Deprescribing in Older Populations: A Comprehensive Review of Evidence, Strategies, and Future Directions

Introduction: Deprescribing has emerged as a critical intervention to address polypharmacy-related complications in older adults. This comprehensive review examines the current evidence base, implementation strategies, and future directions for deprescribing in geriatric populations. Objective: To provide a comprehensive overview of deprescribing in older populations by examining its definition, evidence base, potential benefits and risks, implementation strategies, and emerging technologies, including applications of artificial intelligence. Methods: A comprehensive narrative review was conducted using multiple databases, including Embase, Google Scholar, PubMed, and Scopus. Studies reporting deprescribing interventions in older adults, systematic reviews, meta-analyses, and articles addressing implementation barriers were included. References were hand-searched for additional relevant studies. Results and Discussion: Deprescribing interventions demonstrate significant benefits, including reduced adverse drug reactions (ADRs), decreased falls, improved quality of life, and reduced healthcare utilization. Evidence from multiple international studies shows success rates ranging from 67.4% to 96.9% across different clinical settings. However, potential negative effects include withdrawal symptoms, rebound effects, and disease relapse, occurring in approximately 26% of medication cessations. Key implementation facilitators include patient-centred approaches, multidisciplinary collaboration, and structured decision-making tools. Barriers include time constraints, clinician reluctance, and insufficient standardized protocols. Emerging artificial intelligence technologies show promise for personalizing deprescribing recommendations. Conclusion: Successful deprescribing requires coordinated efforts integrating evidencebased protocols, patient-centred care, and multidisciplinary collaboration. Future research should focus on developing standardized methodologies, addressing implementation barriers, and exploring AI-assisted personalized approaches to optimize medication management in older adults.