Towards a Systematic Software Architecture for Acute Care Support

According to the Institute of Medicine (IOM) close to 100,000 safety-related medical incidents happens each year in US due to preventable medical errors. These preventable medical errors are caused by lack of timely and comprehensive information about the patient that makes the proper and efficient application of best available knowledge difficult rather than lack of such knowledge. The preventable medical errors often occur due to slips and lapses in settings where the staff are overloaded and under stress. Our focus is on acute care scenarios where medical staff must make quick decisions based on the best available evidence. In this paper, we propose an acute care support system (MACMS) that aids the physician with monitoring and making decisions given the best available knowledge to decrease preventable medical errors. Such a system is possible due to the opportunity presented to us by Medical Device Plug-and-Play (MDPnP) to integrate information from different devices in an integrated clinical environment. In this paper, we also present a model driven approach for designing these acute care support systems by developing models that correspond closely to medical mental processes and a system architecture to support execution from these models.unpublishe