualizations of the patient's internal processes. This mixed reality patient will not only offer a wider variety of hands-on experience through the incorporation of patient interviews (e.g., history taking), but it will additionally simulate a variety of external characteristics, such as race, weight, height, and age, and offer conceptual visualizations of highly variable internal characteristics, such as drug sensitivity. Based on these reconfigurable characteristics, the proposed MR-based simulator will give students hands-on experience with a wide variety of simulated patients in a short amount of time. Ultimately, the simulator aims to afford students a deeper understanding of how their procedural decisions can have variable effects on patients. Specific Aims: 1) develop a simulation model of patient variability in conscious sedation, 2) develop model-driven mixed reality patients and debriefing for a conscious sedation scenario, 3) pilot-study the learning effectiveness of the system and establish face validity. The goal of the proposed simulator is to provide a variety of hands-on experiences and feedback that will accelerate learning, enhance decision making skills, and enable students to more effectively manage variability in conscious sedation.

描述（由申请人提供）：患者之间的差异是有意识镇静过程中不良结果的主要促成因素。例如，两个身高、体重和年龄相似的患者对同一种镇静剂的反应可能非常不同，导致镇静过度或镇静不足。在许多这样的病例中，被评估为风险最小的患者实际上处于高风险之中。然后，问题，如意想不到的呼吸抑制，导致不良后果，如神经损伤或死亡。目前的培训计划主要是通过讲座和现实世界的经验来培养学生，从逻辑上讲，这无法在可接受的时间内使学生具备胜任能力。为了解决这个问题，本提案旨在开发一个基于沉浸式混合现实（MR）的训练模拟器，用于教育学生意识镇静过程的可变性。