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.