Clinical decision support system in medical knowledge literature review

Junggi Yang (), Ungu Kang () and Youngho Lee ()
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Junggi Yang: Gachon University
Ungu Kang: Gachon University
Youngho Lee: Gachon University

Information Technology and Management, 2016, vol. 17, issue 1, No 2, 5-14

Abstract: Abstract The current study involved methodology and content analyses of abstracts of 30 clinical decision support system (CDSS) related studies with high impact factors. The main aim of the current work was to identify the performance and efficiency of CDSS, and enhance the understanding of CDSS for a better health management among the physicians and the patients. To add structure to the current study, major research areas were categorized based on a multidimensional unfolding analysis. In this regard, eight studies were conducted based on theoretical research, ten studies were related to the system and performance of CDSS, and 12 studies verified the efficacy through analysis and evaluation of CDSS. The results indicated that the above-mentioned studies on improvement in systematic performance. Then, based on the improvement, effectively used evaluations were conducted comparably. Moreover, 14 studies analyzed patients’ data and assessed decision support system (DSS). The related findings denoted that DSS has been mainly used for patient management and a large number of studies have verified its effectiveness, using several data to ensure its accuracy and reliability. In addition, the analyzed results of the abstracts and the titles were compared to find whether the titles of the literature articles reveal their content. Using these methodological studies, the academic outlook of medical informatics could be forecasted and the academic quality could be improved by resolving the problems, arising out of system development and realization processes. Such problems can be solved through analyses and interpretation of multilateral parameters, such as the trend in academic development, research direction, topics and methods.

Keywords: Decision support; Clinical decision support system; Expert system; Knowledge system; Medical knowledge (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10799-015-0216-6

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