Revolutionizing remote patient care: The role of machine learning and AI in Enhancing Tele-pharmacy Services
1 MBA, Graves School of Business, Morgan State University, USA.
2 Department of Computer Science and Information Technology, Austin Peay State University, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(03), 1133–1149
Publication history:
Received on 03 November 2024; revised on 11 December 2024; accepted on 13 December 2024
Abstract:
The integration of machine learning (ML) and artificial intelligence (AI) is transforming the healthcare landscape, with telepharmacy emerging as a key innovation in remote patient care. Telepharmacy services leverage digital technologies to extend pharmacy expertise beyond physical locations, enabling the provision of essential healthcare services such as prescription management, medication adherence monitoring, and patient counseling. As the demand for remote healthcare solutions accelerates, ML and AI are revolutionizing telepharmacy by enhancing operational efficiency, improving patient outcomes, and personalizing care delivery. At a broader level, AI-driven systems streamline complex processes such as inventory management, automated prescription validation, and drug interaction analysis. Predictive models assess patient-specific factors to recommend optimal treatments, reducing errors and improving clinical decision-making. Additionally, machine learning algorithms enhance real-time medication adherence tracking, providing pharmacists and healthcare providers with actionable insights into patient behaviour. Narrowing the focus, telepharmacy services augmented by ML and AI are addressing unique challenges such as medication accessibility in underserved regions and the rising prevalence of chronic diseases requiring continuous monitoring. For instance, AI-enabled chatbots and virtual assistants are facilitating round-the-clock patient support, ensuring timely interventions for improved adherence and disease management. Despite these advancements, challenges persist, including data privacy concerns, regulatory compliance, and the need for equitable access to digital health tools. This study examines the transformative potential of ML and AI in telepharmacy, highlighting successful implementations, emerging trends, and barriers to widespread adoption. By fostering a deeper understanding of these technologies, healthcare stakeholders can unlock the full potential of telepharmacy to revolutionize remote patient care and bridge gaps in healthcare delivery.
Keywords:
Telepharmacy; Machine Learning; Artificial Intelligence; Remote Patient Care; Medication Adherence; Personalized Healthcare
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0