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 (OR) 护理患者需要一套复杂的资源、人员和后勤保障。 提高此环境中信息交换的准确性、速度和粒度会显着影响 此外，提高效率可以产生显着的积极作用。 经济影响，对所有医院都有重要影响，因此，手动文档和自动化。 任务协调可以提高生产力、安全性和盈利能力，以及信徒的工作满意度。 Whiteboard Coordinator (WC) 平台通过人工智能 (AI) 解决这些市场挑战 该平台部署在医院内的虚拟服务器上。 它与现有的电子病历（EMR）通信以导入当天的手术。 一旦手术室工作流程开始，传感器和摄像机的智能网络就会出现。 使用机器视觉算法记录患者、设备和用品的位置和时间。 活动开始后，软件会通过文本和寻呼自动提醒所有利益相关者重要事件 协调临床流程也在数字显示器上向利益相关者传播。 地点，例如手术室、术前等待室、麻醉后护理室、无菌供应、人流量大的走廊， 鉴于外科手术的不可预测性，这种自动信息馈送。 确保所有提供商轻松了解情况，允许所有利益相关者独立但并行地同步 相机和机器视觉算法的智能传感器网络自动检测和处理。 该软件可自动更新资源的可用性和位置。 最后，WC 有针对性地快速传播详细信息（即向特定的外科医生、护士、 技术人员、清洁人员等）消除报警疲劳并提高生产力。 该项目包括四个主要目标，首先，第一阶段原型平台将通过新功能得到增强。 全面支持所有手术室利益相关者的用户工作流程和效率。有针对性的更新将重点关注。 连接的数据域和跨平台集成、用户界面工作流程和自动化报告，以及 其次，人工智能套件将通过基于其构建的新颖工具进行重大更新。 第一阶段框架包括检测新型手术类型和事件、检测手术用品和 所有平台更新完成后，即可进行库存管理和资源规划模拟工具箱。 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至 支持商业发布。这包括正式的质量功能、运营、支持和登台/生产。 Whiteboard Coordinator 平台和生产环境将根据质量进行验证。 系统需求，然后部署在大规模现场研究中以记录 OR 的有效性和实用性。