  There is a great divide between rural and urban areas, particularly in
medical emergency care. Although medical best practice guidelines exist in
hospital handbooks, they are often lengthy and difficult to apply clinically.
The challenges are exaggerated for doctors in rural areas and emergency medical
technicians (EMT) during patient transport.
  In this paper, we propose the concept of distributed executable medical best
practice guidance systems to assist adherence to best practice from the time
that a patient first presents at a rural hospital, through diagnosis and
ambulance transfer to arrival and treatment at a regional tertiary hospital
center. We codify complex medical knowledge in the form of simplified
distributed executable disease automata, from the thin automata at rural
hospitals to the rich automata in the regional center hospitals. However, a
main challenge is how to efficiently and safely synchronize distributed best
practice models as the communication among medical facilities, devices, and
professionals generates a large number of messages. This complex problem of
patient diagnosis and transport from rural to center facility is also fraught
with many uncertainties and changes resulting in a high degree of dynamism. To
address this situation, we propose a pathophysiological model-driven message
exchange communication architecture that ensures the real-time and dynamic
requirements of synchronization among distributed emergency best-practice
models are met in a reliable and safe manner. Taking the signs, symptoms, and
progress of stroke patients transported across a geographically distributed
healthcare network as the motivating use case, we implement our communication
system and apply it to our developed best practice automata using laboratory
simulations. Our proof-of-concept experiments shows there is potential for the
use of our system in a wide variety of domains.
