AI-Integrated Medication Adherence and Telecare System

This paper proposed a medication adherence and telecare system that brings scheduling, reminders, patient-reported dose responses, authorised caregiver monitoring, voice interaction and remote consultation onto one platform. The design puts accessibility, privacy, clear role boundaries and human oversight first, and treats AI as an optional aid, not a substitute for professional judgement. The architecture and evaluation plan give a starting point for implementation. Usability, reliability, security and any effect on adherence still have to be shown through documented testing and approved studies before clinical benefit can be claimed. The main limitations are these. The paper describes a proposed system, and no implementation details or empirical results are available yet. A patient’s response is self-reported and cannot verify that the medicine was taken. Reminder delivery depends on device settings, battery, network and operating-system restrictions. AI-generated text can be incomplete or wrong and needs validation. Usability, clinical value, scalability, cost and long-term effect on adherence are untested. Finally, linking with electronic health records, pharmacies or clinical workflows would need further technical, governance and interoperability work. Next steps are to build and validate the core reminder and response workflow, run accessibility-focused usability tests and complete a security assessment. A later study could then test feasibility and adherence outcomes using a pre-registered protocol and a validated measure. Other directions include multilingual voice interaction, clinician-approved escalation pathways, integration with existing health systems, and AI-assisted summaries checked against expert-reviewed references. Patient feedback, clinical governance and evidence of safety should guide any expansion.

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