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.

抽象的手术后常见的不良后果包括死亡、呼吸衰竭和肾衰竭是一个严重的公共卫生挑战，可以通过综合的、协作健康信息技术解决方案提供 TECTONICS（手术室远程医疗控制塔：导航）的主要动机。信息、护理和安全）试验表明，多方面的远程医疗解决方案有可能促进动态评估风险、诊断负面患者轨迹并实施循证实践。我们的远程医疗解决方案（称为“远程医疗”）的最终结果将是提高患者的安全性和治疗结果。麻醉控制塔 (ACT)，包含来自电子设备的实时患者数据集成健康记录、临床医生决策支持、预测不良结果的机器学习算法，以及手术室（OR）的远程监控这种复杂的远程监控的概念。 OR 有点类似于繁忙机场的空中交通管制塔。试验将建立在一系列初步研究的基础上（由医疗保健研究和质量局资助，和国家科学基金会）已经 (i) 确定了原型的实用性和可用性远程医疗 ACT；(ii) 根据临床医生用户定制和增强的 ACT 决策支持警报反馈；(iii) 设计、开发和测试预测术后不良反应的机器学习算法结果；(iv) 确定对原型 ACT 进行现实世界随机试验的可行性。 TECTONICS 试验在逻辑上建立在这些初步研究的基础上，目的 1 是表明我们可以实施。并维持集成的 ACT 系统，作为其中的一部分，我们将迭代评估我们机器的准确性。学习算法并对其进行修改，以提高实时预测患者何时处于高风险的能力目标 2 是了解 ACT 系统如何影响’ （麻醉师和注册护士麻醉师 [CRNA]）思维、决策和行为。这种理解将帮助我们增强 ACT 系统，改进 ACT 和 OR，并改善麻醉师和 CRNA 之间的协作互动。目标 3 是开展一项研究。我们将评估 ACT 系统对手术室护理质量的影响，以及临床结果，如术中意识、术后谵妄、肾功能衰竭、呼吸系统疾病失败和 30 天死亡率 TECTONICS 将是第一个实用且科学严谨的试验。手术室的远程医疗解决方案，并将告知将此类技术纳入其中的有用性手术患者的常规护理，包括资源不足的医疗机构，数百万人正在接受手术。每年进行一次手术，这种可行的技术应用可能标志着手术安全和质量的重大转变围手术期护理，并转化为巨大的社会收益。