Whiteboard Coordinator: Intelligent Sensor Network and Machine Learning toImprove Operating Room Outcomes and Efficiency

白板协调员：智能传感器网络和机器学习可提高手术室成果和效率

• 批准号: 10463847
• 负责人: Andrew Gostine
• 金额: $ 82.22万
• 依托单位: ARTISIGHT, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10463847
• 关键词: Algorithms; Anesthesia procedures; Artificial Intelligence; Attention; Automation; Beds; Caring; Clinical; Complex; Computer software; Computerized Medical Record; Data; Data Set; Day Surgery; Detection; Documentation; Economics; Ecosystem; Effectiveness; Ensure; Environment; Equipment; Equipment and Supplies; Equipment and supply inventories; Event; Fatigue; Feedback; Foundations; Funding Agency; Health Services Accessibility; Health system; Hospitals; Human Resources; Infrastructure; Insurance; Intelligence; Interruption; Job Satisfaction; Location; Logistics; Machine Learning; Manuals; Monitor; Nature; Nurses; Operating Rooms; Operative Surgical Procedures; Outcome; Patient Care; Patient-Focused Outcomes; Patients; Phase; Pilot Projects; Positioning Attribute; Procedures; Process; Production; Productivity; Provider; Regulation; Reporting; Resource Allocation; Resources; Safety; Schedule; Services; Small Business Innovation Research Grant; Speed; Staging; Sterility; Stream; Stress; Surgeon; System; Technology; Testing; Text; Time; Training; Underserved Population; Update; Validation; Visual; Voice; artificial intelligence algorithm; automated algorithm; base; care delivery; cost; digital; economic impact; experience; field study; improved; instrument; machine vision; novel; operation; patient safety; prototype; satisfaction; sensor; simulation; success; technology development; tool; usability; virtual

Caring for patients in the operating room (OR) requires a complex set of resources, personnel, and logistics. Improving the accuracy, speed, and granularity of information exchange in this environment significantly impacts outcomes, safety, satisfaction, & access to care. Additionally, increasing efficiency can have a significant positive economic impact, an important implication for all hospitals. Therefore, automation of manual documentation and task coordination can enhance productivity, safety, and profitability, as well as job satisfaction for clinicians. The Whiteboard Coordinator (WC) platform solves these market challenges through artificial intelligence (AI) driven OR workflows and resource management. The platform is deployed on a virtual server within a hospital’s local network. It communicates with the existing electronic medical record (EMR) to import the day’s surgery schedule and assigned resources. Once OR workflow begins, an intelligent network of sensors and cameras employing machine vision algorithms record locations and times of patients, equipment, and supplies. As clinical activities begin, the software automatically alerts all stakeholders of important events via text and paging to coordinate clinical processes. Information is also disseminated on digital displays throughout stakeholder locations, such as the OR, preoperative holding, post anesthesia care unit, sterile supply, high-traffic hallways, and break rooms. Given the unpredictable nature of surgical procedures, this automated information feed ensures all providers are effortlessly informed, allowing all stakeholders to synchronize independent, but parallel workflows. The intelligent sensor network of cameras and machine vision algorithms automatically detects and updates availability and location of resources. The software automates existing manual logistics documentation. Finally, WC rapidly disseminates detailed information in a targeted manner (i.e. to specific surgeons, nurses, technicians, janitorial staff, etc.) to eliminate alarm fatigue and enhance productivity. The project includes four main aims. First, the Phase I prototype platform will be enhanced with new features to fully support user workflow and efficiency across all OR stakeholders. Targeted updates will focus on connected data domains and cross platform integration, user interface workflows and automated reports, and voice command integration. Second, the AI suite will be significantly updated with novel tools that build upon the Phase I framework including detection of novel surgery types & events, detection of surgical supplies & inventory management, and a simulation toolbox for resource planning. Once all platform updates have been technically verified and validated, the supporting infrastructure and production ecosystem will be scaled to support commercial release. This includes formal quality functions, operations, support and staging/production environments. The Whiteboard Coordinator platform and production environment will be validated against quality system requirements, then deployed in a large-scale field study to document OR effectiveness and utility.

在手术室照顾病人需要一套复杂的资源、人员和后勤保障。 在此环境中提高信息交换的准确性、速度和粒度将产生重大影响 结果、安全性、满意度和获得护理的机会。此外，提高效率可以带来显著的积极影响 经济影响，这是对所有医院的重要影响。因此，手动文档的自动化和 任务协调可以提高临床医生的工作效率、安全性和盈利能力，以及工作满意度。 白板协调器(WC)平台通过人工智能(AI)解决了这些市场挑战 受驱动的OR工作流和资源管理。该平台部署在医院内部的虚拟服务器上 本地网络。它与现有的电子病历(EMR)通信，以导入当天的手术 安排和分配资源。一旦OR工作流程开始，由传感器和摄像头组成的智能网络 使用机器视觉算法记录患者、设备和补给的位置和时间。作为临床应用 活动开始时，该软件通过文本和寻呼向所有利益相关者自动提醒重要事件 协调临床流程。信息还通过数字显示器在所有利益相关者中传播 地点，如手术室、术前等待、麻醉后护理病房、无菌供应室、人流量大的走廊、 和休息室。考虑到手术过程的不可预测性，这种自动信息馈送 确保所有提供商毫不费力地得到通知，允许所有利益相关者独立但并行地进行同步 工作流程。由摄像机和机器视觉算法组成的智能传感器网络自动检测和 更新资源的可用性和位置。该软件使现有的人工物流文档自动化。 最后，WC以有针对性的方式迅速传播详细信息(即向特定外科医生、护士、 技术员、清洁工等)消除闹钟疲劳，提高生产效率。 该项目包括四个主要目标。首先，第一阶段原型平台将使用新功能进行增强 全面支持所有OR利益相关者的用户工作流程和效率。有针对性的更新将侧重于 互联数据域和跨平台集成、用户界面工作流和自动化报告，以及 语音命令集成。其次，AI套件将使用构建在以下基础上的新工具进行重大更新 第一阶段框架包括检测新的手术类型和事件、检测手术用品和 库存管理，以及用于资源规划的模拟工具箱。在所有平台更新完成后 经过技术验证和验证后，支持基础设施和生产生态系统将扩展到 支持商业发布。这包括正式的质量职能、运营、支持和准备/生产 环境。白板协调员平台和生产环境将根据质量进行验证 系统要求，然后部署在大规模实地研究中，以记录运营权的有效性和效用。