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A ROBOT-ASSISTED PERFUSION SYSTEM TO IMPROVE PATIENT SAFETY IN THE CARDIAC OPERATING ROOM

机器人辅助灌注系统可提高心脏手术室患者的安全

基本信息

批准号：
10668333
负责人：
Roger Daglius Dias
金额：
$ 68.59万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10668333
关键词：
Adopted Adult Adverse event Algorithms Anesthesia procedures Artificial Intelligence Awareness Belief Cardiac Cardiac Surgery procedures Cardiopulmonary Bypass Childhood Clinical Clinical Decision Support Systems Cognition Cognitive Communication Complex Computers Cues Data Decision Making Decision Support Systems Dedications Deterioration Digital biomarker Discipline of Nursing Electrocardiogram Electroencephalography Engineering Environment Expert Systems Fatigue Future Goals Health Personnel Heterogeneity Hospitals Hour Human Impairment Incidence Interruption Intuition Knowledge Laboratories Learning Libraries Literature Measures Medical Medical Errors Modeling Nurses Operating Rooms Operative Surgical Procedures Outcome Patient Care Patients Performance Perfusion Phase Physiological Policies Probability Procedures Process Protocols documentation Provider Reporting Rewards Risk Robot Robotics Safety Serious Adverse Event Standardization Stress System Techniques Technology Time Training Trust Uncertainty Variant Ventilator Work Workload apprenticeship biomarker performance clinical practice cognitive load computational intelligence design distraction experience human error human-in-the-loop improved interoperability knowledge base medical schools non-verbal novel open source operation patient safety prevent robot assistance simulation skills standardized care usability verbal virtual surgery visual tracking willingness

项目摘要

PROJECT SUMMARY / ABSTRACT The vast majority of pediatric and adult cardiac surgery procedures worldwide involve the use of cardiopulmonary bypass with a dedicated and highly customized perfusion system. Cardiac surgery procedures are complex and entail safety-critical activities, requiring continuous coordination between four subteams: perfusion, surgical, nursing and anesthesia. This environment demands outstanding technical and non-technical skills (e.g. teamwork, communication and situational awareness). Over the past few decades, technological advancements have improved the safety and efficiency of the perfusion system, however, despite substantial progress, recent studies continue to report a high incidence of preventable intraoperative adverse events among cardiac surgery patients. The perfusion system, in particular, relies heavily on the expertise and skills of the perfusionist, and there is currently no computational intelligent system to support perfusionists' optimal decision-making during the critical phase of cardiopulmonary bypass. In this proposal, we seek to develop a data-driven approach to learn from expert perfusionists how to achieve optimal outcomes for cardiac surgery patients. Rather than attempt to engineer a solution, we propose to develop a computer-based apprentice that can learn from high-quality demonstrations of perfusionist actions to infer gold-standard patient care. Our goal is to develop and evaluate a Robot-Assisted Perfusion System (RAPS) that can be integrated into the cardiac surgery workflow as a non-human teammate. The RAPS will support the perfusion team in a way that perfusionists still will keep control of the perfusion system (i.e. human- in-the-loop), but cognitively supported and guided by the RAPS.

项目总结/摘要全世界绝大多数小儿和成人心脏外科手术都涉及使用使用专用和高度定制的灌注系统进行心肺分流术。心脏手术程序复杂，涉及安全关键活动，需要四个部门之间的持续协调，分组：灌注、手术、护理和麻醉。这种环境需要出色的技术和非技术技能（如团队合作、沟通和态势感知）。在过去的几十年里，技术进步提高了安全性和效率，然而，尽管取得了实质性进展，最近的研究继续报告高发生率的灌注系统，心脏手术患者中可预防的术中不良事件。特别是灌注系统，在很大程度上依赖于灌注师的专业知识和技能，目前还没有计算智能系统，以支持灌注师的最佳决策，在心肺转流的关键阶段。在这个建议中，我们寻求开发一种数据驱动的方法，从专家灌注师那里学习如何实现心脏手术患者的最佳结局。与其试图设计一个解决方案，我们建议开发一个基于计算机的学徒，可以从高质量的灌注动作演示中学习，推断黄金标准的病人护理。我们的目标是开发和评估机器人辅助灌注系统（RAPS），其可以作为非人类队友集成到心脏手术工作流程中。RAPS将以灌注师仍然保持灌注系统的控制的方式支持灌注团队（即，人- 在环），但认知支持和指导的RAPS。