Artificial Intelligence in Medication Management for Older Adults in Low‐ and Middle‐Income Countries: A Narrative Review

Abstract

Artificial Intelligence (AI) has emerged as a transformative tool in medication management, particularly for older adults who are vulnerable to adverse drug events, polypharmacy, and medication non-adherence. This narrative review explores the utilization of AI-driven interventions in low and middle-income countries (LMICs) to enhance medication safety, adherence, and prescribing practices. The review synthesizes existing studies on AI applications, including automated drug interaction detection, machine learning models for adverse event prediction, and AI-supported decision-making tools for healthcare professionals. Findings suggest that AI has demonstrated significant potential in reducing inappropriate medication use and improving patient adherence through mobile applications and electronic health record (EHR) integration. However, AI adoption in LMICs remains limited despite its benefits due to high implementation costs, insufficient digital infrastructure, low AI literacy among healthcare providers, and ethical concerns related to data privacy and algorithm bias. Addressing these barriers requires strategic policy reforms, investment in AI education, and improved regulatory frameworks to ensure responsible and equitable AI deployment. Future research should focus on evaluating the long-term effectiveness of AI interventions in real-world settings and developing scalable solutions tailored to LMICs. With the right support, AI has the potential to revolutionize medication management, improving the quality of care and health outcomes for older adults globally.

Ähnliche Arbeiten