SHB: Type II (INT): Collaborative Research: Creating Learning Systems with Mobile Technology to Improve Coordination in Perioperative Services

该项目建议使用移动的技术、学习系统、数据分析、教育和培训的组合创建一个框架，以加强围手术期服务部门（POS）内部和之间的工作人员合作与协调。 围手术期服务包括手术准备、手术室、麻醉后护理、无菌处理和各种其他服务，如放射学和内窥镜检查。 该项目的具体目标是：（1）通过收集和使用重要的工作流程里程碑，并通过使用智能应用程序引入人工智能技术，加强POS工作人员之间的沟通和协调，以提高护理质量，（2）使用数据分析来分析用智能应用程序收集的工作流数据，以提供真实的的直观显示，为一线员工提供时间信息，为管理人员提供日常绩效仪表板，以及（3）通过培训和教育，在医疗保健系统中引发行为和文化变革。虽然现有的信息技术能力，如自然语言处理，人工智能和语音识别技术是计算领域有前途的发展，但它们在医疗保健中的用途有限，因此需要进行彻底的调查，然后才能有效地用于医疗保健。为了实现这些目标，研究团队将与合作医疗机构，格林维尔医院系统（GHS），棕榈健康（棕榈），和南卡罗来纳州医科大学（MUSC），在开发的工具和模型，这将是试点测试在这些组织的工作人员密切合作。 开发的工具和模型将在南卡罗来纳州的卫生保健提供者中广泛传播。此外，智能应用程序和基于代理的模拟模型将为团队提供一个教学和培训工具，可用于克莱姆森大学和南卡罗来纳州大学（USC）的课堂上，为各个领域的学生提供信息和工作流管理技术方面的教学，如商业、工程、科学和医疗保健专业的学生。

This project proposes to create a framework using a combination of mobile technology, learning systems, data analytics, education, and training to enhance cooperation and coordination of staff within and across perioperative services departments (POS). Perioperative services comprise surgery preparation, operating rooms, post-anesthesia care, sterile processing and a variety of other services, such as radiology and endoscopy. The specific objectives of this project are to: (1) enhance communication and coordination among POS staff to improve the quality of care by gathering and using important workflow milestones and introducing artificial intelligence techniques through the use of a smart-app, (2) analyze workflow data gathered with smart-apps using data analytics to provide intuitive displays of real-time information for frontline staff and a daily performance dashboard for managers, and (3) induce behavioral and cultural change in healthcare systems through training and education. While existing information technology capabilities such as natural language processing, artificial intelligence, and speech recognition technology are promising developments in computing, their uses in health care are limited and thus need to be thoroughly investigated before they can be used in health care effectively. To accomplish these objectives, the research team will work closely with the partnering healthcare organizations, Greenville Hospital System (GHS), Palmetto Health (Palmetto), and the Medical University of South Carolina (MUSC), in developing the tools and models which will be pilot-tested at these organizations by their staff. The developed tools and models will be widely disseminated among health care providers in South Carolina. In addition, the smart-apps and agent-based simulation model will provide the team with a teaching and training tool that can be used in the classroom at Clemson University and the University of South Carolina (USC) to teach students across a variety of fields, such as business, engineering, science and healthcare students about information and workflow management techniques.