Revolutionizing remote patient care: The role of machine learning and AI in Enhancing Tele-pharmacy Services

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-30
DOI
https://doi.org/10.5281/zenodo.15187747
Primary Topic
Neuroscience and Neuropharmacology Research
Type
article
Field-Weighted Citation Impact
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article

Revolutionizing remote patient care: The role of machine learning and AI in Enhancing Tele-pharmacy Services

Zenodo (CERN European Organization for Nuclear Research)
Neuroscience and Neuropharmacology Research
article

Revolutionizing remote patient care: The role of machine learning and AI in Enhancing Tele-pharmacy Services

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Austin Peay State University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 60%
Neuroscience and Neuropharmacology Research
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Revolutionizing remote patient care: The role of machine learning and AI in Enhancing Tele-pharmacy Services · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS