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Review
. 2021 Jun 29:3:669869.
doi: 10.3389/fdgth.2021.669869. eCollection 2021.

Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases

Aditi Babel  1 , Richi Taneja  2 , Franco Mondello Malvestiti  3 , Alessandro Monaco  4 , Shaantanu Donde  5
Affiliations
Review

Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases

Aditi Babel et al. Front Digit Health. .

Abstract

Artificial intelligence (AI) tools are increasingly being used within healthcare for various purposes, including helping patients to adhere to drug regimens. The aim of this narrative review was to describe: (1) studies on AI tools that can be used to measure and increase medication adherence in patients with non-communicable diseases (NCDs); (2) the benefits of using AI for these purposes; (3) challenges of the use of AI in healthcare; and (4) priorities for future research. We discuss the current AI technologies, including mobile phone applications, reminder systems, tools for patient empowerment, instruments that can be used in integrated care, and machine learning. The use of AI may be key to understanding the complex interplay of factors that underly medication non-adherence in NCD patients. AI-assisted interventions aiming to improve communication between patients and physicians, monitor drug consumption, empower patients, and ultimately, increase adherence levels may lead to better clinical outcomes and increase the quality of life of NCD patients. However, the use of AI in healthcare is challenged by numerous factors; the characteristics of users can impact the effectiveness of an AI tool, which may lead to further inequalities in healthcare, and there may be concerns that it could depersonalize medicine. The success and widespread use of AI technologies will depend on data storage capacity, processing power, and other infrastructure capacities within healthcare systems. Research is needed to evaluate the effectiveness of AI solutions in different patient groups and establish the barriers to widespread adoption, especially in light of the COVID-19 pandemic, which has led to a rapid increase in the use and development of digital health technologies.

Keywords: NCD; artificial intelligence; big data; cardiovascular disease; compliance; digital health; machine learning; patient empowerment.

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Conflict of interest statement

RT is an employee of Upjohn, a division of Pfizer. FM and SD are full-time employees and stockholders of Viatris. The writing of this paper was commercially funded by Viatris, UK, in the form of a payment for professional scientific writing support to Oliba, Rome, Italy. No products or services of Viatris, UK, have been discussed or promoted within this manuscript. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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