TECTONICS (Telemedicine Control Tower for the OR: Navigating Information, Care and Safety) trial

TECTONICS（手术室远程医疗控制塔：导航信息、护理和安全）试验

基本信息

批准号：
10378109
负责人：
Michael Simon Avidan
金额：
$ 64.5万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-15 至 2024-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10378109
关键词：
Address Adherence Affect Air Algorithms Anesthesia procedures Anesthesiology Anesthetics Area Awareness Behavior Caring Certified registered nurse anesthetist Cessation of life Clinical Clinical Trials Cognitive Collaborations Computer software Consent Custom Data Data Science Decision Making Delirium Diagnosis Effectiveness Electronic Health Record Enabling Factors Engineering Evidence based practice Failure Feedback Fostering Foundations Funding Funding Agency Future Goals Health Healthcare Human Informatics Institutes Institution Kidney Failure Machine Learning Measures Motivation Operating Rooms Operative Surgical Procedures Outcome Patient risk Patient-Focused Outcomes Patients Perioperative Perioperative Care Perioperative complication Postoperative Period Process Public Health Quality of Care Randomized Resources Respiratory Failure Risk Risk Assessment Safety Science Series Signal Transduction System Technology Telemedicine Testing Thinking Time Training Translating United States Agency for Healthcare Research and Quality Update adverse outcome algorithm development base clinical decision support clinically relevant cognitive process computer science data integration design evidence base experience health care settings health information technology high risk implementation framework improved improved outcome innovation machine learning algorithm modifiable risk mortality neural network novel patient oriented postoperative delirium prediction algorithm prevent prototype randomized trial remote monitoring remote patient monitoring risk prediction routine care safety outcomes support tools surgery outcome usability user-friendly waiver

项目摘要

Abstract Adverse outcomes, including death, respiratory failure and renal failure, are common after surgery, and represent a serious public health challenge. Such adverse outcomes can be mitigated through integrated, collaborative health information technology solutions that provide clinicians cognitive and computational support. The chief motivation for the TECTONICS (Telemedicine Control Tower for the OR: Navigating Information, Care and Safety) trial is that a multi-faceted telemedicine solution has the potential to facilitate the dynamic assessment of risk, diagnose negative patient trajectories, and implement evidence-based practices. The net result for patients would be improved safety and outcomes. Our telemedicine solution, called the Anesthesiology Control Tower (ACT), encompasses real-time patient data integration from the electronic health record, clinician decision support, machine learning algorithms that predict adverse outcomes, and remote monitoring for the operating room (OR). This conceptualization of sophisticated remote monitoring for the OR is somewhat analogous to an air traffic control tower for a busy airport. The innovative TECTONICS trial will build on a series of preliminary studies (funded by the Agency for Healthcare Research and Quality, and the National Science Foundation) that have (i) established the usefulness and usability of a prototype telemedicine ACT; (ii) customized and enhanced decision-support alerts for the ACT, based on clinician user feedback; (iii) designed, developed, and tested machine learning algorithms that predict adverse postoperative outcomes; and (iv) established the feasibility of conducing a real-world randomized trial of the prototype ACT. The TECTONICS trial builds logically on these preliminary studies. Aim 1 is to show that we can implement and sustain an integrated ACT system. As part of this, we will iteratively assess the accuracy of our machine learning algorithms and modify them to improve their ability to predict in real time when patients are at high risk for experiencing negative outcomes. Aim 2 is to understand how the ACT system affects clinicians’ (anesthesiologists and certified registered nurse anesthetists [CRNAs]) thinking, decision-making and behavior. This understanding will help us to enhance the ACT system, improve workflow processes in the ACT and in the OR, and improve collaborative interactions between anesthesiologists and CRNAs. Aim 3 is to conduct a rigorous clinical trial. We will evaluate the impact of the ACT system on the quality of care in the OR, and clinical outcomes such as intraoperative awareness, and postoperative delirium, renal failure, respiratory failure, and 30-day mortality. TECTONICS will be the first practical and scientifically rigorous trial of a telemedicine solution for the operating room, and will inform the usefulness of incorporating such technology in routine care of surgical patients, including under-resourced healthcare settings. With many millions undergoing surgery yearly, this feasible application of technology could signal a major shift in the safety and quality of perioperative care, and translate into substantial societal gain.

抽象的不良后果，包括死亡，呼吸衰竭和肾衰竭，在手术后常见，并且代表了严重的公共卫生挑战。可以通过综合，可以减轻这种不良结果，协作健康信息技术解决方案，为临床医生提供认知和计算支持。构造的主要动机（远程医疗控制塔的OR：导航信息，护理和安全性）试验是，多面远程医疗解决方案有可能促进动态评估风险，诊断性阴性患者轨迹和实施基于证据的做法。患者的最终结果将改善安全性和结果。我们的远程医疗解决方案称为麻醉控制塔（ACT），包括电子的实时患者数据集成健康记录，临床决策支持，预测不良结果的机器学习算法以及远程监视手术室（OR）。对复杂远程监视的这种概念化 OR有点类似于繁忙机场的空中交通管制塔。创新的构造学试验将基于一系列初步研究（由医疗保健研究和质量机构资助，和国家科学基金会（i）建立了原型的实用性和可用性远程医疗法；（ii）根据临床用户的定制和增强该法案的决策支持警报反馈; （iii）设计，开发和测试的机器学习算法可以预测术后不良的结果；（iv）确定了对原型法进行真实世界随机试验的可行性。构造试验以这些初步研究为基础。目标1是表明我们可以实施并维持一个综合行动系统。为此，我们将迭代评估机器的准确性学习算法并修改它们，以提高他们实时预测患者高风险的能力用于经历负面结果。目标2是了解该行为系统如何影响临床医生（麻醉师和经认证的注册护士麻醉师[CRNA]）思考，决策和行为。这种理解将有助于我们增强ACT系统，改善该法案中的工作流程流程或者，改善麻醉师和CRNA之间的协作互动。目标3是进行严格的临床试验。我们将评估ACT系统对OR护理质量的影响，以及临床结果，例如术中意识和术后del妄，肾衰竭，呼吸系统失败和30天死亡率。构造学将是第一个实用和科学严格的试验手术室的远程医疗解决方案，并将告知将这种技术纳入其中的有用性外科患者的常规护理，包括资源不足的医疗机构。数百万正在进行每年手术，这种可行的技术应用可能表明安全性和质量的重大转变围手术期护理，并转化为实质性的社会利益。