A NASSS Framework-Guided Review of Technology Supported Medicines Optimization for Geriatric Polypharmacy: Challenges, Opportunities, and Implementation Strategies

Background: Polypharmacy is a growing challenge in older adults with multimorbidity, increasing the risk of adverse drug events, hospital admissions, and healthcare utilisation. Technology-supported interventions, such as clinical decision support systems (CDSS) and digital deprescribing tools, offer new opportunities to optimize medication use. However, adoption and sustainability remain variable across healthcare settings. Objective: This review systematically examines the adoption, scale-up, and sustainability of technology-supported medicines optimization interventions for older adults, guided by the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. Methods: A systematic search was conducted across Scopus, PubMed, Cochrane Library, and CINAHL. After screening and eligibility assessment, 30 studies were included. A narrative synthesis was performed, mapping intervention characteristics and outcomes to NASSS domains. An exploratory predictive modelling, including logistic regression and decision tree analysis, were used to identify factors influencing intervention success. This review was registered with PROSPERO (CRD420251006170). Results: The included studies evaluated diverse interventions such as CDSS, electronic prescribing platforms, pharmacist-led deprescribing systems, and telehealth-supported medication reviews. Thematic synthesis revealed that successful adoption was associated with user-centred technology design, strong clinical leadership, integration into clinical workflows, and organizational readiness for change. Interventions that incorporated multidisciplinary collaboration, continuous feedback mechanisms, and iterative adaptation to clinical contexts showed stronger patterns of sustainability. Common barriers included technological complexity, poor interoperability with existing systems, lack of provider engagement, insufficient training for end-users, and external regulatory and policy constraints. Predictive modelling using logistic regression and decision tree analysis supported the thematic findings, identifying usability, early stakeholder engagement, organizational alignment, and system adaptability as consistent factors associated with successful adoption and sustainability. Conclusion: This is the first review to integrate the NASSS framework with predictive modelling to evaluate technology-supported medicines optimization for older adults with multimorbidity and polypharmacy. The findings emphasize that successful implementation requires a formative, contextually sensitive approach that addresses technological, organizational, and policy-level complexities.