Geographic access to healthcare is crucial to ensure equal opportunities for a healthy future for all and to achieve universal health coverage, a key target of the United Nations Sustainable Development Goals (SDGs) for 2030. Quantifying geographic accessibility to healthcare is necessary to identify gaps in health system coverage and to support targeted health system optimization and planning, especially in low- and middle-income (LMICs) countries where health services are scarcely available. This PhD thesis reviews, applies, and evaluates geographical accessibility models in different settings in LMICs to 1) identify the effect of spatial access to care on epidemiological modelling, 2) create a post-disaster accessibility modelling workflow to support post-disaster health system evaluation and optimization, and 3) evaluate the effect of different population datasets in accessibility modelling on population coverage statistics. This PhD thesis has not only shown new fields for application of accessibility modelling but has also contributed to improved efficiency of data processing and visualization techniques. This is of high importance to ensure that the produced outcomes and maps are of best use to policy- and decision makers, so we can contribute to informed health system improvement to ensure better access and health outcomes across populations.