Artificial Intelligence for Patient Engagement in Digital Healthcare: A Systematic Literature Review
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Abstract
Artificial Intelligence (AI) has become a key driver of digital healthcare transformation by enabling more intelligent, personalized, and patient-centered healthcare services. Despite its rapid adoption, existing studies remain fragmented across diverse AI technologies, healthcare settings, and patient populations, limiting a comprehensive understanding of how AI enhances patient engagement. Therefore, this study aims to systematically synthesize recent evidence on the role of Artificial Intelligence in improving patient engagement within digital healthcare. This study employs a Systematic Literature Review (SLR) following the PRISMA 2020 guidelines to identify, evaluate, and synthesize peer-reviewed journal articles published between 2021 and 2026. Thirty-one studies were included in the review after a systematic screening process. The review synthesizes current evidence indicating that AI applications—including conversational AI, Large Language Models, intelligent decision-support systems, and AI-powered digital health assistants—support patient engagement by improving patient communication, health education, self-management, personalized healthcare delivery, and shared decision-making. The review also highlights recurring challenges related to trust, ethical governance, data privacy, and implementation readiness while identifying future research opportunities for developing trustworthy and patient-centered AI-enabled healthcare systems. This study contributes by integrating fragmented evidence into a comprehensive understanding of how AI strengthens patient engagement and supports the future development of digital healthcare.
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