Vol. 3 No. 2 (2023): Hong Kong Journal of AI and Medicine
Articles

Enhancing Patient Care Coordination with AI-Powered Clinical Pathway Optimization: Applies AI algorithms to optimize clinical pathways and care coordination processes, ensuring seamless transitions of care and improved patient outcomes across healthcare settings

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  • Dr. Hamid Reza Jamali
Dr. Hamid Reza Jamali
Professor of Computer Science, University of Isfahan, Iran
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Published 18-12-2023

Keywords

  • Clinical Pathways,
  • Care Coordination,
  • Patient Outcomes,
  • Healthcare Systems
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Hamid Reza Jamali, “Enhancing Patient Care Coordination with AI-Powered Clinical Pathway Optimization: Applies AI algorithms to optimize clinical pathways and care coordination processes, ensuring seamless transitions of care and improved patient outcomes across healthcare settings”, Hong Kong J. of AI and Med., vol. 3, no. 2, pp. 53–62, Dec. 2023, Accessed: Nov. 21, 2024. [Online]. Available: https://hongkongscipub.com/index.php/hkjaim/article/view/53

Abstract

This research paper explores the application of artificial intelligence (AI) in optimizing clinical pathways and enhancing patient care coordination. The healthcare industry is increasingly adopting AI technologies to improve patient outcomes, reduce costs, and enhance overall efficiency. Clinical pathways are standardized, evidence-based multidisciplinary care plans that outline the recommended course of treatment for patients with specific medical conditions. However, the complexity of healthcare systems and the variability in patient needs often lead to challenges in effectively implementing and managing these pathways. AI offers the potential to address these challenges by analyzing large volumes of patient data, identifying patterns, and providing actionable insights to healthcare providers. This paper discusses the use of AI algorithms, such as machine learning and natural language processing, to optimize clinical pathways, improve care coordination, and ultimately enhance patient outcomes. The paper also examines the benefits, challenges, and future directions of AI-powered clinical pathway optimization in healthcare settings.

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