Chen You, Lehmann Christoph U, Malin Bradley
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.
Department of Computer Science, Vanderbilt University, Nashville, TN, United States.
J Med Internet Res. 2024 Dec 2;26:e60258. doi: 10.2196/60258.
The integration of digital technologies into health care has significantly enhanced the efficiency and effectiveness of care coordination. Our perspective paper explores the digital information ecosystems in modern care coordination, focusing on the processes of information generation, updating, transmission, and exchange along a patient's care pathway. We identify several challenges within this ecosystem, including interoperability issues, information silos, hard-to-map patient care journeys, increased workload on health care professionals, coordination and communication gaps, and compliance with privacy regulations. These challenges are often associated with inefficiencies and diminished care quality. We also examine how emerging artificial intelligence (AI) tools have the potential to enhance the management of patient information flow. Specifically, AI can boost interoperability across diverse health systems; optimize and monitor patient care pathways; improve information retrieval and care transitions; humanize health care by integrating patients' desired outcomes and patient-reported outcome measures; and optimize clinical workflows, resource allocation, and digital tool usability and user experiences. By strategically leveraging AI, health care systems can establish a more robust and responsive digital information ecosystem, improving care coordination and patient outcomes. This perspective underscores the importance of continued research and investment in AI technologies in patient care pathways. We advocate for a thoughtful integration of AI into health care practices to fully realize its potential in revolutionizing care coordination.
将数字技术融入医疗保健显著提高了护理协调的效率和效果。我们的观点文章探讨了现代护理协调中的数字信息生态系统，重点关注患者护理路径上信息的生成、更新、传输和交换过程。我们识别出该生态系统中的几个挑战，包括互操作性问题、信息孤岛、难以映射的患者护理旅程、医疗保健专业人员工作量增加、协调和沟通差距以及遵守隐私法规。这些挑战往往与效率低下和护理质量下降相关。我们还研究了新兴的人工智能（AI）工具如何有可能加强患者信息流的管理。具体而言，人工智能可以提高不同医疗系统之间的互操作性；优化和监测患者护理路径；改善信息检索和护理过渡；通过整合患者的期望结果和患者报告的结果指标使医疗保健人性化；以及优化临床工作流程、资源分配和数字工具的可用性及用户体验。通过战略性地利用人工智能，医疗保健系统可以建立一个更强大、响应更迅速的数字信息生态系统，改善护理协调和患者结局。这一观点强调了在患者护理路径中持续研究和投资人工智能技术的重要性。我们主张将人工智能深思熟虑地融入医疗保健实践，以充分实现其在变革护理协调方面的潜力。
