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A NASSS framework-guided systematic review and exploratory modelling of digital health interventions for polypharmacy
Arun Vamadevan1,2,3,4, Vijesh Vijayan5, Christine Cole6
1NIHR Clinical Research Facility, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK. arun.vamadevan@liverpoolft.nhs.uk.
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. The Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework offers a valuable lens to evaluate complex digital health interventions targeting medication optimization in older adults.
Objective:
This review systematically examines the adoption, scale-up, and sustainability of technology-supported medicines optimization interventions for older adults, guided by the 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 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. Successful adoption was associated with user-centred technology design, strong clinical leadership, workflow integration, and organizational readiness. Interventions incorporating multidisciplinary collaboration, continuous feedback, and iterative adaptation showed stronger sustainability. Common barriers included technological complexity, poor interoperability, lack of provider engagement, insufficient training, and regulatory constraints. Decision tree analysis identified usability, early stakeholder engagement, organizational alignment, and system adaptability as key factors predicting successful adoption and sustainability.
Conclusion:
This is the first review to integrate the NASSS framework with decision tree 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.
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