Background: Populations are under-served by local health policies and management ofresources. This partly reflects a lack of realistically complex models to enable appraisal of awide range of potential options. Rising computing power coupled with advances in machinelearning and healthcare information now enables such models to be constructed andexecuted. However, such models are not generally accessible to public health practitionerswho often lack the requisite technical knowledge or skills.Objectives: To design and develop a system for creating, executing and analysing the resultsof simulated public health and healthcare policy interventions, in ways that are accessibleand usable by modellers and policy-makers.Methods: The system requirements were captured and analysed in parallel with thestatistical method development for the simulation engine. From the resulting softwarerequirement specification the system architecture was designed, implemented and tested. Amodel for Coronary Heart Disease (CHD) was created and validated against empirical data.Results: The system was successfully used to create and validate the CHD model. The initialvalidation results show concordance between the simulation results and the empirical data.Conclusions: We have demonstrated the ability to connect health policy-modellers andpolicy-makers in a unified system, thereby making population health models easier to share,maintain, reuse and deploy.</p
