Development and Implementation of Clincal Decision Support System: Success and Risk Factors

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-48 Number-4
Year of Publication : 2017
Authors : Kholood M. Al Motairi, Tahani F. Al shareef


Kholood M. Al Motairi, Tahani F. Al shareef "Development and Implementation of Clincal Decision Support System: Success and Risk Factors". International Journal of Computer Trends and Technology (IJCTT) V48(4):181-188, June 2017. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Decision support systems (DSSs) are used to assist in the design making process and sometimes replace the decision-maker role. DSSs are implemented in different fields, and one of them is the healthcare field. The clinical decision support system (CDSS) is one of the implementations of DSS in the field of healthcare. In this paper, we will investigate the success and the risk factors that come from adopting CDSS. Thus, studies in the performance measurement of implementing CDSS either in real-life case study or in experimental ways will be presented to show the positive impact resulting from adopting such a system.

[1] J. P. Shim, M. Warkentin, J. F. Courtney, D. J. Power, R. Sharda, and C. Carlsson, “Past, present, and future of decision support technology,"Decision support systems, vol. 33, no. 2, pp. 111-126, 2002.
[2] M. R. Rahim, S. Nordin, and R. M. Linden, “ Machine learning-based clinical decision support system for early diagnosis from real-timephysiological data,”in Region 10 Conference (TENCON), 2016 IEEE, pp. 2943-2946, IEEE, 2016.
[3] N. R. Rahim, S. Nordin, and R. M. Dom, “Review on barriers and considerations of clinical decision support system for medication prescribing,”in Research and Development (SCOReD), 2015 IEEE Student Conference on, pp. 489-494, IEEE, 2015.
[4] A. Abdullah, K. S. Albeladi, and R. F. AlCattan, “Clinical decision support system in healthcare industry success and risk factors,”IJCTT, 2014.
[5] S. P. N. Prabhu Murugesan and L. Karthigeyan, “Clinical decision support systems,”CSC PAPERS, 2014.
[6] H. Liu, H. Hu, Q. Chen, F. Yu, and Y. Liu, “Application of the clinicaldecision support systems in the management of chronic diseases,” in Systems and Informatics (ICSAI), 2016 3rd International Conference on, pp. 482-486, IEEE, 2016.
[7] E. S. Berner, “Clinical decision support systems: state of the art,” AHRQ publication, vol. 90069, 2009.
[8] E. S. Berner and T. J. La Lande, “Overview of clinical decision supportsystems,” in Clinical decision support systems, pp. 1-17, Springer, 2016.
[9] A. Ebadi, P. J. Tighe, L. Zhang, and P. Rashidi, “Disteam: A decision support tool for surgical team selection,” Artificial Intelligence in Medicine, vol. 76, pp. 16-26, 2017.
[10] K. Kawamoto, C. A. Houlihan, E. A. Balas, and D. F. Lobach, “Improving clinical practice using clinical decision support systems: a systematicreview of trials to identify features critical to success,”Bmj, vol. 330,no. 7494, p. 765, 2005.
[11] K. Gayathri and K. Easwarakumar, “Intelligent decision support systemfor dementia care through smart home,” Procedia Computer Science,vol. 93, pp. 947-955, 2016.
[12] W. P. Goh, X. Tao, J. Zhang, and J. Yong, “Decision support systemsfor adoption in dental clinics: A survey,” Knowledge-Based Systems,vol. 104, pp. 195-206, 2016.
[13] M. B. Ayed, H. Lti_, C. Kolski, and A. M. Alimi, “A user-centeredapproach for the design and implementation of kdd-based dss: A casestudy in the healthcare domain,” Decision Support Systems, vol. 50,no. 1, pp. 64-78, 2010.
[14] B. Thanathornwong, S. Suebnukarn, and K. Ouivirach, “Decision support system for predicting color change after tooth whitening,” Computer methods and programs in biomedicine, vol. 125, pp. 88-93, 2016.
[15] S. Shilaskar, A. Ghatol, and P. Chatur, “Medical decision support system for extremely imbalanced datasets,” Information Sciences, vol. 384,pp. 205-219, 2017.

Clinical Decision Support System, Healthcare, Decision Support System, CDSS Development.