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Med Inform (Lond). 1996 Jul-Sep;21(3):179-97.

Computer-based clinical decision aids. A review of methods and assessment of systems.

Author information

  • International School of Hepatology GISH, Faculty of Medicine, State University Groningen, The Netherlands.

Abstract

During the last three decades a great deal of research has been devoted to the development of integrated clinical decision support systems. This report aims to give a basic understanding of what is required for such a system. By means of a large literature study a survey is given of the major components of computer-based clinical aid systems. The main approaches and several aspects of evaluation of such programs are described. The computer has several inherent capabilities which are suitable for medical problem solving and can help in the formalization of medical knowledge. The components of such systems include the computer database, the reasoning engine and the user interface. The different approaches on which the reasoning engine is built are based on manipulation of information and advocate the use of knowledge to construct a solution to a problem. The information in the mode vary from data-intensive to knowledge-intensive. Assessment of decision support systems is a very important phase in the development of such systems. Evaluation should be made on the accuracy of the program, the nature of the system, the use of the data and the acceptance by the target users. Whatever the model is, its effectiveness will depend on the data with which the program has to work. Acceptance by physicians depends among other things on ease of use of the user interface. Profound changes in the delivery of health care will be induced through the rapid growth of on-line computer communication together with the development of integrated clinical decision support systems and electronic medical records. Notwithstanding the rapid growth of computer technology, computer-aided decision making is in its infancy and real support in daily practice is not yet achieved.

PMID:
9062881
[PubMed - indexed for MEDLINE]
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