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September 18, 2025PeerJ Computer Science8 citationsOpen Access

Exploring mHealth interventions for medication management: a scoping review of digital tools, implementation barriers, and patient outcomes

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XWXuye WangBWBeibei WangWTWan Yin Tew

Key Points

  • Among the 319 studies analyzed, 85% showed improved medication adherence linked to personalized reminders and real-time tracking, suggesting effective tools exist.
  • Clinical improvements include better control of blood pressure and glucose levels, alongside enhanced quality of life reported by patients using mHealth applications.
  • Key barriers to adopting mHealth tools involve limited digital literacy and concerns about data privacy, indicating a need for user-friendly designs.
  • Future research must explore cost-efficiency and integration of mHealth applications within existing healthcare systems for sustained impact on patient outcomes.

Abstract

Background Medication non-adherence remains a significant global healthcare challenge, resulting in inadequate disease management, increased hospitalisations, and higher healthcare costs. Mobile health (mHealth) applications have emerged as promising digital health tools for enhancing medication adherence through real-time monitoring, personalised reminders, artificial intelligence (AI)-driven interventions, and improved patient engagement. Objectives This scoping review examines the effectiveness, key features, and challenges of mHealth applications in promoting medication adherence across diverse patient populations and healthcare settings. It also seeks to identify research gaps and inform future development and implementation strategies for digital therapeutics. Eligibility Criteria Studies published between 2020 and 2024 were included if they investigated the use of mHealth applications to improve medication adherence and reported outcomes related to adherence rates, patient health indicators, or user engagement. Only studies with empirical data, including randomised controlled trials, observational studies, or mixed-methods research, were considered. Sources of Evidence A comprehensive search was conducted across Scopus, Web of Science, PubMed/MEDLINE, Google Scholar, and CINAHL databases. In total, 319 studies met the inclusion criteria following a systematic screening process based on Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Charting Methods Data were extracted on study design, app functionalities, patient demographics, adherence outcomes, and barriers to adoption. The charted data were thematically synthesised to identify trends, success factors, and limitations. Results Among the included studies, 85% reported improved medication adherence associated with features such as personalised medication reminders, real-time health tracking, and AI-powered adherence prediction. Clinical outcomes were also frequently observed, including improved blood pressure, glucose control, and patient-reported quality of life. Key barriers to adoption included limited digital literacy, concerns about data privacy, socioeconomic disparities, and a lack of integration with electronic health records (EHRs). Conclusions mHealth applications show significant potential to improve medication adherence and health outcomes, particularly in the management of chronic diseases. However, inclusive design, robust data privacy frameworks, and evidence-based implementation strategies are essential for scalability and sustained impact. Future research should focus on long-term effectiveness, cost-efficiency, and integration of mHealth tools within broader healthcare systems.

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Cite This Study

Wang et al. (2025) studied this question.

synapsesocial.com/papers/68d462c131b076d99fa61e47https://doi.org/10.7717/peerj-cs.3190
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