Several European countries, including the UK, are investing in large-scale telehealthcare pilots, to thoroughly evaluate the benefits of telehealthcare. Due to the high level of risk associated with such projects, it becomes desirable to be able to predict the success of telehealthcare systems in potential deployments, in order to inform investment and help save resources. An important factor for the success of any telehealthcare deployment is usability, as it helps to achieve the benefits of the technology through increased productivity, decreased error rates, and better acceptance. In particular, efficiency, one of the characteristics of usability, should be seen as a central measure for success, as the timely care of a high number of patients is one of the important claims of telehealthcare. Despite the recognized importance of usability, it is seen as secondary in the design of telehealthcare systems. The resulting problems are difficult to predict due to the heterogeneity of deployment contexts. This thesis proposes the automation of usability evaluation through the use of modelling and simulation techniques. It describes a generic methodology which can guide a modeller in reusing models for predicting characteristics of usability within different deployment sites. It also describes a modelling approach which can be used together with the methodology, to run in parallel a user model, inspired from a cognitive architecture, and a system model, represented as a basic labelled transition system. The approach simulates a user working with a telehealthcare system, and within her environment, to predict the efficiency of the system and work process surrounding it. The modeller can experiment with different inputs to the models in terms of user profile, workload, ways of working, and system design, to model different potential- real or hypothetical- deployments, and obtain efficiency predictions for each. A comparison of the predictions helps analyse the effects on efficiency of changes in deployments. The work is presented as an experimental investigation, but emphasises the great potential of modelling and simulation for helping to inform investment, help reduce costs, mitigate risks and suggest changes that would be necessary for improving the usability, and therefore success or telehealthcare deployments. My vision is that, if used commercially, the approaches presented in this thesis could help reduce risks for scaling up telehealthcare deployments.