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: 10319306
• 负责人: Andrew Gostine
• 金额: $ 83.78万
• 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/10319306
• 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; automated algorithm; base; care delivery; cost; digital; economic impact; experience; field study; improved; instrument; intelligent algorithm; 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。 在此环境中提高信息交换的准确性、速度和粒度， 结果、安全性、满意度和获得护理的机会。此外，提高效率可以产生显著的积极影响 经济影响，对所有医院都有重要意义。因此，手动文档的自动化和 任务协调可以提高生产力、安全性和收益性，以及临床医生的工作满意度。 白板协调器（WC）平台通过人工智能（AI）解决了这些市场挑战 驱动的OR工作流和资源管理。该平台部署在医院的虚拟服务器上， 本地网络。它与现有的电子病历（EMR）进行通信，导入当天的手术 时间表和分配的资源。一旦手术室工作流程开始，传感器和摄像头的智能网络 使用机器视觉算法记录病人、设备和供给的位置和时间。作为临床 活动开始时，软件会自动通过文本和分页提醒所有利益相关者重要事件， 协调临床流程。信息还通过数字显示器传播给所有利益攸关方 位置，如手术室、术前等待、麻醉后监护室、无菌供应、高流量走廊， 还有休息室考虑到外科手术的不可预测性，这种自动化的信息反馈 确保所有提供者都能轻松获得信息，使所有利益相关者能够独立但并行地同步 工作流程。智能传感器网络的摄像头和机器视觉算法自动检测和 更新资源的可用性和位置。该软件自动化现有的手动物流文件。 最后，WC以有针对性的方式快速传播详细信息（即，向特定的外科医生、护士， 技术员、清洁工等）以消除警报疲劳并提高生产力。 该项目包括四个主要目标。首先，第一阶段原型平台将得到增强，增加新功能 全面支持所有OR利益相关者的用户工作流程和效率。有针对性的更新将集中在 连接的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，人工智能套件将大幅更新，采用基于 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 库存管理和资源规划模拟工具箱。一旦所有平台更新完成， 经过技术验证和验证，支持基础设施和生产生态系统将扩展到 支持商业发行。这包括正式的质量职能、运营、支持和试运行/生产 环境.白板协调器平台和生产环境将根据质量进行验证 系统要求，然后部署在一个大规模的现场研究，以记录或有效性和实用性。