Mixed-reality Simulation Training for Pediatric Airway Management Procedures
Mixed-reality Simulation Training for Pediatric Airway Management Procedures
批准号:
9249670
负责人:
ROBERT J LEVINE
金额:
$73.66万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-01 至 2020-03-31
关键词:
AdoptionAnatomyAugmented RealityCessation of lifeChildhoodCommunity Health EducationCritiquesDataDevicesEquipmentEvaluationHealth SciencesImageryIntubationLifeLocationMaintenanceManikinsMedicalMedical EducationMedical StudentsMedical centerMethodologyModelingModernizationMonitorMultimediaNeonatalNeonatal Intensive Care UnitsPathologicPatientsPhasePhysiciansPhysiologicalProceduresRandomized Controlled TrialsSavingsStreamSystemTechnologyTestingTexasTimeTrainingUniversitiesVisualbasebrief interventioncognitive skillcognitive testingimprovedneonatal patientoptical sensorpediatric patientspost interventionprenatalprospectiveprototypepublic health relevancesimulationskill acquisitionskillssuccesssynergismusabilityvisual feedback
中文摘要
描述(由申请人提供):儿科和新生儿呼吸道管理技能是救命的,很难掌握,而且使用频率很低,使技能维护成为一个严重的挑战。例如,多项研究表明,儿童和新生儿的插管程序往往不到一半的时间是成功的,特别是在居民中。鉴于技能获得周期较长(尽管有现代模拟培训),需要新的培训方法。近年来,患者模拟器在医学教育界得到了广泛的采用。如果学员能够理解内部地标的位置,则这些模拟器的教学价值将显著提高,如
以及在训练过程中形象化身体的正常和病理状态。这将帮助受训者了解他们的行为与体内发生的事情之间的关系。ArchieMD建议开发一种儿科呼吸道混合现实医学模拟系统,将多媒体技术与人体模型相结合,使医疗训练师能够覆盖内部解剖。使用混合现实跟踪,ArchieMD的人体内部解剖的3D图像可以叠加在用户的视图上,在使用任务训练器人体模型的同时提供额外的3D教学信息。然后,生成的叠加视频流显示在宽屏监视器上。这在医学教育的视觉和实践部分之间提供了高度有效的协同作用。光学传感器允许在进行手术时将医疗设备与解剖模型和人体模型集成在一起。这导致了对患者的真实的解剖和生理表现。使用我们的第一阶段原型从21名医学生那里收集了试点数据。从基线到干预后,认知和技能评估在统计上有显著改善。对于认知评估,平均分数从56.5%提高到82.0%(p=0.001)。在技能评估方面,平均分从70.4%提高到94.2%(p=<;0.001),显示了这一一次性、相对短暂的干预带来的巨大影响。在第二阶段,我们将扩大儿科呼吸道混合现实训练器,以涵盖全方位的
该方案可用于解决产前和新生儿困难的呼吸道情况,并采用全方位的产前和新生儿适当的声门上/声门外呼吸道装置。该系统的教育价值将是
在一项随机对照试验中进行了评估,以评估与传统人体模型相比,混合现实医学生培训师平台提高程序技能的能力。
英文摘要
DESCRIPTION (provided by applicant): Pediatric and neonatal airway management skills are life-saving, difficult to master, and used infrequently enough to make skill maintenance a serious challenge. For example, multiple studies have shown that pediatric and neonatal intubation procedures are often successful less than half of the time, especially among residents. Given the long skill acquisition cycles (in spite of modern simulation training), new training methodologies are required. In recent years, there has widespread adoption of patient simulators in the medical education community. The didactic value of these simulators could be significantly improved if the trainee was able to understand the location of internal landmarks, as
well as visualize normal and pathological states of the body during training. This would help trainees understand the relationship between their actions and what is occurring in the body. ArchieMD proposes to develop a pediatric airway mixed reality medical simulation system to combine multimedia technologies with manikins to enable internal anatomy overlays on medical trainers. Using mixed reality tracking, ArchieMD's 3D imagery of the body's internal anatomy can be superimposed over the view of the user, providing additional 3D didactic information while using a task trainer manikin. The resulting overlayed video stream is then displayed on a widescreen monitor. This provides highly effective synergy between the visual and hands-on component of medical education. Optical sensors allow integration of the medical equipment with the anatomy models and the manikin while the procedures are being conducted. This results in a realistic anatomic and physiologic representation of the patient. Pilot data was collected from 21 medical students using our Phase I prototype. There were statistically significant improvements in cognitive and skills assessments from baseline to post- intervention. For the cognitive assessment, the mean scores improved from 56.5 percent to 82.0 percent (p= <0.001). For the skills assessment, the mean scores improved from 70.4 percent to 94.2 percent (p= <0.001) revealing a big impact from this one-time, relatively brief intervention. During Phase II, we will expand the pediatric airway mixed-reality trainer to cover a full range of
prenatal and neonatal difficult airway scenarios and incorporate a full range of prenatal and neonatal appropriate supraglottic/extraglottic airway devices. The system's didiactic value will be
evaluated in a randomized controlled trial to assess the ability of the Mixed Reality Medical Student Trainer Platform to improve procedure skills, as compared to traditional manikins.
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