Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 6, 2024
Date Accepted: Oct 28, 2024
Digital Information Ecosystems in Modern Care Coordination and Patient Care Pathways: Challenges and Opportunities for Artificial Intelligence Solutions
ABSTRACT
The integration of digital technologies into healthcare has significantly enhanced the efficiency and effectiveness of care coordination. This perspective paper delves into 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, increased workload on healthcare professionals, communication gaps, and compliance with privacy regulations, which often lead to inefficiencies and diminished care quality. Furthermore, we characterize how emerging artificial intelligence (AI) tools have the potential to enhance the management of patient information by improving data accuracy, accessibility, and responsiveness, boosting interoperability across diverse health systems, and optimizing clinical workflows and digital tool usability. By strategically leveraging AI, healthcare systems can establish a more robust and responsive digital information ecosystem, ultimately leading to improved care coordination and better patient outcomes. This perspective underscores the importance of continued research and investment in AI technologies and for advocating for a thoughtful integration of AI into healthcare practices to fully realize its potential in revolutionizing care coordination.
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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.