Presentation (CTI)

OBJECTIVES: Mobile Stroke Units (MSUs) enable pre-hospital stroke diagnosis and treatment, potentially improving outcomes by reducing time to reperfusion; however, strategic deployment is required to optimize economic value. This targeted literature review (TLR) evaluated published spatial analyses of MSU placement and stroke emergency care to identify modelling approaches, parameters, and decision criteria relevant to developing a comprehensive, internationally adaptable geospatial cost-effectiveness framework for MSUs.
METHODS: A TLR was conducted in PubMed, Embase, and grey literature sources. Studies reporting geospatial, optimization, simulation, or location-allocation analyses of MSUs or other time-critical stroke services were included. Data were extracted on explicit modelling frameworks, geographic inputs, optimization objectives, healthcare perspectives (societal versus payer), and clinical or economic outcomes to identify methodological variations and critical research gaps.
RESULTS: Identified studies utilized geographic information systems, simulation, and location-allocation algorithms. Clinical outcomes (treatment time, functional independence) consistently improved across settings, but economic results were highly heterogeneous, varying significantly by geography and chosen evaluation perspective (e.g., societal versus healthcare payer). Optimization objectives directly dictated recommended deployment locations: urban models prioritized total population coverage density, whereas rural models maximized per-patient accessibility benefits despite lower case volumes. A major identified literature gap is that operational constraints, such as dynamic staffing schedules, capital costs, and localized emergency service integration, are rarely integrated dynamically with geospatial outcomes, limiting real-world decision support.
CONCLUSIONS: Published analyses demonstrate a wide variety of approaches, highlighting that MSU value is highly dependent on chosen stakeholder perspectives and optimization goals. Findings explicitly highlighted trade-offs between maximizing total population benefit, benefit per patient, service coverage, and economic efficiency. Because these objectives often conflict, future spatial-economic analyses must be completely flexible and transparent. These insights explicitly characterize existing literature gaps, successfully laying the structural groundwork for our own future research to build a robust, multi-perspective modelling framework.