The CMO System Model: A Dynamic Framework to Operationalize Adaptive Pharmaceutical Care and Drive Health-System Sustainability

Background Pharmaceutical care (PC) models are evolving from episodic interactions to complex, continuous systems managing multimorbidity and polypharmacy. The Capacity–Motivation–Opportunity (CMO) framework is widely used to stratify patients, but current applications often treat these dimensions as static and independent. This study aims to reconceptualise the CMO framework as a dynamic system in which these constructs influence one another through feedback loops, and to formalise this architecture into a model that supports adaptive, sustainable pharmacist-led care. Methods We conducted a conceptual theory-building study integrating systems thinking, abductive reasoning, and cross-impact analysis. Purposive conceptual sampling was used to identify relevant literature across pharmaceutical care, behavioural science, complexity science, and implementation frameworks. Interdependencies among capacity, motivation, and opportunity were iteratively mapped and synthesised into a Conceptual Interdependence Matrix (CIM). The resulting model and a derived Theoretical Taxonomy of Pharmaceutical Interventions (TTPI) underwent external expert audit to assess conceptual coherence and mechanistic plausibility. Results Six directional interdependencies were identified, forming a closed set of reinforcing and balancing feedback loops. Two mechanisms emerged as dominant regulators: a balancing sustainability loop where motivation reduces pharmacotherapeutic complexity, and a reinforcing value-generation loop where opportunity enhances early detection and stabilises trajectories. These loops organise the system into a fast-timescale behavioural subsystem and a slower structural subsystem. The derived TTPI links interventions to specific leverage points, providing a decision structure for workload planning. Conclusions The CMO System Model offers a coherent mid-range theory explaining how pharmacist-led care produces both patient-level behavioural change and system-level organisational effects. By articulating the feedback mechanisms that generate value, it provides a theoretical foundation for the redesign and digital augmentation of personalised pharmaceutical care.