Aspects of Clinical Decision Support Systems

The envisioned role of computer programs in health care is perhaps the most important. Everything we know today in medicine might not have been possible without the valuable contribution of computers. Medical knowledge in modern health care is vast and constantly changing, as well as expanding. The provisioning of Clinical Decision Support Systems (CDSSs) would enable the discovery of patterns in health data which might be important for the fight against incorrect diagnosis. Medicine uses empirical knowledge about superficial associations between symptoms and diseases. Uncertainty is a central, critical fact about medical reasoning. Many of intelligent CDSSs are based on the fuzzy set theory, which describes medical complex systems mathematical model in terms of linguistic rules. Considering the fuzzy nature of the data in a medical environment, it becomes obvious that the ability of managing uncertainty turns to be a crucial issue for CDSSs. Since the potential of medical decision making was first realized, hundreds of articles introducing CDSSs have been published in the last three decades. But even today, only few systems are in clinical use. Even fewer are in use outside their site of origin. This paper addresses, works out advantages and disadvantages of several approaches and compares them against possible alternatives. Finally, experiences, gained by clinical use of two introduced systems, are used to analyze the little use of CDSSs in today's clinical routine practice.