This chapter proposes an agent-based architecture for home care support, whose main capability is to continuously admit and apply new medical knowledge entered into the system, capturing and codifying implicit knowledge deriving from the medical staff. Knowledge is the fundamental catalyst in all application domains, and this is particularly true especially for the medical context. Knowledge formalization, representation, exploitation, creation, and sharing are some of the most complex issues related to Knowledge Management. Moreover, Artificial Intelligence techniques and MAS (Multi-Agent System) in health care are increasingly justifying the large demand for their application, since traditional techniques are often not suitable to manage complex tasks or to adapt to unexpected events. The chapter presents also a methodology for approaching medical knowledge management from its representation symbolism to the implementation details. The codification of health care treatments, as well as the formalization of domain knowledge, serves as an explicit, a priori asset for the agent platform implementation. The system has the capability of applying new, implicit knowledge emerging from physicians.
TopIntroduction
The work presented in this chapter is part of the K4CAREa (Knowledge for Care) European project, whose aim is, among the others, to provide a Home Care Model, and develop a prototype system based on Web technology and intelligent agents. The percentage of old and chronically ill people in European countries is putting very heavy economic and social pressure on all national health care systems. This problem can be somehow enlightened if home care services are improved and used as a valid alternative to hospitalization. In the context of the K4CARE project, we are targeting a software engineering method that automates the development of an agent platform for this knowledge-intensive application. The intended solution has two basic features. On the one hand, actors are members of well defined organizations. On the other hand, there is extensive domain knowledge to be considered.
Developing software for medical applications, in particular for home care, is special, since the software needs to incorporate complex and sometimes intuitive knowledge present in the mind of the medical staff. Moreover, the medical staff is organized into a well-structured model, where roles and responsibilities of each participant are well-defined. The most relevant aspect of our architecture is the separation of knowledge description from software implementation, granting a high level of interoperability and independence among elements of the system. Key elements of the architecture are shown in Figure 1 and will be described in details throughout this chapter.
Figure 1. Knowledge-driven architecture of the home care platform
The declarative and procedural knowledge form the Explicit Knowledge Layer, where domain entities and actor capabilities can be formally described. Agent-oriented code generation is the core function of the Implementation Layer. The deployment of agents and the end-user involvements are illustrated in the Application Layer. The Implicit Knowledge Layer embeds the capability of the architecture to capture implicit knowledge. This is the functional point where new medical knowledge is tacitly created and formalized by a proper description mechanism.
The agent paradigm advances the modeling of software systems by embodying a stronger notion of autonomy and control than objects, including the notion of reactive, proactive, and social behaviors, as well as assuming inherent multi-threaded control. This allows handling the complexity by powerful abstractions in engineering software systems. In order to be able to build complex and reliable systems, we need not only new models and technologies, but also an appropriate set of software engineering abstractions that can be used as a reference for system analysis, and as the basis for methodologies that enable developers to engineer software systems in a robust, reliable, and repeatable fashion.
The result of our investigations is an architecture driven by the knowledge, which is able to generate agent code from ontology and codified treatments. Moreover, the architecture enables the creation, valorization and embedment of new medical knowledge (referred to as implicit knowledge).
TopThe Actual Home Care
In e-health it is increasingly necessary to develop tele-informatic applications to support people involved in providing basic medical care (physicians, nurses, patients, relatives, and citizens in general). The care of chronic and disabled patients involves lifelong treatments under continuous expert supervision. Moreover, healthcare workers and patients accept that being cared for in hospitals or residential facilities may be unnecessary and even counterproductive. From a global view, such patients may saturate national health services and increase health-related costs. The debate over the crisis of financing healthcare is open and is a basic political issue for old and new EU member countries and could hinder European convergence.