SynthesisFrontiers in digital health2025
Artificial intelligence-based tools for patient support to enhance medication adherence: a focused review.
Synthesis in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- The widening medication adherence gap.PLoS medicine · 2026Article
- Integrated Psychological-Behavioral Predictive Model Using Explainable Machine Learning.Healthcare (Basel, Switzerland) · 2026Article
- Review
- Artificial Intelligence in Pharmaceutical Care:Saudi medical journal · 2026Review
- Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.Journal of materials science. Materials in medicine · 2026Review
- Large Language Model-Generated Patient Instructions for Prescriptions in Primary Health Care: Preclinical Algorithm Validation.Journal of medical Internet research · 2026Article
- Exploring Students' Perceptions and Usage of Artificial Intelligence in Supporting Mental Health: A Preliminary Study in Higher Education in Qatar.Healthcare (Basel, Switzerland) · 2026Article
- Review
- Exploring Influencing Factors of Medication Adherence Among Chinese Patients With Alzheimer Disease: Delphi Study Informing Future Artificial Intelligence-Supported Interventions.JMIR formative research · 2026Article
- Artificial Intelligence in Cardiovascular Medicine: A Giant Step in Personalized Medicine?Journal of personalized medicine · 2026Review
- Artificial intelligence-based approaches for monitoring medication adherence among cardiovascular disease patients: a scoping review.BMC medical informatics and decision making · 2026Article
- Transition to electronic prescriptions in pharmacies: Workflows, services, and access to medication - A mixed methods approach.Exploratory research in clinical and social pharmacy · 2026Article
- Integrating emerging technologies for varicose veins: A systematic review of comparative efficacy.Pakistan journal of medical sciences · 2026Review
- Artificial intelligence in cardiology: a narrative review with focus on patient outcomes.Cardiovascular diagnosis and therapy · 2026Review
- Artificial intelligence approaches to predicting treatment non-adherence in chronic diseases: a narrative review.Frontiers in digital health · 2026Review
- Enhancing Physicians' Adherence to the 2023 Sudan Malaria Case Management Protocol Using AI as an Intervention Tool.Cureus · 2025Article
- Artificial Intelligence in Healthcare: A Narrative Review of Recent Clinical Applications, Implementation Strategies, and Challenges.Journal of healthcare leadership · 2025Review
- Editorial: The continuing challenge of medication adherence.Frontiers in pharmacology · 2025Article
- Digital interventions in medication adherence: a narrative review of current evidence and challenges.Frontiers in pharmacology · 2025Review
- The Evolution of Vision Therapy Software and Its Impact on Vision Care - A Comprehensive Major Review.Romanian journal of ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Medication adherence involves patients correctly taking medications as prescribed. This review evaluates whether artificial intelligence (AI) based tools contribute to adherence-related insights or avoid medication intake errors. Methods: We assessed studies employing AI tools to directly benefit patient medication use, promoting adherence or avoiding self-administration error outcomes. The search strategy was conducted on six databases in August 2024. ROB2 and ROBINS1 assessed the risk of bias. Results: The review gathered seven eligible studies, including patients from three clinical trials and one prospective cohort. The overall risk of bias was moderate to high. Three reports drew on conceptual frameworks with simulated testing. The evidence identified was scarce considering measurable outcomes. However, based on randomized clinical trials, AI-based tools improved medication adherence ranging from 6.7% to 32.7% compared to any intervention controls and current practices, respectively. Digital intervention using video and voice interaction providing real-time monitoring pointed to AI's potential to alert to self-medication errors. Based on conceptual framework reports, we highlight the potential of cognitive behavioral approaches tailored to engage patients in their treatment. Conclusion: Even though the present evidence is weak, smart systems using AI tools are promising in helping patients use prescribed medications. The review offers insights for future research. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024571504, identifier: CRD42024571504.
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