Co-Development of Telehealth, Remote Patient Monitoring, and AI-based Tools for Inclusive Technology-Facilitated Healthcare Work of the Future

随着数字健康技术的使用越来越多，新技术的潜力、现有的医疗实践和工作人员对新技术的准备之间的差距限制了数字健康实现大规模接受和有效利用的潜力。这一向规模化研究项目的过渡将包容性视为未来技术促进的医疗工作规模的关键驱动因素。医疗保健工作的包容性技术将使不同角色和技能的员工能够利用越来越多的数据驱动技术。该项目的重点是数据密集型技术(DIT)的增长，其中包括远程医疗和基于人工智能的工具。该项目向规模化过渡的方法集中在三个方面，以缓解当前医疗保健工作与数据密集型技术之间的现有错位。首先是通过与用户共同开发工具和通用设计原则，降低医护人员进行技术集成的门槛。其次是授权医疗系统中具有不同角色的个人采用和使用这些工具，并提高他们的技能。第三是实现以患者为中心的医疗保健，促进自主性，加强临床医生与患者的和谐。该项目代表了多机构致力于将创新的医疗保健转变为规模化，通过DIT促进将不同的员工纳入美国各地的医疗保健系统，该系统总共包括美国24个州的1000多个护理地点、多个工作角色以及不同级别的培训和层级。该项目汇集了多个科学领域，包括人机交互、健康信息学、人工智能(AI)、传感、医学、组织行为以及对多样性和包容性的研究。研究人员团队的结构旨在实现多个融合目标，例如量化扩展DIT对包容性医疗工作的影响，以及模拟处方和采用DIT以实现大规模包容性部署。此外，调查人员试图确定可概括的DIT设计原则，用于大规模的包容性医疗工作，并开发理论和工具，通过基于DIT的患者-提供者一致性促进规模内的纳入。最后，该项目预计将开发工具和实践，以降低不同医疗工作者理解和参与DIT的障碍；创建基于人工智能的团队重点工具；并分析将人工智能用于不同医疗团队工作的机会和挑战。该项目由美国国家科学基金会人-技术前沿交叉部门工作未来计划资助，旨在通过推进与人类工作者和谐运作的智能工作技术的设计，促进对工作环境中相互依赖的人-技术伙伴关系的更深层次的基本了解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

As the use of digital health technologies grows, gaps between the potential of new technologies, existing healthcare practices, and workers’ preparedness for new technologies limit the potential of digital health to achieve acceptance and effective utilization at scale. This transition to scale research project views inclusion as a key driver of scale in future technology-facilitated healthcare work. Inclusive technology for healthcare work will enable workers in diverse roles and skills to leverage increasing access to data-driven technologies. The project focuses on the growth of Data-Intensive Technologies (DIT), which include telehealth and AI-based tools. The project’s approach to transition to scale centers on alleviating existing misalignment between current healthcare work and data-intensive technologies in three ways. First is through the co-development of tools and generalizable design principles with users that lower the barrier to technology integration for healthcare workers. Second is by empowering individuals within healthcare systems who have diverse roles to adopt and use the tools and improve their skills. Third is to enable patient-centered healthcare that promotes autonomy and strengthens clinician-patient concordance. The project represents a multi-institutional commitment to transitioning innovative healthcare to scale, through DIT facilitated inclusion of diverse workers in healthcare systems across the U.S., which together encompass over 1000 care sites in U.S. 24 states, multiple work roles, and different levels of training and hierarchy.This project brings together several scientific fields, including human-computer interaction, health informatics, artificial intelligence (AI), sensing, medicine, organizational behavior, and research on diversity and inclusion. The investigator team is structured to achieve multiple convergent goals such as quantifying the impacts of scaling DIT on inclusive healthcare work and modelling prescription and adoption of DIT towards inclusive deployment at scale. Additionally, the investigators seek to identify generalizable DIT design principles for inclusive healthcare work at scale, and to develop theory and tools to facilitate at-scale inclusion through DIT-based patient-provider concordance. Finally, the project expects to develop tools and practices for lowering barriers to comprehension of and engagement with DIT by diverse healthcare workers; to create AI-based team-focused tools; and to analyze the opportunities and challenges in using AI for diverse healthcare teams’ work. This project has been funded by the NSF Future of Work at the Human-Technology Frontier cross-directorate program to promote deeper basic understanding of the interdependent human-technology partnership in work contexts by advancing design of intelligent work technologies that operate in harmony with human workers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.