The chapter presents decision support systems in medicine, their basic principles, and structure. From the point of view of patient safety, the decision support systems can bring new unexpected sources of errors, which must be anticipated at the design, implementation, and validation stages. Nevertheless, a safe and easy-to-use system can greatly improve the quality of determining the diagnosis, prognosis, and therapy in healthcare. The authors of this chapter concentrate on the contribution of decision support systems to patient safety and on their potential to future contributions. A decision support system requires a user-friendly interface with the electronic health record and information system within the healthcare facility. The authors also present two examples of decision support systems from the genetics research.
TopBackground
Healthcare requires reliable information as a basis for medical decision making. However, the concept of information is often used without a careful specification of its meaning, which has been changing throughout the history. In general, it describes such facts, events, things, persons, ideas or concepts, which reflect certain real or abstract objects or processes. Information usually consists of a syntactic (structure), semantic (meaning) and pragmatic (aim, purpose) component. Data and knowledge are two main sources to get information for decision support systems (Zvárová, Veselý & Vajda, 2009).
Decision making can be described as a process of selecting an activity or series of activities among several alternatives. Decision making integrates uncertainty as one of the aspects with an influence on the outcome. Medical decision making is one of concepts of e3-health (Zvárová & Zvára, 2011). In medicine, the physician solves the task of medical decision making based on data and knowledge connected to the cognition and determination of diagnosis, therapy and prognosis.
Decision support systems are very complicated systems offering assistance with the decision making process. In a general context, they are capable to solve a variety of complex tasks, to analyze different information components, to extract information of different types, and deduce conclusions from them. In medicine, they compare different possibilities for the diagnosis, therapy or prognosis in terms of their risk. Thus, they represent an inherent tool of e-health technologies for diagnostic and prognostic purposes capable to help during the therapy. The search for the appropriate therapy is very complex and depends on many factors and only a few decision support systems aiming at therapy have been sufficiently evaluated up to now. In practice there exist specialized decision support systems for diagnosis and therapy in invididual medicine fields and also specialized prescribing decision support systems. There has been less attention paid to decision support systems for prognosis, while there are still obstacles to apply decision support systems in healthcare routinely, although diagnostics and therapy would greatly benefit from reliable interdisciplinary and multidisciplinary systems.