The traditional service market is composed of customers and service providers, interacting within a given structure and following market‐specific rules. These basic attributes are obvious and persistent. The fragile entity, which is essential for normally operating and self‐controlling market, is information. In this context the aim is to distinguish between a background noise, arising from comprehensive marketing campaigns, customer care activities or advertisement and data, advices or knowledge, necessary for any focused business decision. The straightforward example of prospective market suffering from information shortage is healthcare. For a normal patient it is almost impossible to select purposely a better doctor, hospital or therapy. Even providers of care are not always sure about the exact diagnosis, resulting in the extended length of patient's stay and its related costs.
From the knowledge engineering point of view, the national market of healthcare services is a platform where distributed micro behavior of patients interacts with centralized, systemic activities of medical care and insurance providers under the umbrella of governmental rules. Owing to the problem complexity, a significant portion of included subjectivity and natural heterogeneity of available knowledge, the authors have adopted a combined modeling platform as the most natural way of its formalization and processing. Typical groups of patients are represented as multi‐state agents, adjusting reactions and preferences quickly in accordance with time, changing environment and quality of accessible information. Hospitals, on the contrary, are considered as system dynamic enterprises with domain‐tailored processes both on operational and managerial levels.
The first interesting outcome is the clear experimental evidence, justifying the impossibility of purely market‐driven control and development of a national healthcare system. Furthermore, the paper presents a novelty heterogeneous model as a viable tool for analysis of emergent market behavior enabling evaluation of different public health policies.
The developed model can serve both policy makers and hospital managers. To the former it can experimentally help to investigate the influence of parametric changes of overall market regulations. The latter can benefit especially from optimization of internal processes, leading both to performance and competitive advantage improvements. Moreover, due to its transparency and interactivity, the method of heterogeneous modeling is ideal for strategic planning, group decision making, capturing and sharing of organizational knowledge or organizational learning. Finally, the implementation flexibility and architectural scalability predetermines combined modeling as a convenient technique for rapid prototyping of complex problems.
This paper combines areas of health economics, enterprise management and computational economics in a challenging and innovative way. The value of the proposed research methods relies on the application of a heterogeneous paradigm in multiple perspectives – not only by combining the agent‐based models with system dynamics approach, but also by combining and evaluating alternative approaches to representing agents' state and knowledge.
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