Currently submitted to: JMIR Aging
Date Submitted: Apr 9, 2026
Open Peer Review Period: Apr 25, 2026 - Jun 20, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Implementation of Digital Medicines Optimisation Interventions for Older Adults With Polypharmacy: A Realist Synthesis of What Works, For Whom, and Under What Circumstances
ABSTRACT
Background:
Polypharmacy is highly prevalent among older adults and is associated with adverse drug events, functional decline, and increased healthcare utilisation. Digital medicines optimisation interventions including clinical decision support systems (CDSS), EHR-integrated tools, and emerging AI-enabled systems have been developed to support medication optimisation, yet their real-world effectiveness, adoption, and sustainability remain highly variable across healthcare settings.
Objective:
This review aimed to develop and refine explanatory programme theories that clarify how, why, and under what circumstances digital medicines optimisation interventions succeed or fail in optimising medication use among older adults with polypharmacy.
Methods:
A realist synthesis was conducted in accordance with RAMESES guidelines. Comprehensive searches of MEDLINE, Embase, CINAHL, PsycINFO, Scopus, Web of Science, and the Cochrane Library identified empirical and grey literature on digital medicines optimisation interventions. Databases were searched from inception to December 2025 to capture conceptually rich studies informing theory development across the evolution of digital decision support systems. Studies were included based on relevance and rigour for theory building rather than design hierarchy. CMO configurations were extracted and synthesised using abductive and retroductive reasoning, and findings were mapped onto a multi-level GEAR-up conceptual framework.
Results:
Twenty-three studies were included, spanning primary care, hospital, community, and emergency settings. Seven programme theories were identified, explaining how workflow-aligned integration, alert relevance, human mediation, patient-centred alignment, organisational readiness, limits of automation, and transparency influence adoption, fidelity, sustainability, and conditional use of digital medicines optimisation tools. Most mechanisms driving uptake such as reduced cognitive burden, trust, and professional legitimacy operated at individual and care-team levels, while organisational and system-level contexts determined sustainability and scale-up.
Conclusions:
Digital medicines optimisation interventions are effective when aligned with clinical workflows, supported by interprofessional mediation, and reinforced by organisational and ethical governance structures. This realist synthesis provides theory-informed guidance to support the design, implementation, and scale-up of digital medicines optimisation strategies to enhance medication optimisation and patient safety in older adults with polypharmacy
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