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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：
10184079
负责人：
Roger Daglius Dias
金额：
$ 84.19万
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：
2021
资助国家：
美国
起止时间：
2021-09-20 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10184079
关键词：
Adopted Adult Adverse event Algorithms Anesthesia procedures Artificial Intelligence Awareness Belief Cardiac Cardiac Surgery procedures Cardiopulmonary Bypass Childhood Clinical Cognition Cognitive Communication Complex Cues Custom Data Decision Making Deterioration Electrocardiogram Electroencephalography Engineering Ensure Environment Expert Systems Fatigue Future Goals Gold Health Personnel Heterogeneity Hospitals Hour Human Impairment Incidence Interruption Intuition Knowledge Laboratories Lead Learning Libraries Literature Measures Medical Errors Modeling Nurses Operating Rooms Operative Surgical Procedures Outcome Patient Care Patients Performance Perfusion Perioperative Nursing Phase Physiological Policies Probability Procedures Process Protocols documentation Provider Reporting Rewards Risk Robot Safety Serious Adverse Event Standardization Stress System Techniques Technology Time Training Trust Uncertainty Ventilator Work Workload apprenticeship biomarker performance clinical practice cognitive load computational intelligence design digital distraction experience human error human-in-the-loop improved interoperability knowledge base medical schools novel open source operation patient safety prevent robot assistance robotic system skills standardized care usability 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 robot 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.

项目摘要/摘要