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.

照顾手术室中的患者（OR）需要一组复杂的资源，人员和物流。 在这种环境下，提高信息交换的准确性，速度和粒度会显着影响 结果，安全，满意度和获得护理的机会。此外，提高效率可以具有显着的正面 经济影响，对所有医院的重要含义。因此，手动文档的自动化和 任务协调可以提高生产力，安全性和利润率，以及临床医生的工作满意度。 白板协调员（WC）平台通过人工智能（AI）解决了这些市场挑战 驱动或工作流程和资源管理。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）通信以进口当天的手术 安排和分配的资源。一旦开始或工作流程开始，传感器和相机的智能网络 采用机器视觉算法记录了患者，设备和用品的时间和时间。作为临床 活动开始，该软件会自动通过文本向所有利益相关者提醒重要事件，并向 协调临床过程。在整个利益相关者的数字显示上，信息也会传播 位置，例如术前持有，麻醉后护理单元，无菌供应，高流量走廊， 和休息室。鉴于外科手术程序的不可预测性质，此自动化信息为 确保所有提供商都毫不费力地告知所有提供商，从而使所有利益相关者都可以独立同步，但平行 工作流程。相机和机器视觉算法的智能传感器网络自动检测和 更新可用性和资源位置。该软件可自动化现有的手动登录文档。 最后，WC以目标方式迅速传播详细信息（即特定的外科医生，护士， 技术人员，清洁人员等）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，I期原型平台将通过新功能增强 充分支持所有或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放在 连接的数据域和跨平台集成，用户界面工作流和自动报告以及 语音命令集成。其次，AI套件将通过基于的新颖工具进行大量更新 I期框架，包括检测新型手术类型和事件，外科用品的检测和 库存管理和用于资源计划的仿真工具箱。一旦所有平台更新 经过技术验证和验证，支持基础架构和生产生态系统将缩放到 支持商业版本。这包括正式的质量功能，操作，支持和分期/生产 环境。白板协调员平台和生产环境将被验证针对质量 系统要求，然后部署在大型现场研究中，以记录或有效性和实用性。